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autoware_planning_validator_rear_collision_checker package from autoware_universe repo

autoware_agnocast_wrapper autoware_auto_common autoware_boundary_departure_checker autoware_component_interface_specs_universe autoware_component_interface_tools autoware_component_interface_utils autoware_cuda_dependency_meta autoware_fake_test_node autoware_glog_component autoware_goal_distance_calculator autoware_grid_map_utils autoware_path_distance_calculator autoware_polar_grid autoware_time_utils autoware_traffic_light_recognition_marker_publisher autoware_traffic_light_utils autoware_universe_utils tier4_api_utils autoware_autonomous_emergency_braking autoware_collision_detector autoware_control_command_gate autoware_control_performance_analysis autoware_control_validator autoware_external_cmd_selector autoware_joy_controller autoware_lane_departure_checker autoware_mpc_lateral_controller autoware_obstacle_collision_checker autoware_operation_mode_transition_manager autoware_pid_longitudinal_controller autoware_predicted_path_checker autoware_pure_pursuit autoware_shift_decider autoware_smart_mpc_trajectory_follower autoware_stop_mode_operator autoware_trajectory_follower_base autoware_trajectory_follower_node autoware_vehicle_cmd_gate autoware_control_evaluator autoware_kinematic_evaluator autoware_localization_evaluator autoware_perception_online_evaluator autoware_planning_evaluator autoware_scenario_simulator_v2_adapter autoware_diagnostic_graph_test_examples tier4_autoware_api_launch tier4_control_launch tier4_localization_launch tier4_map_launch tier4_perception_launch tier4_planning_launch tier4_sensing_launch tier4_simulator_launch tier4_system_launch tier4_vehicle_launch autoware_geo_pose_projector autoware_ar_tag_based_localizer autoware_landmark_manager autoware_lidar_marker_localizer autoware_localization_error_monitor autoware_pose2twist autoware_pose_covariance_modifier autoware_pose_estimator_arbiter autoware_pose_instability_detector yabloc_common yabloc_image_processing yabloc_monitor yabloc_particle_filter yabloc_pose_initializer autoware_map_tf_generator autoware_bevfusion autoware_bytetrack autoware_cluster_merger autoware_compare_map_segmentation autoware_crosswalk_traffic_light_estimator autoware_detected_object_feature_remover autoware_detected_object_validation autoware_detection_by_tracker autoware_elevation_map_loader autoware_euclidean_cluster autoware_ground_segmentation autoware_image_projection_based_fusion autoware_lidar_apollo_instance_segmentation autoware_lidar_centerpoint autoware_lidar_transfusion autoware_map_based_prediction autoware_multi_object_tracker autoware_object_merger autoware_object_range_splitter autoware_object_sorter autoware_object_velocity_splitter autoware_occupancy_grid_map_outlier_filter autoware_probabilistic_occupancy_grid_map autoware_radar_fusion_to_detected_object autoware_radar_object_tracker autoware_radar_tracks_msgs_converter autoware_raindrop_cluster_filter autoware_shape_estimation autoware_simpl_prediction autoware_simple_object_merger autoware_tensorrt_bevdet autoware_tensorrt_classifier autoware_tensorrt_common autoware_tensorrt_plugins autoware_tensorrt_yolox autoware_tracking_object_merger autoware_traffic_light_arbiter autoware_traffic_light_category_merger autoware_traffic_light_classifier autoware_traffic_light_fine_detector autoware_traffic_light_map_based_detector autoware_traffic_light_multi_camera_fusion autoware_traffic_light_occlusion_predictor autoware_traffic_light_selector autoware_traffic_light_visualization perception_utils autoware_costmap_generator autoware_diffusion_planner autoware_external_velocity_limit_selector autoware_freespace_planner autoware_freespace_planning_algorithms autoware_hazard_lights_selector autoware_mission_planner_universe autoware_path_optimizer autoware_path_smoother autoware_remaining_distance_time_calculator autoware_rtc_interface autoware_scenario_selector autoware_surround_obstacle_checker autoware_behavior_path_avoidance_by_lane_change_module autoware_behavior_path_bidirectional_traffic_module autoware_behavior_path_dynamic_obstacle_avoidance_module autoware_behavior_path_external_request_lane_change_module autoware_behavior_path_goal_planner_module autoware_behavior_path_lane_change_module autoware_behavior_path_planner autoware_behavior_path_planner_common autoware_behavior_path_sampling_planner_module autoware_behavior_path_side_shift_module autoware_behavior_path_start_planner_module autoware_behavior_path_static_obstacle_avoidance_module autoware_behavior_velocity_blind_spot_module autoware_behavior_velocity_crosswalk_module autoware_behavior_velocity_detection_area_module autoware_behavior_velocity_intersection_module autoware_behavior_velocity_no_drivable_lane_module autoware_behavior_velocity_no_stopping_area_module autoware_behavior_velocity_occlusion_spot_module autoware_behavior_velocity_rtc_interface autoware_behavior_velocity_run_out_module autoware_behavior_velocity_speed_bump_module autoware_behavior_velocity_template_module autoware_behavior_velocity_traffic_light_module autoware_behavior_velocity_virtual_traffic_light_module autoware_behavior_velocity_walkway_module autoware_motion_velocity_boundary_departure_prevention_module autoware_motion_velocity_dynamic_obstacle_stop_module autoware_motion_velocity_obstacle_cruise_module autoware_motion_velocity_obstacle_slow_down_module autoware_motion_velocity_obstacle_velocity_limiter_module autoware_motion_velocity_out_of_lane_module autoware_motion_velocity_road_user_stop_module autoware_motion_velocity_run_out_module autoware_planning_validator autoware_planning_validator_intersection_collision_checker autoware_planning_validator_latency_checker autoware_planning_validator_rear_collision_checker autoware_planning_validator_test_utils autoware_planning_validator_trajectory_checker autoware_bezier_sampler autoware_frenet_planner autoware_path_sampler autoware_sampler_common autoware_cuda_pointcloud_preprocessor autoware_cuda_utils autoware_image_diagnostics autoware_image_transport_decompressor autoware_imu_corrector autoware_pcl_extensions autoware_pointcloud_preprocessor autoware_radar_objects_adapter autoware_radar_scan_to_pointcloud2 autoware_radar_static_pointcloud_filter autoware_radar_threshold_filter autoware_radar_tracks_noise_filter autoware_livox_tag_filter autoware_carla_interface autoware_dummy_perception_publisher autoware_fault_injection autoware_learning_based_vehicle_model autoware_simple_planning_simulator autoware_vehicle_door_simulator tier4_dummy_object_rviz_plugin autoware_bluetooth_monitor autoware_command_mode_decider autoware_command_mode_decider_plugins autoware_command_mode_switcher autoware_command_mode_switcher_plugins autoware_command_mode_types autoware_component_monitor autoware_component_state_monitor autoware_adapi_visualizers autoware_automatic_pose_initializer autoware_default_adapi_universe autoware_diagnostic_graph_aggregator autoware_diagnostic_graph_utils autoware_dummy_diag_publisher autoware_dummy_infrastructure autoware_duplicated_node_checker autoware_hazard_status_converter autoware_mrm_comfortable_stop_operator autoware_mrm_emergency_stop_operator autoware_mrm_handler autoware_pipeline_latency_monitor autoware_processing_time_checker autoware_system_monitor autoware_topic_relay_controller autoware_topic_state_monitor autoware_velodyne_monitor reaction_analyzer autoware_accel_brake_map_calibrator autoware_external_cmd_converter autoware_raw_vehicle_cmd_converter autoware_steer_offset_estimator autoware_bag_time_manager_rviz_plugin autoware_traffic_light_rviz_plugin tier4_adapi_rviz_plugin tier4_camera_view_rviz_plugin tier4_control_mode_rviz_plugin tier4_datetime_rviz_plugin tier4_perception_rviz_plugin tier4_planning_factor_rviz_plugin tier4_state_rviz_plugin tier4_system_rviz_plugin tier4_traffic_light_rviz_plugin tier4_vehicle_rviz_plugin

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github

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Package Summary

Tags No category tags.
Version 0.47.0
License Apache License 2.0
Build type AMENT_CMAKE
Use RECOMMENDED

Repository Summary

Description
Checkout URI https://github.com/autowarefoundation/autoware_universe.git
VCS Type git
VCS Version main
Last Updated 2025-08-16
Dev Status UNKNOWN
Released UNRELEASED
Tags planner ros calibration self-driving-car autonomous-driving autonomous-vehicles ros2 3d-map autoware
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

The autoware_planning_validator_rear_collision_checker package

Additional Links

No additional links.

Maintainers

  • Satoshi Ota
  • Alqudah Mohammad
  • kyoichi sugahara
  • Maxime Clement

Authors

  • Satoshi Ota
planning/planning_validator/autoware_planning_validator_rear_collision_checker/README.md

Rear Collision Checker

The rear_collision_checker is a plugin module of the autoware_planning_validator node. It validates the planned trajectory by verifying that it does not lead to a collision with other road users (primarily vehicles, but also pedestrian/cyclists/motorcycles) approaching from lateral/rear directions. In particular, it is designed to detect potential rear-end collisions and entrapment risks when the ego vehicle is making a right/left turn or merging into an adjacent lane.

Inner Workings

The module operates by:

  1. Identifying conflict lanes
    • Uses the current route and lanelet topology to determine lanes that the ego vehicle’s trajectory may intersect with during right/left turns or lane changes.
    • Focuses on lanes where vehicles, bicycles, or motorcycles could approach from behind or from a lateral direction, posing a potential rear-end or entrapment risk.
    • Considers the turn_direction of the approaching lanelets to filter out irrelevant lanes.
  2. Filtering perception data
    • Subscribes to obstacle pointcloud and first filters by the conflict region, keeping only points that fall within relevant spatial bounds.
    • Performs clustering on the filtered points to form obstacle candidates.
    • Associates clusters with nearby lanelets and computes the nearest face of each obstacle along the lane direction.
    • Applies configurable range gates (forward/backward, lateral, height) and basic outlier rejection to discard distant or irrelevant clusters.
  3. Estimating motion
    • For each selected object, determines its motion relative to the lane direction.
    • Estimates speed and direction based on frame-to-frame position changes along the lane’s centerline.
    • Maintains a per-lane tracking list to stabilize velocity estimation and reduce noise from perception flicker.
  4. Calculating metrics
    • Depending on the selected metric (e.g., TTC, RSS), the calculation method and decision logic differ. The chosen metric is computed, and the result is used to determine whether there is a potential collision risk.
  5. Judging collision risk
    • Evaluates the selected metric results against predefined thresholds to determine whether a collision is likely.
    • Applies hysteresis logic:
      • on_time_buffer: Hazardous state must persist for this duration before marking the trajectory unsafe.
      • off_time_buffer: Safe state must persist for this duration before clearing the unsafe flag.
    • If check_on_unstoppable=false, the module will skip collision warnings in cases where the ego vehicle cannot realistically stop before the conflict area (to prevent unnecessary alerts when stopping is already infeasible).

Flowchart

WIP

General Parameters

Name Unit Type Description Default value
on_time_buffer [s] double Time buffer before enabling detection after a relevant condition is met 0.5
off_time_buffer [s] double Time buffer before disabling detection after the condition clears 1.5
check_on_unstoppable [-] bool If true, the module continues collision checking even when the ego vehicle cannot stop before entering a potential collision area, and outputs an ERROR if a collision risk is detected. If false, checking is skipped in such cases to avoid unnecessary warnings. false

Pointcloud Preprocess

Name Unit Type Description Default value
pointcloud.range.dead_zone [m] double Distance in front of the ego vehicle ignored for collision detection 0.3
pointcloud.range.buffer [m] double Additional margin around detection range 1.0
pointcloud.crop_box_filter.x.max [m] double Maximum X coordinate for cropped detection range 30.0
pointcloud.crop_box_filter.x.min [m] double Minimum X coordinate for cropped detection range -100.0
pointcloud.crop_box_filter.z.max [m] double Maximum Z coordinate for cropped detection range -1.0
pointcloud.crop_box_filter.z.min [m] double Minimum Z coordinate for cropped detection range 0.3
pointcloud.voxel_grid_filter.x [m] double Voxel grid filter size in X direction 0.1
pointcloud.voxel_grid_filter.y [m] double Voxel grid filter size in Y direction 0.1
pointcloud.voxel_grid_filter.z [m] double Voxel grid filter size in Z direction 0.5
pointcloud.clustering.cluster_tolerance [m] double Maximum distance between points to be considered part of the same cluster 0.15
pointcloud.clustering.min_cluster_height [m] double Minimum height of a cluster to be considered valid 0.1
pointcloud.clustering.min_cluster_size [points] int Minimum number of points in a valid cluster 5
pointcloud.clustering.max_cluster_size [points] int Maximum number of points in a valid cluster 10000
pointcloud.velocity_estimation.observation_time [s] double Time window used for velocity estimation 0.3
pointcloud.velocity_estimation.max_acceleration [m/s^2] double Maximum allowed acceleration in velocity estimation 10.0
pointcloud.latency [s] double Assumed system latency for point cloud processing 0.3

Object Filtering

Name Unit Type Description Default value
filter.min_velocity [m/s] double Minimum velocity threshold for objects to be considered moving 1.0
filter.moving_time [s] double Minimum time duration an object must be moving to be considered as such 0.5

TTC

Name Unit Type Description Default value
time_to_collision.margin [s] double Additional margin added to time-to-collision calculation 2.0

Ego Behavior

Name Unit Type Description Default value
ego.reaction_time [s] double Reaction time of the ego vehicle 1.2
ego.min_velocity [m/s] double Minimum considered velocity of the ego vehicle 1.38
ego.max_velocity [m/s] double Maximum considered velocity of the ego vehicle 16.6
ego.max_acceleration [m/s^2] double Maximum considered acceleration of the ego vehicle 1.5
ego.max_deceleration [m/s^2] double Maximum considered deceleration of the ego vehicle (negative value) -4.0
ego.max_positive_jerk [m/s^3] double Maximum allowed positive jerk for the ego vehicle 5.0
ego.max_negative_jerk [m/s^3] double Maximum allowed negative jerk for the ego vehicle -5.0
ego.nominal_deceleration [m/s^2] double Nominal deceleration used for calculations -1.5
ego.nominal_positive_jerk [m/s^3] double Nominal positive jerk used for calculations 0.6
ego.nominal_negative_jerk [m/s^3] double Nominal negative jerk used for calculations -0.6

Collision Check For Blind Spot

Name Unit Type Description Default value
blind_spot.lookahead_time [s] double Lookahead time for blind spot detection 4.0

File truncated at 100 lines see the full file

CHANGELOG

Changelog for package autoware_planning_validator_rear_collision_checker

0.47.0 (2025-08-11)

  • feat(rear_collision_checker): support selecting safety metric from TTC or RSS (#11072)

    • fix: return distance to predicted collision point
    • refactor: move to utils
    • refactor: move to utils
    • refactor: generalize function
    • feat: selectable metric
    • chore: rename variable for readability

    * refactor: not use lambda ---------

  • refactor(planning_validator): refactor planning validator configuration and error handling (#11081)

    • refactor trajectory check error handling
    • define set_diag_status function for each module locally

    * update documentation ---------

  • style(pre-commit): update to clang-format-20 (#11088) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

  • refactor(rear_collision_checker): update parameter structure (#11067)

    • refactor(rear_collision_checker): update parameter structure

    * chore: remove unused msg type ---------

  • chore(rear_collision_checker): add maintainer (#11069)

  • feat(rear_collision_checker): improve collision detection logic (#10992)

    • feat(rear_collision_checker): added a parameter to configure how many seconds ahead to predict collisions

    * feat(rear_collision_checker): add parameter to enable collision check for forward obstacles ---------

  • feat(intersection_collision_checker): improve icc debug markers (#10967)

    • add DebugData struct
    • refactor and publish debug info and markers
    • always publish lanelet debug markers
    • refactor debug markers code
    • remove unused functions
    • pass string by reference
    • set is_safe flag for rear_collision_checker debug data
    • fix for cpp check

    * add maintainer ---------

  • feat(intersection_collision_checker): improve feature to reduce false positive occurrence (#10899)

    • keep a map of already detected target lanelets
    • fix on/off time buffers logic
    • add debug marker to visualize colliding object
    • use resampled trajectory instead of raw trajectory
    • fix overlap index computation
    • fix on/off time buffers logic for rear collision checker
    • fix planning .pages file, fix format
    • update readme
    • ignore not moving pcd object

    * handle case when object is very close to overlap point ---------

  • feat(planning_validator): improve intersection collision checker implementation (#10839)

    • use parameter generator library
    • add pointcloud latency compensation
    • change msg field name
    • add readme file
    • add parameters dection to readme
    • publish planning factor for intersection_collision_checker
    • refactor lanelet selection and filtering
    • update readme
    • set safety factor array in planning factor
    • clean up includes
    • publish planning factor for rear collision checker
    • fix spelling
    • rename variables to avoid shadowing

    * Update

File truncated at 100 lines see the full file

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autoware_planning_validator_rear_collision_checker package from autoware_universe repo

autoware_agnocast_wrapper autoware_auto_common autoware_boundary_departure_checker autoware_component_interface_specs_universe autoware_component_interface_tools autoware_component_interface_utils autoware_cuda_dependency_meta autoware_fake_test_node autoware_glog_component autoware_goal_distance_calculator autoware_grid_map_utils autoware_path_distance_calculator autoware_polar_grid autoware_time_utils autoware_traffic_light_recognition_marker_publisher autoware_traffic_light_utils autoware_universe_utils tier4_api_utils autoware_autonomous_emergency_braking autoware_collision_detector autoware_control_command_gate autoware_control_performance_analysis autoware_control_validator autoware_external_cmd_selector autoware_joy_controller autoware_lane_departure_checker autoware_mpc_lateral_controller autoware_obstacle_collision_checker autoware_operation_mode_transition_manager autoware_pid_longitudinal_controller autoware_predicted_path_checker autoware_pure_pursuit autoware_shift_decider autoware_smart_mpc_trajectory_follower autoware_stop_mode_operator autoware_trajectory_follower_base autoware_trajectory_follower_node autoware_vehicle_cmd_gate autoware_control_evaluator autoware_kinematic_evaluator autoware_localization_evaluator autoware_perception_online_evaluator autoware_planning_evaluator autoware_scenario_simulator_v2_adapter autoware_diagnostic_graph_test_examples tier4_autoware_api_launch tier4_control_launch tier4_localization_launch tier4_map_launch tier4_perception_launch tier4_planning_launch tier4_sensing_launch tier4_simulator_launch tier4_system_launch tier4_vehicle_launch autoware_geo_pose_projector autoware_ar_tag_based_localizer autoware_landmark_manager autoware_lidar_marker_localizer autoware_localization_error_monitor autoware_pose2twist autoware_pose_covariance_modifier autoware_pose_estimator_arbiter autoware_pose_instability_detector yabloc_common yabloc_image_processing yabloc_monitor yabloc_particle_filter yabloc_pose_initializer autoware_map_tf_generator autoware_bevfusion autoware_bytetrack autoware_cluster_merger autoware_compare_map_segmentation autoware_crosswalk_traffic_light_estimator autoware_detected_object_feature_remover autoware_detected_object_validation autoware_detection_by_tracker autoware_elevation_map_loader autoware_euclidean_cluster autoware_ground_segmentation autoware_image_projection_based_fusion autoware_lidar_apollo_instance_segmentation autoware_lidar_centerpoint autoware_lidar_transfusion autoware_map_based_prediction autoware_multi_object_tracker autoware_object_merger autoware_object_range_splitter autoware_object_sorter autoware_object_velocity_splitter autoware_occupancy_grid_map_outlier_filter autoware_probabilistic_occupancy_grid_map autoware_radar_fusion_to_detected_object autoware_radar_object_tracker autoware_radar_tracks_msgs_converter autoware_raindrop_cluster_filter autoware_shape_estimation autoware_simpl_prediction autoware_simple_object_merger autoware_tensorrt_bevdet autoware_tensorrt_classifier autoware_tensorrt_common autoware_tensorrt_plugins autoware_tensorrt_yolox autoware_tracking_object_merger autoware_traffic_light_arbiter autoware_traffic_light_category_merger autoware_traffic_light_classifier autoware_traffic_light_fine_detector autoware_traffic_light_map_based_detector autoware_traffic_light_multi_camera_fusion autoware_traffic_light_occlusion_predictor autoware_traffic_light_selector autoware_traffic_light_visualization perception_utils autoware_costmap_generator autoware_diffusion_planner autoware_external_velocity_limit_selector autoware_freespace_planner autoware_freespace_planning_algorithms autoware_hazard_lights_selector autoware_mission_planner_universe autoware_path_optimizer autoware_path_smoother autoware_remaining_distance_time_calculator autoware_rtc_interface autoware_scenario_selector autoware_surround_obstacle_checker autoware_behavior_path_avoidance_by_lane_change_module autoware_behavior_path_bidirectional_traffic_module autoware_behavior_path_dynamic_obstacle_avoidance_module autoware_behavior_path_external_request_lane_change_module autoware_behavior_path_goal_planner_module autoware_behavior_path_lane_change_module autoware_behavior_path_planner autoware_behavior_path_planner_common autoware_behavior_path_sampling_planner_module autoware_behavior_path_side_shift_module autoware_behavior_path_start_planner_module autoware_behavior_path_static_obstacle_avoidance_module autoware_behavior_velocity_blind_spot_module autoware_behavior_velocity_crosswalk_module autoware_behavior_velocity_detection_area_module autoware_behavior_velocity_intersection_module autoware_behavior_velocity_no_drivable_lane_module autoware_behavior_velocity_no_stopping_area_module autoware_behavior_velocity_occlusion_spot_module autoware_behavior_velocity_rtc_interface autoware_behavior_velocity_run_out_module autoware_behavior_velocity_speed_bump_module autoware_behavior_velocity_template_module autoware_behavior_velocity_traffic_light_module autoware_behavior_velocity_virtual_traffic_light_module autoware_behavior_velocity_walkway_module autoware_motion_velocity_boundary_departure_prevention_module autoware_motion_velocity_dynamic_obstacle_stop_module autoware_motion_velocity_obstacle_cruise_module autoware_motion_velocity_obstacle_slow_down_module autoware_motion_velocity_obstacle_velocity_limiter_module autoware_motion_velocity_out_of_lane_module autoware_motion_velocity_road_user_stop_module autoware_motion_velocity_run_out_module autoware_planning_validator autoware_planning_validator_intersection_collision_checker autoware_planning_validator_latency_checker autoware_planning_validator_rear_collision_checker autoware_planning_validator_test_utils autoware_planning_validator_trajectory_checker autoware_bezier_sampler autoware_frenet_planner autoware_path_sampler autoware_sampler_common autoware_cuda_pointcloud_preprocessor autoware_cuda_utils autoware_image_diagnostics autoware_image_transport_decompressor autoware_imu_corrector autoware_pcl_extensions autoware_pointcloud_preprocessor autoware_radar_objects_adapter autoware_radar_scan_to_pointcloud2 autoware_radar_static_pointcloud_filter autoware_radar_threshold_filter autoware_radar_tracks_noise_filter autoware_livox_tag_filter autoware_carla_interface autoware_dummy_perception_publisher autoware_fault_injection autoware_learning_based_vehicle_model autoware_simple_planning_simulator autoware_vehicle_door_simulator tier4_dummy_object_rviz_plugin autoware_bluetooth_monitor autoware_command_mode_decider autoware_command_mode_decider_plugins autoware_command_mode_switcher autoware_command_mode_switcher_plugins autoware_command_mode_types autoware_component_monitor autoware_component_state_monitor autoware_adapi_visualizers autoware_automatic_pose_initializer autoware_default_adapi_universe autoware_diagnostic_graph_aggregator autoware_diagnostic_graph_utils autoware_dummy_diag_publisher autoware_dummy_infrastructure autoware_duplicated_node_checker autoware_hazard_status_converter autoware_mrm_comfortable_stop_operator autoware_mrm_emergency_stop_operator autoware_mrm_handler autoware_pipeline_latency_monitor autoware_processing_time_checker autoware_system_monitor autoware_topic_relay_controller autoware_topic_state_monitor autoware_velodyne_monitor reaction_analyzer autoware_accel_brake_map_calibrator autoware_external_cmd_converter autoware_raw_vehicle_cmd_converter autoware_steer_offset_estimator autoware_bag_time_manager_rviz_plugin autoware_traffic_light_rviz_plugin tier4_adapi_rviz_plugin tier4_camera_view_rviz_plugin tier4_control_mode_rviz_plugin tier4_datetime_rviz_plugin tier4_perception_rviz_plugin tier4_planning_factor_rviz_plugin tier4_state_rviz_plugin tier4_system_rviz_plugin tier4_traffic_light_rviz_plugin tier4_vehicle_rviz_plugin

ROS Distro
github

API Docs
Browse Code

Package Summary

Tags No category tags.
Version 0.47.0
License Apache License 2.0
Build type AMENT_CMAKE
Use RECOMMENDED

Repository Summary

Description
Checkout URI https://github.com/autowarefoundation/autoware_universe.git
VCS Type git
VCS Version main
Last Updated 2025-08-16
Dev Status UNKNOWN
Released UNRELEASED
Tags planner ros calibration self-driving-car autonomous-driving autonomous-vehicles ros2 3d-map autoware
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

The autoware_planning_validator_rear_collision_checker package

Additional Links

No additional links.

Maintainers

  • Satoshi Ota
  • Alqudah Mohammad
  • kyoichi sugahara
  • Maxime Clement

Authors

  • Satoshi Ota
planning/planning_validator/autoware_planning_validator_rear_collision_checker/README.md

Rear Collision Checker

The rear_collision_checker is a plugin module of the autoware_planning_validator node. It validates the planned trajectory by verifying that it does not lead to a collision with other road users (primarily vehicles, but also pedestrian/cyclists/motorcycles) approaching from lateral/rear directions. In particular, it is designed to detect potential rear-end collisions and entrapment risks when the ego vehicle is making a right/left turn or merging into an adjacent lane.

Inner Workings

The module operates by:

  1. Identifying conflict lanes
    • Uses the current route and lanelet topology to determine lanes that the ego vehicle’s trajectory may intersect with during right/left turns or lane changes.
    • Focuses on lanes where vehicles, bicycles, or motorcycles could approach from behind or from a lateral direction, posing a potential rear-end or entrapment risk.
    • Considers the turn_direction of the approaching lanelets to filter out irrelevant lanes.
  2. Filtering perception data
    • Subscribes to obstacle pointcloud and first filters by the conflict region, keeping only points that fall within relevant spatial bounds.
    • Performs clustering on the filtered points to form obstacle candidates.
    • Associates clusters with nearby lanelets and computes the nearest face of each obstacle along the lane direction.
    • Applies configurable range gates (forward/backward, lateral, height) and basic outlier rejection to discard distant or irrelevant clusters.
  3. Estimating motion
    • For each selected object, determines its motion relative to the lane direction.
    • Estimates speed and direction based on frame-to-frame position changes along the lane’s centerline.
    • Maintains a per-lane tracking list to stabilize velocity estimation and reduce noise from perception flicker.
  4. Calculating metrics
    • Depending on the selected metric (e.g., TTC, RSS), the calculation method and decision logic differ. The chosen metric is computed, and the result is used to determine whether there is a potential collision risk.
  5. Judging collision risk
    • Evaluates the selected metric results against predefined thresholds to determine whether a collision is likely.
    • Applies hysteresis logic:
      • on_time_buffer: Hazardous state must persist for this duration before marking the trajectory unsafe.
      • off_time_buffer: Safe state must persist for this duration before clearing the unsafe flag.
    • If check_on_unstoppable=false, the module will skip collision warnings in cases where the ego vehicle cannot realistically stop before the conflict area (to prevent unnecessary alerts when stopping is already infeasible).

Flowchart

WIP

General Parameters

Name Unit Type Description Default value
on_time_buffer [s] double Time buffer before enabling detection after a relevant condition is met 0.5
off_time_buffer [s] double Time buffer before disabling detection after the condition clears 1.5
check_on_unstoppable [-] bool If true, the module continues collision checking even when the ego vehicle cannot stop before entering a potential collision area, and outputs an ERROR if a collision risk is detected. If false, checking is skipped in such cases to avoid unnecessary warnings. false

Pointcloud Preprocess

Name Unit Type Description Default value
pointcloud.range.dead_zone [m] double Distance in front of the ego vehicle ignored for collision detection 0.3
pointcloud.range.buffer [m] double Additional margin around detection range 1.0
pointcloud.crop_box_filter.x.max [m] double Maximum X coordinate for cropped detection range 30.0
pointcloud.crop_box_filter.x.min [m] double Minimum X coordinate for cropped detection range -100.0
pointcloud.crop_box_filter.z.max [m] double Maximum Z coordinate for cropped detection range -1.0
pointcloud.crop_box_filter.z.min [m] double Minimum Z coordinate for cropped detection range 0.3
pointcloud.voxel_grid_filter.x [m] double Voxel grid filter size in X direction 0.1
pointcloud.voxel_grid_filter.y [m] double Voxel grid filter size in Y direction 0.1
pointcloud.voxel_grid_filter.z [m] double Voxel grid filter size in Z direction 0.5
pointcloud.clustering.cluster_tolerance [m] double Maximum distance between points to be considered part of the same cluster 0.15
pointcloud.clustering.min_cluster_height [m] double Minimum height of a cluster to be considered valid 0.1
pointcloud.clustering.min_cluster_size [points] int Minimum number of points in a valid cluster 5
pointcloud.clustering.max_cluster_size [points] int Maximum number of points in a valid cluster 10000
pointcloud.velocity_estimation.observation_time [s] double Time window used for velocity estimation 0.3
pointcloud.velocity_estimation.max_acceleration [m/s^2] double Maximum allowed acceleration in velocity estimation 10.0
pointcloud.latency [s] double Assumed system latency for point cloud processing 0.3

Object Filtering

Name Unit Type Description Default value
filter.min_velocity [m/s] double Minimum velocity threshold for objects to be considered moving 1.0
filter.moving_time [s] double Minimum time duration an object must be moving to be considered as such 0.5

TTC

Name Unit Type Description Default value
time_to_collision.margin [s] double Additional margin added to time-to-collision calculation 2.0

Ego Behavior

Name Unit Type Description Default value
ego.reaction_time [s] double Reaction time of the ego vehicle 1.2
ego.min_velocity [m/s] double Minimum considered velocity of the ego vehicle 1.38
ego.max_velocity [m/s] double Maximum considered velocity of the ego vehicle 16.6
ego.max_acceleration [m/s^2] double Maximum considered acceleration of the ego vehicle 1.5
ego.max_deceleration [m/s^2] double Maximum considered deceleration of the ego vehicle (negative value) -4.0
ego.max_positive_jerk [m/s^3] double Maximum allowed positive jerk for the ego vehicle 5.0
ego.max_negative_jerk [m/s^3] double Maximum allowed negative jerk for the ego vehicle -5.0
ego.nominal_deceleration [m/s^2] double Nominal deceleration used for calculations -1.5
ego.nominal_positive_jerk [m/s^3] double Nominal positive jerk used for calculations 0.6
ego.nominal_negative_jerk [m/s^3] double Nominal negative jerk used for calculations -0.6

Collision Check For Blind Spot

Name Unit Type Description Default value
blind_spot.lookahead_time [s] double Lookahead time for blind spot detection 4.0

File truncated at 100 lines see the full file

CHANGELOG

Changelog for package autoware_planning_validator_rear_collision_checker

0.47.0 (2025-08-11)

  • feat(rear_collision_checker): support selecting safety metric from TTC or RSS (#11072)

    • fix: return distance to predicted collision point
    • refactor: move to utils
    • refactor: move to utils
    • refactor: generalize function
    • feat: selectable metric
    • chore: rename variable for readability

    * refactor: not use lambda ---------

  • refactor(planning_validator): refactor planning validator configuration and error handling (#11081)

    • refactor trajectory check error handling
    • define set_diag_status function for each module locally

    * update documentation ---------

  • style(pre-commit): update to clang-format-20 (#11088) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

  • refactor(rear_collision_checker): update parameter structure (#11067)

    • refactor(rear_collision_checker): update parameter structure

    * chore: remove unused msg type ---------

  • chore(rear_collision_checker): add maintainer (#11069)

  • feat(rear_collision_checker): improve collision detection logic (#10992)

    • feat(rear_collision_checker): added a parameter to configure how many seconds ahead to predict collisions

    * feat(rear_collision_checker): add parameter to enable collision check for forward obstacles ---------

  • feat(intersection_collision_checker): improve icc debug markers (#10967)

    • add DebugData struct
    • refactor and publish debug info and markers
    • always publish lanelet debug markers
    • refactor debug markers code
    • remove unused functions
    • pass string by reference
    • set is_safe flag for rear_collision_checker debug data
    • fix for cpp check

    * add maintainer ---------

  • feat(intersection_collision_checker): improve feature to reduce false positive occurrence (#10899)

    • keep a map of already detected target lanelets
    • fix on/off time buffers logic
    • add debug marker to visualize colliding object
    • use resampled trajectory instead of raw trajectory
    • fix overlap index computation
    • fix on/off time buffers logic for rear collision checker
    • fix planning .pages file, fix format
    • update readme
    • ignore not moving pcd object

    * handle case when object is very close to overlap point ---------

  • feat(planning_validator): improve intersection collision checker implementation (#10839)

    • use parameter generator library
    • add pointcloud latency compensation
    • change msg field name
    • add readme file
    • add parameters dection to readme
    • publish planning factor for intersection_collision_checker
    • refactor lanelet selection and filtering
    • update readme
    • set safety factor array in planning factor
    • clean up includes
    • publish planning factor for rear collision checker
    • fix spelling
    • rename variables to avoid shadowing

    * Update

File truncated at 100 lines see the full file

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

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autoware_agnocast_wrapper autoware_auto_common autoware_boundary_departure_checker autoware_component_interface_specs_universe autoware_component_interface_tools autoware_component_interface_utils autoware_cuda_dependency_meta autoware_fake_test_node autoware_glog_component autoware_goal_distance_calculator autoware_grid_map_utils autoware_path_distance_calculator autoware_polar_grid autoware_time_utils autoware_traffic_light_recognition_marker_publisher autoware_traffic_light_utils autoware_universe_utils tier4_api_utils autoware_autonomous_emergency_braking autoware_collision_detector autoware_control_command_gate autoware_control_performance_analysis autoware_control_validator autoware_external_cmd_selector autoware_joy_controller autoware_lane_departure_checker autoware_mpc_lateral_controller autoware_obstacle_collision_checker autoware_operation_mode_transition_manager autoware_pid_longitudinal_controller autoware_predicted_path_checker autoware_pure_pursuit autoware_shift_decider autoware_smart_mpc_trajectory_follower autoware_stop_mode_operator autoware_trajectory_follower_base autoware_trajectory_follower_node autoware_vehicle_cmd_gate autoware_control_evaluator autoware_kinematic_evaluator autoware_localization_evaluator autoware_perception_online_evaluator autoware_planning_evaluator autoware_scenario_simulator_v2_adapter autoware_diagnostic_graph_test_examples tier4_autoware_api_launch tier4_control_launch tier4_localization_launch tier4_map_launch tier4_perception_launch tier4_planning_launch tier4_sensing_launch tier4_simulator_launch tier4_system_launch tier4_vehicle_launch autoware_geo_pose_projector autoware_ar_tag_based_localizer autoware_landmark_manager autoware_lidar_marker_localizer autoware_localization_error_monitor autoware_pose2twist autoware_pose_covariance_modifier autoware_pose_estimator_arbiter autoware_pose_instability_detector yabloc_common yabloc_image_processing yabloc_monitor yabloc_particle_filter yabloc_pose_initializer autoware_map_tf_generator autoware_bevfusion autoware_bytetrack autoware_cluster_merger autoware_compare_map_segmentation autoware_crosswalk_traffic_light_estimator autoware_detected_object_feature_remover autoware_detected_object_validation autoware_detection_by_tracker autoware_elevation_map_loader autoware_euclidean_cluster autoware_ground_segmentation autoware_image_projection_based_fusion autoware_lidar_apollo_instance_segmentation autoware_lidar_centerpoint autoware_lidar_transfusion autoware_map_based_prediction autoware_multi_object_tracker autoware_object_merger autoware_object_range_splitter autoware_object_sorter autoware_object_velocity_splitter autoware_occupancy_grid_map_outlier_filter autoware_probabilistic_occupancy_grid_map autoware_radar_fusion_to_detected_object autoware_radar_object_tracker autoware_radar_tracks_msgs_converter autoware_raindrop_cluster_filter autoware_shape_estimation autoware_simpl_prediction autoware_simple_object_merger autoware_tensorrt_bevdet autoware_tensorrt_classifier autoware_tensorrt_common autoware_tensorrt_plugins autoware_tensorrt_yolox autoware_tracking_object_merger autoware_traffic_light_arbiter autoware_traffic_light_category_merger autoware_traffic_light_classifier autoware_traffic_light_fine_detector autoware_traffic_light_map_based_detector autoware_traffic_light_multi_camera_fusion autoware_traffic_light_occlusion_predictor autoware_traffic_light_selector autoware_traffic_light_visualization perception_utils autoware_costmap_generator autoware_diffusion_planner autoware_external_velocity_limit_selector autoware_freespace_planner autoware_freespace_planning_algorithms autoware_hazard_lights_selector autoware_mission_planner_universe autoware_path_optimizer autoware_path_smoother autoware_remaining_distance_time_calculator autoware_rtc_interface autoware_scenario_selector autoware_surround_obstacle_checker autoware_behavior_path_avoidance_by_lane_change_module autoware_behavior_path_bidirectional_traffic_module autoware_behavior_path_dynamic_obstacle_avoidance_module autoware_behavior_path_external_request_lane_change_module autoware_behavior_path_goal_planner_module autoware_behavior_path_lane_change_module autoware_behavior_path_planner autoware_behavior_path_planner_common autoware_behavior_path_sampling_planner_module autoware_behavior_path_side_shift_module autoware_behavior_path_start_planner_module autoware_behavior_path_static_obstacle_avoidance_module autoware_behavior_velocity_blind_spot_module autoware_behavior_velocity_crosswalk_module autoware_behavior_velocity_detection_area_module autoware_behavior_velocity_intersection_module autoware_behavior_velocity_no_drivable_lane_module autoware_behavior_velocity_no_stopping_area_module autoware_behavior_velocity_occlusion_spot_module autoware_behavior_velocity_rtc_interface autoware_behavior_velocity_run_out_module autoware_behavior_velocity_speed_bump_module autoware_behavior_velocity_template_module autoware_behavior_velocity_traffic_light_module autoware_behavior_velocity_virtual_traffic_light_module autoware_behavior_velocity_walkway_module autoware_motion_velocity_boundary_departure_prevention_module autoware_motion_velocity_dynamic_obstacle_stop_module autoware_motion_velocity_obstacle_cruise_module autoware_motion_velocity_obstacle_slow_down_module autoware_motion_velocity_obstacle_velocity_limiter_module autoware_motion_velocity_out_of_lane_module autoware_motion_velocity_road_user_stop_module autoware_motion_velocity_run_out_module autoware_planning_validator autoware_planning_validator_intersection_collision_checker autoware_planning_validator_latency_checker autoware_planning_validator_rear_collision_checker autoware_planning_validator_test_utils autoware_planning_validator_trajectory_checker autoware_bezier_sampler autoware_frenet_planner autoware_path_sampler autoware_sampler_common autoware_cuda_pointcloud_preprocessor autoware_cuda_utils autoware_image_diagnostics autoware_image_transport_decompressor autoware_imu_corrector autoware_pcl_extensions autoware_pointcloud_preprocessor autoware_radar_objects_adapter autoware_radar_scan_to_pointcloud2 autoware_radar_static_pointcloud_filter autoware_radar_threshold_filter autoware_radar_tracks_noise_filter autoware_livox_tag_filter autoware_carla_interface autoware_dummy_perception_publisher autoware_fault_injection autoware_learning_based_vehicle_model autoware_simple_planning_simulator autoware_vehicle_door_simulator tier4_dummy_object_rviz_plugin autoware_bluetooth_monitor autoware_command_mode_decider autoware_command_mode_decider_plugins autoware_command_mode_switcher autoware_command_mode_switcher_plugins autoware_command_mode_types autoware_component_monitor autoware_component_state_monitor autoware_adapi_visualizers autoware_automatic_pose_initializer autoware_default_adapi_universe autoware_diagnostic_graph_aggregator autoware_diagnostic_graph_utils autoware_dummy_diag_publisher autoware_dummy_infrastructure autoware_duplicated_node_checker autoware_hazard_status_converter autoware_mrm_comfortable_stop_operator autoware_mrm_emergency_stop_operator autoware_mrm_handler autoware_pipeline_latency_monitor autoware_processing_time_checker autoware_system_monitor autoware_topic_relay_controller autoware_topic_state_monitor autoware_velodyne_monitor reaction_analyzer autoware_accel_brake_map_calibrator autoware_external_cmd_converter autoware_raw_vehicle_cmd_converter autoware_steer_offset_estimator autoware_bag_time_manager_rviz_plugin autoware_traffic_light_rviz_plugin tier4_adapi_rviz_plugin tier4_camera_view_rviz_plugin tier4_control_mode_rviz_plugin tier4_datetime_rviz_plugin tier4_perception_rviz_plugin tier4_planning_factor_rviz_plugin tier4_state_rviz_plugin tier4_system_rviz_plugin tier4_traffic_light_rviz_plugin tier4_vehicle_rviz_plugin

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Package Summary

Tags No category tags.
Version 0.47.0
License Apache License 2.0
Build type AMENT_CMAKE
Use RECOMMENDED

Repository Summary

Description
Checkout URI https://github.com/autowarefoundation/autoware_universe.git
VCS Type git
VCS Version main
Last Updated 2025-08-16
Dev Status UNKNOWN
Released UNRELEASED
Tags planner ros calibration self-driving-car autonomous-driving autonomous-vehicles ros2 3d-map autoware
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

The autoware_planning_validator_rear_collision_checker package

Additional Links

No additional links.

Maintainers

  • Satoshi Ota
  • Alqudah Mohammad
  • kyoichi sugahara
  • Maxime Clement

Authors

  • Satoshi Ota
planning/planning_validator/autoware_planning_validator_rear_collision_checker/README.md

Rear Collision Checker

The rear_collision_checker is a plugin module of the autoware_planning_validator node. It validates the planned trajectory by verifying that it does not lead to a collision with other road users (primarily vehicles, but also pedestrian/cyclists/motorcycles) approaching from lateral/rear directions. In particular, it is designed to detect potential rear-end collisions and entrapment risks when the ego vehicle is making a right/left turn or merging into an adjacent lane.

Inner Workings

The module operates by:

  1. Identifying conflict lanes
    • Uses the current route and lanelet topology to determine lanes that the ego vehicle’s trajectory may intersect with during right/left turns or lane changes.
    • Focuses on lanes where vehicles, bicycles, or motorcycles could approach from behind or from a lateral direction, posing a potential rear-end or entrapment risk.
    • Considers the turn_direction of the approaching lanelets to filter out irrelevant lanes.
  2. Filtering perception data
    • Subscribes to obstacle pointcloud and first filters by the conflict region, keeping only points that fall within relevant spatial bounds.
    • Performs clustering on the filtered points to form obstacle candidates.
    • Associates clusters with nearby lanelets and computes the nearest face of each obstacle along the lane direction.
    • Applies configurable range gates (forward/backward, lateral, height) and basic outlier rejection to discard distant or irrelevant clusters.
  3. Estimating motion
    • For each selected object, determines its motion relative to the lane direction.
    • Estimates speed and direction based on frame-to-frame position changes along the lane’s centerline.
    • Maintains a per-lane tracking list to stabilize velocity estimation and reduce noise from perception flicker.
  4. Calculating metrics
    • Depending on the selected metric (e.g., TTC, RSS), the calculation method and decision logic differ. The chosen metric is computed, and the result is used to determine whether there is a potential collision risk.
  5. Judging collision risk
    • Evaluates the selected metric results against predefined thresholds to determine whether a collision is likely.
    • Applies hysteresis logic:
      • on_time_buffer: Hazardous state must persist for this duration before marking the trajectory unsafe.
      • off_time_buffer: Safe state must persist for this duration before clearing the unsafe flag.
    • If check_on_unstoppable=false, the module will skip collision warnings in cases where the ego vehicle cannot realistically stop before the conflict area (to prevent unnecessary alerts when stopping is already infeasible).

Flowchart

WIP

General Parameters

Name Unit Type Description Default value
on_time_buffer [s] double Time buffer before enabling detection after a relevant condition is met 0.5
off_time_buffer [s] double Time buffer before disabling detection after the condition clears 1.5
check_on_unstoppable [-] bool If true, the module continues collision checking even when the ego vehicle cannot stop before entering a potential collision area, and outputs an ERROR if a collision risk is detected. If false, checking is skipped in such cases to avoid unnecessary warnings. false

Pointcloud Preprocess

Name Unit Type Description Default value
pointcloud.range.dead_zone [m] double Distance in front of the ego vehicle ignored for collision detection 0.3
pointcloud.range.buffer [m] double Additional margin around detection range 1.0
pointcloud.crop_box_filter.x.max [m] double Maximum X coordinate for cropped detection range 30.0
pointcloud.crop_box_filter.x.min [m] double Minimum X coordinate for cropped detection range -100.0
pointcloud.crop_box_filter.z.max [m] double Maximum Z coordinate for cropped detection range -1.0
pointcloud.crop_box_filter.z.min [m] double Minimum Z coordinate for cropped detection range 0.3
pointcloud.voxel_grid_filter.x [m] double Voxel grid filter size in X direction 0.1
pointcloud.voxel_grid_filter.y [m] double Voxel grid filter size in Y direction 0.1
pointcloud.voxel_grid_filter.z [m] double Voxel grid filter size in Z direction 0.5
pointcloud.clustering.cluster_tolerance [m] double Maximum distance between points to be considered part of the same cluster 0.15
pointcloud.clustering.min_cluster_height [m] double Minimum height of a cluster to be considered valid 0.1
pointcloud.clustering.min_cluster_size [points] int Minimum number of points in a valid cluster 5
pointcloud.clustering.max_cluster_size [points] int Maximum number of points in a valid cluster 10000
pointcloud.velocity_estimation.observation_time [s] double Time window used for velocity estimation 0.3
pointcloud.velocity_estimation.max_acceleration [m/s^2] double Maximum allowed acceleration in velocity estimation 10.0
pointcloud.latency [s] double Assumed system latency for point cloud processing 0.3

Object Filtering

Name Unit Type Description Default value
filter.min_velocity [m/s] double Minimum velocity threshold for objects to be considered moving 1.0
filter.moving_time [s] double Minimum time duration an object must be moving to be considered as such 0.5

TTC

Name Unit Type Description Default value
time_to_collision.margin [s] double Additional margin added to time-to-collision calculation 2.0

Ego Behavior

Name Unit Type Description Default value
ego.reaction_time [s] double Reaction time of the ego vehicle 1.2
ego.min_velocity [m/s] double Minimum considered velocity of the ego vehicle 1.38
ego.max_velocity [m/s] double Maximum considered velocity of the ego vehicle 16.6
ego.max_acceleration [m/s^2] double Maximum considered acceleration of the ego vehicle 1.5
ego.max_deceleration [m/s^2] double Maximum considered deceleration of the ego vehicle (negative value) -4.0
ego.max_positive_jerk [m/s^3] double Maximum allowed positive jerk for the ego vehicle 5.0
ego.max_negative_jerk [m/s^3] double Maximum allowed negative jerk for the ego vehicle -5.0
ego.nominal_deceleration [m/s^2] double Nominal deceleration used for calculations -1.5
ego.nominal_positive_jerk [m/s^3] double Nominal positive jerk used for calculations 0.6
ego.nominal_negative_jerk [m/s^3] double Nominal negative jerk used for calculations -0.6

Collision Check For Blind Spot

Name Unit Type Description Default value
blind_spot.lookahead_time [s] double Lookahead time for blind spot detection 4.0

File truncated at 100 lines see the full file

CHANGELOG

Changelog for package autoware_planning_validator_rear_collision_checker

0.47.0 (2025-08-11)

  • feat(rear_collision_checker): support selecting safety metric from TTC or RSS (#11072)

    • fix: return distance to predicted collision point
    • refactor: move to utils
    • refactor: move to utils
    • refactor: generalize function
    • feat: selectable metric
    • chore: rename variable for readability

    * refactor: not use lambda ---------

  • refactor(planning_validator): refactor planning validator configuration and error handling (#11081)

    • refactor trajectory check error handling
    • define set_diag_status function for each module locally

    * update documentation ---------

  • style(pre-commit): update to clang-format-20 (#11088) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

  • refactor(rear_collision_checker): update parameter structure (#11067)

    • refactor(rear_collision_checker): update parameter structure

    * chore: remove unused msg type ---------

  • chore(rear_collision_checker): add maintainer (#11069)

  • feat(rear_collision_checker): improve collision detection logic (#10992)

    • feat(rear_collision_checker): added a parameter to configure how many seconds ahead to predict collisions

    * feat(rear_collision_checker): add parameter to enable collision check for forward obstacles ---------

  • feat(intersection_collision_checker): improve icc debug markers (#10967)

    • add DebugData struct
    • refactor and publish debug info and markers
    • always publish lanelet debug markers
    • refactor debug markers code
    • remove unused functions
    • pass string by reference
    • set is_safe flag for rear_collision_checker debug data
    • fix for cpp check

    * add maintainer ---------

  • feat(intersection_collision_checker): improve feature to reduce false positive occurrence (#10899)

    • keep a map of already detected target lanelets
    • fix on/off time buffers logic
    • add debug marker to visualize colliding object
    • use resampled trajectory instead of raw trajectory
    • fix overlap index computation
    • fix on/off time buffers logic for rear collision checker
    • fix planning .pages file, fix format
    • update readme
    • ignore not moving pcd object

    * handle case when object is very close to overlap point ---------

  • feat(planning_validator): improve intersection collision checker implementation (#10839)

    • use parameter generator library
    • add pointcloud latency compensation
    • change msg field name
    • add readme file
    • add parameters dection to readme
    • publish planning factor for intersection_collision_checker
    • refactor lanelet selection and filtering
    • update readme
    • set safety factor array in planning factor
    • clean up includes
    • publish planning factor for rear collision checker
    • fix spelling
    • rename variables to avoid shadowing

    * Update

File truncated at 100 lines see the full file

Launch files

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autoware_planning_validator_rear_collision_checker package from autoware_universe repo

autoware_agnocast_wrapper autoware_auto_common autoware_boundary_departure_checker autoware_component_interface_specs_universe autoware_component_interface_tools autoware_component_interface_utils autoware_cuda_dependency_meta autoware_fake_test_node autoware_glog_component autoware_goal_distance_calculator autoware_grid_map_utils autoware_path_distance_calculator autoware_polar_grid autoware_time_utils autoware_traffic_light_recognition_marker_publisher autoware_traffic_light_utils autoware_universe_utils tier4_api_utils autoware_autonomous_emergency_braking autoware_collision_detector autoware_control_command_gate autoware_control_performance_analysis autoware_control_validator autoware_external_cmd_selector autoware_joy_controller autoware_lane_departure_checker autoware_mpc_lateral_controller autoware_obstacle_collision_checker autoware_operation_mode_transition_manager autoware_pid_longitudinal_controller autoware_predicted_path_checker autoware_pure_pursuit autoware_shift_decider autoware_smart_mpc_trajectory_follower autoware_stop_mode_operator autoware_trajectory_follower_base autoware_trajectory_follower_node autoware_vehicle_cmd_gate autoware_control_evaluator autoware_kinematic_evaluator autoware_localization_evaluator autoware_perception_online_evaluator autoware_planning_evaluator autoware_scenario_simulator_v2_adapter autoware_diagnostic_graph_test_examples tier4_autoware_api_launch tier4_control_launch tier4_localization_launch tier4_map_launch tier4_perception_launch tier4_planning_launch tier4_sensing_launch tier4_simulator_launch tier4_system_launch tier4_vehicle_launch autoware_geo_pose_projector autoware_ar_tag_based_localizer autoware_landmark_manager autoware_lidar_marker_localizer autoware_localization_error_monitor autoware_pose2twist autoware_pose_covariance_modifier autoware_pose_estimator_arbiter autoware_pose_instability_detector yabloc_common yabloc_image_processing yabloc_monitor yabloc_particle_filter yabloc_pose_initializer autoware_map_tf_generator autoware_bevfusion autoware_bytetrack autoware_cluster_merger autoware_compare_map_segmentation autoware_crosswalk_traffic_light_estimator autoware_detected_object_feature_remover autoware_detected_object_validation autoware_detection_by_tracker autoware_elevation_map_loader autoware_euclidean_cluster autoware_ground_segmentation autoware_image_projection_based_fusion autoware_lidar_apollo_instance_segmentation autoware_lidar_centerpoint autoware_lidar_transfusion autoware_map_based_prediction autoware_multi_object_tracker autoware_object_merger autoware_object_range_splitter autoware_object_sorter autoware_object_velocity_splitter autoware_occupancy_grid_map_outlier_filter autoware_probabilistic_occupancy_grid_map autoware_radar_fusion_to_detected_object autoware_radar_object_tracker autoware_radar_tracks_msgs_converter autoware_raindrop_cluster_filter autoware_shape_estimation autoware_simpl_prediction autoware_simple_object_merger autoware_tensorrt_bevdet autoware_tensorrt_classifier autoware_tensorrt_common autoware_tensorrt_plugins autoware_tensorrt_yolox autoware_tracking_object_merger autoware_traffic_light_arbiter autoware_traffic_light_category_merger autoware_traffic_light_classifier autoware_traffic_light_fine_detector autoware_traffic_light_map_based_detector autoware_traffic_light_multi_camera_fusion autoware_traffic_light_occlusion_predictor autoware_traffic_light_selector autoware_traffic_light_visualization perception_utils autoware_costmap_generator autoware_diffusion_planner autoware_external_velocity_limit_selector autoware_freespace_planner autoware_freespace_planning_algorithms autoware_hazard_lights_selector autoware_mission_planner_universe autoware_path_optimizer autoware_path_smoother autoware_remaining_distance_time_calculator autoware_rtc_interface autoware_scenario_selector autoware_surround_obstacle_checker autoware_behavior_path_avoidance_by_lane_change_module autoware_behavior_path_bidirectional_traffic_module autoware_behavior_path_dynamic_obstacle_avoidance_module autoware_behavior_path_external_request_lane_change_module autoware_behavior_path_goal_planner_module autoware_behavior_path_lane_change_module autoware_behavior_path_planner autoware_behavior_path_planner_common autoware_behavior_path_sampling_planner_module autoware_behavior_path_side_shift_module autoware_behavior_path_start_planner_module autoware_behavior_path_static_obstacle_avoidance_module autoware_behavior_velocity_blind_spot_module autoware_behavior_velocity_crosswalk_module autoware_behavior_velocity_detection_area_module autoware_behavior_velocity_intersection_module autoware_behavior_velocity_no_drivable_lane_module autoware_behavior_velocity_no_stopping_area_module autoware_behavior_velocity_occlusion_spot_module autoware_behavior_velocity_rtc_interface autoware_behavior_velocity_run_out_module autoware_behavior_velocity_speed_bump_module autoware_behavior_velocity_template_module autoware_behavior_velocity_traffic_light_module autoware_behavior_velocity_virtual_traffic_light_module autoware_behavior_velocity_walkway_module autoware_motion_velocity_boundary_departure_prevention_module autoware_motion_velocity_dynamic_obstacle_stop_module autoware_motion_velocity_obstacle_cruise_module autoware_motion_velocity_obstacle_slow_down_module autoware_motion_velocity_obstacle_velocity_limiter_module autoware_motion_velocity_out_of_lane_module autoware_motion_velocity_road_user_stop_module autoware_motion_velocity_run_out_module autoware_planning_validator autoware_planning_validator_intersection_collision_checker autoware_planning_validator_latency_checker autoware_planning_validator_rear_collision_checker autoware_planning_validator_test_utils autoware_planning_validator_trajectory_checker autoware_bezier_sampler autoware_frenet_planner autoware_path_sampler autoware_sampler_common autoware_cuda_pointcloud_preprocessor autoware_cuda_utils autoware_image_diagnostics autoware_image_transport_decompressor autoware_imu_corrector autoware_pcl_extensions autoware_pointcloud_preprocessor autoware_radar_objects_adapter autoware_radar_scan_to_pointcloud2 autoware_radar_static_pointcloud_filter autoware_radar_threshold_filter autoware_radar_tracks_noise_filter autoware_livox_tag_filter autoware_carla_interface autoware_dummy_perception_publisher autoware_fault_injection autoware_learning_based_vehicle_model autoware_simple_planning_simulator autoware_vehicle_door_simulator tier4_dummy_object_rviz_plugin autoware_bluetooth_monitor autoware_command_mode_decider autoware_command_mode_decider_plugins autoware_command_mode_switcher autoware_command_mode_switcher_plugins autoware_command_mode_types autoware_component_monitor autoware_component_state_monitor autoware_adapi_visualizers autoware_automatic_pose_initializer autoware_default_adapi_universe autoware_diagnostic_graph_aggregator autoware_diagnostic_graph_utils autoware_dummy_diag_publisher autoware_dummy_infrastructure autoware_duplicated_node_checker autoware_hazard_status_converter autoware_mrm_comfortable_stop_operator autoware_mrm_emergency_stop_operator autoware_mrm_handler autoware_pipeline_latency_monitor autoware_processing_time_checker autoware_system_monitor autoware_topic_relay_controller autoware_topic_state_monitor autoware_velodyne_monitor reaction_analyzer autoware_accel_brake_map_calibrator autoware_external_cmd_converter autoware_raw_vehicle_cmd_converter autoware_steer_offset_estimator autoware_bag_time_manager_rviz_plugin autoware_traffic_light_rviz_plugin tier4_adapi_rviz_plugin tier4_camera_view_rviz_plugin tier4_control_mode_rviz_plugin tier4_datetime_rviz_plugin tier4_perception_rviz_plugin tier4_planning_factor_rviz_plugin tier4_state_rviz_plugin tier4_system_rviz_plugin tier4_traffic_light_rviz_plugin tier4_vehicle_rviz_plugin

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github

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Package Summary

Tags No category tags.
Version 0.47.0
License Apache License 2.0
Build type AMENT_CMAKE
Use RECOMMENDED

Repository Summary

Description
Checkout URI https://github.com/autowarefoundation/autoware_universe.git
VCS Type git
VCS Version main
Last Updated 2025-08-16
Dev Status UNKNOWN
Released UNRELEASED
Tags planner ros calibration self-driving-car autonomous-driving autonomous-vehicles ros2 3d-map autoware
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

The autoware_planning_validator_rear_collision_checker package

Additional Links

No additional links.

Maintainers

  • Satoshi Ota
  • Alqudah Mohammad
  • kyoichi sugahara
  • Maxime Clement

Authors

  • Satoshi Ota
planning/planning_validator/autoware_planning_validator_rear_collision_checker/README.md

Rear Collision Checker

The rear_collision_checker is a plugin module of the autoware_planning_validator node. It validates the planned trajectory by verifying that it does not lead to a collision with other road users (primarily vehicles, but also pedestrian/cyclists/motorcycles) approaching from lateral/rear directions. In particular, it is designed to detect potential rear-end collisions and entrapment risks when the ego vehicle is making a right/left turn or merging into an adjacent lane.

Inner Workings

The module operates by:

  1. Identifying conflict lanes
    • Uses the current route and lanelet topology to determine lanes that the ego vehicle’s trajectory may intersect with during right/left turns or lane changes.
    • Focuses on lanes where vehicles, bicycles, or motorcycles could approach from behind or from a lateral direction, posing a potential rear-end or entrapment risk.
    • Considers the turn_direction of the approaching lanelets to filter out irrelevant lanes.
  2. Filtering perception data
    • Subscribes to obstacle pointcloud and first filters by the conflict region, keeping only points that fall within relevant spatial bounds.
    • Performs clustering on the filtered points to form obstacle candidates.
    • Associates clusters with nearby lanelets and computes the nearest face of each obstacle along the lane direction.
    • Applies configurable range gates (forward/backward, lateral, height) and basic outlier rejection to discard distant or irrelevant clusters.
  3. Estimating motion
    • For each selected object, determines its motion relative to the lane direction.
    • Estimates speed and direction based on frame-to-frame position changes along the lane’s centerline.
    • Maintains a per-lane tracking list to stabilize velocity estimation and reduce noise from perception flicker.
  4. Calculating metrics
    • Depending on the selected metric (e.g., TTC, RSS), the calculation method and decision logic differ. The chosen metric is computed, and the result is used to determine whether there is a potential collision risk.
  5. Judging collision risk
    • Evaluates the selected metric results against predefined thresholds to determine whether a collision is likely.
    • Applies hysteresis logic:
      • on_time_buffer: Hazardous state must persist for this duration before marking the trajectory unsafe.
      • off_time_buffer: Safe state must persist for this duration before clearing the unsafe flag.
    • If check_on_unstoppable=false, the module will skip collision warnings in cases where the ego vehicle cannot realistically stop before the conflict area (to prevent unnecessary alerts when stopping is already infeasible).

Flowchart

WIP

General Parameters

Name Unit Type Description Default value
on_time_buffer [s] double Time buffer before enabling detection after a relevant condition is met 0.5
off_time_buffer [s] double Time buffer before disabling detection after the condition clears 1.5
check_on_unstoppable [-] bool If true, the module continues collision checking even when the ego vehicle cannot stop before entering a potential collision area, and outputs an ERROR if a collision risk is detected. If false, checking is skipped in such cases to avoid unnecessary warnings. false

Pointcloud Preprocess

Name Unit Type Description Default value
pointcloud.range.dead_zone [m] double Distance in front of the ego vehicle ignored for collision detection 0.3
pointcloud.range.buffer [m] double Additional margin around detection range 1.0
pointcloud.crop_box_filter.x.max [m] double Maximum X coordinate for cropped detection range 30.0
pointcloud.crop_box_filter.x.min [m] double Minimum X coordinate for cropped detection range -100.0
pointcloud.crop_box_filter.z.max [m] double Maximum Z coordinate for cropped detection range -1.0
pointcloud.crop_box_filter.z.min [m] double Minimum Z coordinate for cropped detection range 0.3
pointcloud.voxel_grid_filter.x [m] double Voxel grid filter size in X direction 0.1
pointcloud.voxel_grid_filter.y [m] double Voxel grid filter size in Y direction 0.1
pointcloud.voxel_grid_filter.z [m] double Voxel grid filter size in Z direction 0.5
pointcloud.clustering.cluster_tolerance [m] double Maximum distance between points to be considered part of the same cluster 0.15
pointcloud.clustering.min_cluster_height [m] double Minimum height of a cluster to be considered valid 0.1
pointcloud.clustering.min_cluster_size [points] int Minimum number of points in a valid cluster 5
pointcloud.clustering.max_cluster_size [points] int Maximum number of points in a valid cluster 10000
pointcloud.velocity_estimation.observation_time [s] double Time window used for velocity estimation 0.3
pointcloud.velocity_estimation.max_acceleration [m/s^2] double Maximum allowed acceleration in velocity estimation 10.0
pointcloud.latency [s] double Assumed system latency for point cloud processing 0.3

Object Filtering

Name Unit Type Description Default value
filter.min_velocity [m/s] double Minimum velocity threshold for objects to be considered moving 1.0
filter.moving_time [s] double Minimum time duration an object must be moving to be considered as such 0.5

TTC

Name Unit Type Description Default value
time_to_collision.margin [s] double Additional margin added to time-to-collision calculation 2.0

Ego Behavior

Name Unit Type Description Default value
ego.reaction_time [s] double Reaction time of the ego vehicle 1.2
ego.min_velocity [m/s] double Minimum considered velocity of the ego vehicle 1.38
ego.max_velocity [m/s] double Maximum considered velocity of the ego vehicle 16.6
ego.max_acceleration [m/s^2] double Maximum considered acceleration of the ego vehicle 1.5
ego.max_deceleration [m/s^2] double Maximum considered deceleration of the ego vehicle (negative value) -4.0
ego.max_positive_jerk [m/s^3] double Maximum allowed positive jerk for the ego vehicle 5.0
ego.max_negative_jerk [m/s^3] double Maximum allowed negative jerk for the ego vehicle -5.0
ego.nominal_deceleration [m/s^2] double Nominal deceleration used for calculations -1.5
ego.nominal_positive_jerk [m/s^3] double Nominal positive jerk used for calculations 0.6
ego.nominal_negative_jerk [m/s^3] double Nominal negative jerk used for calculations -0.6

Collision Check For Blind Spot

Name Unit Type Description Default value
blind_spot.lookahead_time [s] double Lookahead time for blind spot detection 4.0

File truncated at 100 lines see the full file

CHANGELOG

Changelog for package autoware_planning_validator_rear_collision_checker

0.47.0 (2025-08-11)

  • feat(rear_collision_checker): support selecting safety metric from TTC or RSS (#11072)

    • fix: return distance to predicted collision point
    • refactor: move to utils
    • refactor: move to utils
    • refactor: generalize function
    • feat: selectable metric
    • chore: rename variable for readability

    * refactor: not use lambda ---------

  • refactor(planning_validator): refactor planning validator configuration and error handling (#11081)

    • refactor trajectory check error handling
    • define set_diag_status function for each module locally

    * update documentation ---------

  • style(pre-commit): update to clang-format-20 (#11088) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

  • refactor(rear_collision_checker): update parameter structure (#11067)

    • refactor(rear_collision_checker): update parameter structure

    * chore: remove unused msg type ---------

  • chore(rear_collision_checker): add maintainer (#11069)

  • feat(rear_collision_checker): improve collision detection logic (#10992)

    • feat(rear_collision_checker): added a parameter to configure how many seconds ahead to predict collisions

    * feat(rear_collision_checker): add parameter to enable collision check for forward obstacles ---------

  • feat(intersection_collision_checker): improve icc debug markers (#10967)

    • add DebugData struct
    • refactor and publish debug info and markers
    • always publish lanelet debug markers
    • refactor debug markers code
    • remove unused functions
    • pass string by reference
    • set is_safe flag for rear_collision_checker debug data
    • fix for cpp check

    * add maintainer ---------

  • feat(intersection_collision_checker): improve feature to reduce false positive occurrence (#10899)

    • keep a map of already detected target lanelets
    • fix on/off time buffers logic
    • add debug marker to visualize colliding object
    • use resampled trajectory instead of raw trajectory
    • fix overlap index computation
    • fix on/off time buffers logic for rear collision checker
    • fix planning .pages file, fix format
    • update readme
    • ignore not moving pcd object

    * handle case when object is very close to overlap point ---------

  • feat(planning_validator): improve intersection collision checker implementation (#10839)

    • use parameter generator library
    • add pointcloud latency compensation
    • change msg field name
    • add readme file
    • add parameters dection to readme
    • publish planning factor for intersection_collision_checker
    • refactor lanelet selection and filtering
    • update readme
    • set safety factor array in planning factor
    • clean up includes
    • publish planning factor for rear collision checker
    • fix spelling
    • rename variables to avoid shadowing

    * Update

File truncated at 100 lines see the full file

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Recent questions tagged autoware_planning_validator_rear_collision_checker at Robotics Stack Exchange

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autoware_planning_validator_rear_collision_checker package from autoware_universe repo

autoware_agnocast_wrapper autoware_auto_common autoware_boundary_departure_checker autoware_component_interface_specs_universe autoware_component_interface_tools autoware_component_interface_utils autoware_cuda_dependency_meta autoware_fake_test_node autoware_glog_component autoware_goal_distance_calculator autoware_grid_map_utils autoware_path_distance_calculator autoware_polar_grid autoware_time_utils autoware_traffic_light_recognition_marker_publisher autoware_traffic_light_utils autoware_universe_utils tier4_api_utils autoware_autonomous_emergency_braking autoware_collision_detector autoware_control_command_gate autoware_control_performance_analysis autoware_control_validator autoware_external_cmd_selector autoware_joy_controller autoware_lane_departure_checker autoware_mpc_lateral_controller autoware_obstacle_collision_checker autoware_operation_mode_transition_manager autoware_pid_longitudinal_controller autoware_predicted_path_checker autoware_pure_pursuit autoware_shift_decider autoware_smart_mpc_trajectory_follower autoware_stop_mode_operator autoware_trajectory_follower_base autoware_trajectory_follower_node autoware_vehicle_cmd_gate autoware_control_evaluator autoware_kinematic_evaluator autoware_localization_evaluator autoware_perception_online_evaluator autoware_planning_evaluator autoware_scenario_simulator_v2_adapter autoware_diagnostic_graph_test_examples tier4_autoware_api_launch tier4_control_launch tier4_localization_launch tier4_map_launch tier4_perception_launch tier4_planning_launch tier4_sensing_launch tier4_simulator_launch tier4_system_launch tier4_vehicle_launch autoware_geo_pose_projector autoware_ar_tag_based_localizer autoware_landmark_manager autoware_lidar_marker_localizer autoware_localization_error_monitor autoware_pose2twist autoware_pose_covariance_modifier autoware_pose_estimator_arbiter autoware_pose_instability_detector yabloc_common yabloc_image_processing yabloc_monitor yabloc_particle_filter yabloc_pose_initializer autoware_map_tf_generator autoware_bevfusion autoware_bytetrack autoware_cluster_merger autoware_compare_map_segmentation autoware_crosswalk_traffic_light_estimator autoware_detected_object_feature_remover autoware_detected_object_validation autoware_detection_by_tracker autoware_elevation_map_loader autoware_euclidean_cluster autoware_ground_segmentation autoware_image_projection_based_fusion autoware_lidar_apollo_instance_segmentation autoware_lidar_centerpoint autoware_lidar_transfusion autoware_map_based_prediction autoware_multi_object_tracker autoware_object_merger autoware_object_range_splitter autoware_object_sorter autoware_object_velocity_splitter autoware_occupancy_grid_map_outlier_filter autoware_probabilistic_occupancy_grid_map autoware_radar_fusion_to_detected_object autoware_radar_object_tracker autoware_radar_tracks_msgs_converter autoware_raindrop_cluster_filter autoware_shape_estimation autoware_simpl_prediction autoware_simple_object_merger autoware_tensorrt_bevdet autoware_tensorrt_classifier autoware_tensorrt_common autoware_tensorrt_plugins autoware_tensorrt_yolox autoware_tracking_object_merger autoware_traffic_light_arbiter autoware_traffic_light_category_merger autoware_traffic_light_classifier autoware_traffic_light_fine_detector autoware_traffic_light_map_based_detector autoware_traffic_light_multi_camera_fusion autoware_traffic_light_occlusion_predictor autoware_traffic_light_selector autoware_traffic_light_visualization perception_utils autoware_costmap_generator autoware_diffusion_planner autoware_external_velocity_limit_selector autoware_freespace_planner autoware_freespace_planning_algorithms autoware_hazard_lights_selector autoware_mission_planner_universe autoware_path_optimizer autoware_path_smoother autoware_remaining_distance_time_calculator autoware_rtc_interface autoware_scenario_selector autoware_surround_obstacle_checker autoware_behavior_path_avoidance_by_lane_change_module autoware_behavior_path_bidirectional_traffic_module autoware_behavior_path_dynamic_obstacle_avoidance_module autoware_behavior_path_external_request_lane_change_module autoware_behavior_path_goal_planner_module autoware_behavior_path_lane_change_module autoware_behavior_path_planner autoware_behavior_path_planner_common autoware_behavior_path_sampling_planner_module autoware_behavior_path_side_shift_module autoware_behavior_path_start_planner_module autoware_behavior_path_static_obstacle_avoidance_module autoware_behavior_velocity_blind_spot_module autoware_behavior_velocity_crosswalk_module autoware_behavior_velocity_detection_area_module autoware_behavior_velocity_intersection_module autoware_behavior_velocity_no_drivable_lane_module autoware_behavior_velocity_no_stopping_area_module autoware_behavior_velocity_occlusion_spot_module autoware_behavior_velocity_rtc_interface autoware_behavior_velocity_run_out_module autoware_behavior_velocity_speed_bump_module autoware_behavior_velocity_template_module autoware_behavior_velocity_traffic_light_module autoware_behavior_velocity_virtual_traffic_light_module autoware_behavior_velocity_walkway_module autoware_motion_velocity_boundary_departure_prevention_module autoware_motion_velocity_dynamic_obstacle_stop_module autoware_motion_velocity_obstacle_cruise_module autoware_motion_velocity_obstacle_slow_down_module autoware_motion_velocity_obstacle_velocity_limiter_module autoware_motion_velocity_out_of_lane_module autoware_motion_velocity_road_user_stop_module autoware_motion_velocity_run_out_module autoware_planning_validator autoware_planning_validator_intersection_collision_checker autoware_planning_validator_latency_checker autoware_planning_validator_rear_collision_checker autoware_planning_validator_test_utils autoware_planning_validator_trajectory_checker autoware_bezier_sampler autoware_frenet_planner autoware_path_sampler autoware_sampler_common autoware_cuda_pointcloud_preprocessor autoware_cuda_utils autoware_image_diagnostics autoware_image_transport_decompressor autoware_imu_corrector autoware_pcl_extensions autoware_pointcloud_preprocessor autoware_radar_objects_adapter autoware_radar_scan_to_pointcloud2 autoware_radar_static_pointcloud_filter autoware_radar_threshold_filter autoware_radar_tracks_noise_filter autoware_livox_tag_filter autoware_carla_interface autoware_dummy_perception_publisher autoware_fault_injection autoware_learning_based_vehicle_model autoware_simple_planning_simulator autoware_vehicle_door_simulator tier4_dummy_object_rviz_plugin autoware_bluetooth_monitor autoware_command_mode_decider autoware_command_mode_decider_plugins autoware_command_mode_switcher autoware_command_mode_switcher_plugins autoware_command_mode_types autoware_component_monitor autoware_component_state_monitor autoware_adapi_visualizers autoware_automatic_pose_initializer autoware_default_adapi_universe autoware_diagnostic_graph_aggregator autoware_diagnostic_graph_utils autoware_dummy_diag_publisher autoware_dummy_infrastructure autoware_duplicated_node_checker autoware_hazard_status_converter autoware_mrm_comfortable_stop_operator autoware_mrm_emergency_stop_operator autoware_mrm_handler autoware_pipeline_latency_monitor autoware_processing_time_checker autoware_system_monitor autoware_topic_relay_controller autoware_topic_state_monitor autoware_velodyne_monitor reaction_analyzer autoware_accel_brake_map_calibrator autoware_external_cmd_converter autoware_raw_vehicle_cmd_converter autoware_steer_offset_estimator autoware_bag_time_manager_rviz_plugin autoware_traffic_light_rviz_plugin tier4_adapi_rviz_plugin tier4_camera_view_rviz_plugin tier4_control_mode_rviz_plugin tier4_datetime_rviz_plugin tier4_perception_rviz_plugin tier4_planning_factor_rviz_plugin tier4_state_rviz_plugin tier4_system_rviz_plugin tier4_traffic_light_rviz_plugin tier4_vehicle_rviz_plugin

ROS Distro
github

API Docs
Browse Code

Package Summary

Tags No category tags.
Version 0.47.0
License Apache License 2.0
Build type AMENT_CMAKE
Use RECOMMENDED

Repository Summary

Description
Checkout URI https://github.com/autowarefoundation/autoware_universe.git
VCS Type git
VCS Version main
Last Updated 2025-08-16
Dev Status UNKNOWN
Released UNRELEASED
Tags planner ros calibration self-driving-car autonomous-driving autonomous-vehicles ros2 3d-map autoware
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

The autoware_planning_validator_rear_collision_checker package

Additional Links

No additional links.

Maintainers

  • Satoshi Ota
  • Alqudah Mohammad
  • kyoichi sugahara
  • Maxime Clement

Authors

  • Satoshi Ota
planning/planning_validator/autoware_planning_validator_rear_collision_checker/README.md

Rear Collision Checker

The rear_collision_checker is a plugin module of the autoware_planning_validator node. It validates the planned trajectory by verifying that it does not lead to a collision with other road users (primarily vehicles, but also pedestrian/cyclists/motorcycles) approaching from lateral/rear directions. In particular, it is designed to detect potential rear-end collisions and entrapment risks when the ego vehicle is making a right/left turn or merging into an adjacent lane.

Inner Workings

The module operates by:

  1. Identifying conflict lanes
    • Uses the current route and lanelet topology to determine lanes that the ego vehicle’s trajectory may intersect with during right/left turns or lane changes.
    • Focuses on lanes where vehicles, bicycles, or motorcycles could approach from behind or from a lateral direction, posing a potential rear-end or entrapment risk.
    • Considers the turn_direction of the approaching lanelets to filter out irrelevant lanes.
  2. Filtering perception data
    • Subscribes to obstacle pointcloud and first filters by the conflict region, keeping only points that fall within relevant spatial bounds.
    • Performs clustering on the filtered points to form obstacle candidates.
    • Associates clusters with nearby lanelets and computes the nearest face of each obstacle along the lane direction.
    • Applies configurable range gates (forward/backward, lateral, height) and basic outlier rejection to discard distant or irrelevant clusters.
  3. Estimating motion
    • For each selected object, determines its motion relative to the lane direction.
    • Estimates speed and direction based on frame-to-frame position changes along the lane’s centerline.
    • Maintains a per-lane tracking list to stabilize velocity estimation and reduce noise from perception flicker.
  4. Calculating metrics
    • Depending on the selected metric (e.g., TTC, RSS), the calculation method and decision logic differ. The chosen metric is computed, and the result is used to determine whether there is a potential collision risk.
  5. Judging collision risk
    • Evaluates the selected metric results against predefined thresholds to determine whether a collision is likely.
    • Applies hysteresis logic:
      • on_time_buffer: Hazardous state must persist for this duration before marking the trajectory unsafe.
      • off_time_buffer: Safe state must persist for this duration before clearing the unsafe flag.
    • If check_on_unstoppable=false, the module will skip collision warnings in cases where the ego vehicle cannot realistically stop before the conflict area (to prevent unnecessary alerts when stopping is already infeasible).

Flowchart

WIP

General Parameters

Name Unit Type Description Default value
on_time_buffer [s] double Time buffer before enabling detection after a relevant condition is met 0.5
off_time_buffer [s] double Time buffer before disabling detection after the condition clears 1.5
check_on_unstoppable [-] bool If true, the module continues collision checking even when the ego vehicle cannot stop before entering a potential collision area, and outputs an ERROR if a collision risk is detected. If false, checking is skipped in such cases to avoid unnecessary warnings. false

Pointcloud Preprocess

Name Unit Type Description Default value
pointcloud.range.dead_zone [m] double Distance in front of the ego vehicle ignored for collision detection 0.3
pointcloud.range.buffer [m] double Additional margin around detection range 1.0
pointcloud.crop_box_filter.x.max [m] double Maximum X coordinate for cropped detection range 30.0
pointcloud.crop_box_filter.x.min [m] double Minimum X coordinate for cropped detection range -100.0
pointcloud.crop_box_filter.z.max [m] double Maximum Z coordinate for cropped detection range -1.0
pointcloud.crop_box_filter.z.min [m] double Minimum Z coordinate for cropped detection range 0.3
pointcloud.voxel_grid_filter.x [m] double Voxel grid filter size in X direction 0.1
pointcloud.voxel_grid_filter.y [m] double Voxel grid filter size in Y direction 0.1
pointcloud.voxel_grid_filter.z [m] double Voxel grid filter size in Z direction 0.5
pointcloud.clustering.cluster_tolerance [m] double Maximum distance between points to be considered part of the same cluster 0.15
pointcloud.clustering.min_cluster_height [m] double Minimum height of a cluster to be considered valid 0.1
pointcloud.clustering.min_cluster_size [points] int Minimum number of points in a valid cluster 5
pointcloud.clustering.max_cluster_size [points] int Maximum number of points in a valid cluster 10000
pointcloud.velocity_estimation.observation_time [s] double Time window used for velocity estimation 0.3
pointcloud.velocity_estimation.max_acceleration [m/s^2] double Maximum allowed acceleration in velocity estimation 10.0
pointcloud.latency [s] double Assumed system latency for point cloud processing 0.3

Object Filtering

Name Unit Type Description Default value
filter.min_velocity [m/s] double Minimum velocity threshold for objects to be considered moving 1.0
filter.moving_time [s] double Minimum time duration an object must be moving to be considered as such 0.5

TTC

Name Unit Type Description Default value
time_to_collision.margin [s] double Additional margin added to time-to-collision calculation 2.0

Ego Behavior

Name Unit Type Description Default value
ego.reaction_time [s] double Reaction time of the ego vehicle 1.2
ego.min_velocity [m/s] double Minimum considered velocity of the ego vehicle 1.38
ego.max_velocity [m/s] double Maximum considered velocity of the ego vehicle 16.6
ego.max_acceleration [m/s^2] double Maximum considered acceleration of the ego vehicle 1.5
ego.max_deceleration [m/s^2] double Maximum considered deceleration of the ego vehicle (negative value) -4.0
ego.max_positive_jerk [m/s^3] double Maximum allowed positive jerk for the ego vehicle 5.0
ego.max_negative_jerk [m/s^3] double Maximum allowed negative jerk for the ego vehicle -5.0
ego.nominal_deceleration [m/s^2] double Nominal deceleration used for calculations -1.5
ego.nominal_positive_jerk [m/s^3] double Nominal positive jerk used for calculations 0.6
ego.nominal_negative_jerk [m/s^3] double Nominal negative jerk used for calculations -0.6

Collision Check For Blind Spot

Name Unit Type Description Default value
blind_spot.lookahead_time [s] double Lookahead time for blind spot detection 4.0

File truncated at 100 lines see the full file

CHANGELOG

Changelog for package autoware_planning_validator_rear_collision_checker

0.47.0 (2025-08-11)

  • feat(rear_collision_checker): support selecting safety metric from TTC or RSS (#11072)

    • fix: return distance to predicted collision point
    • refactor: move to utils
    • refactor: move to utils
    • refactor: generalize function
    • feat: selectable metric
    • chore: rename variable for readability

    * refactor: not use lambda ---------

  • refactor(planning_validator): refactor planning validator configuration and error handling (#11081)

    • refactor trajectory check error handling
    • define set_diag_status function for each module locally

    * update documentation ---------

  • style(pre-commit): update to clang-format-20 (#11088) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

  • refactor(rear_collision_checker): update parameter structure (#11067)

    • refactor(rear_collision_checker): update parameter structure

    * chore: remove unused msg type ---------

  • chore(rear_collision_checker): add maintainer (#11069)

  • feat(rear_collision_checker): improve collision detection logic (#10992)

    • feat(rear_collision_checker): added a parameter to configure how many seconds ahead to predict collisions

    * feat(rear_collision_checker): add parameter to enable collision check for forward obstacles ---------

  • feat(intersection_collision_checker): improve icc debug markers (#10967)

    • add DebugData struct
    • refactor and publish debug info and markers
    • always publish lanelet debug markers
    • refactor debug markers code
    • remove unused functions
    • pass string by reference
    • set is_safe flag for rear_collision_checker debug data
    • fix for cpp check

    * add maintainer ---------

  • feat(intersection_collision_checker): improve feature to reduce false positive occurrence (#10899)

    • keep a map of already detected target lanelets
    • fix on/off time buffers logic
    • add debug marker to visualize colliding object
    • use resampled trajectory instead of raw trajectory
    • fix overlap index computation
    • fix on/off time buffers logic for rear collision checker
    • fix planning .pages file, fix format
    • update readme
    • ignore not moving pcd object

    * handle case when object is very close to overlap point ---------

  • feat(planning_validator): improve intersection collision checker implementation (#10839)

    • use parameter generator library
    • add pointcloud latency compensation
    • change msg field name
    • add readme file
    • add parameters dection to readme
    • publish planning factor for intersection_collision_checker
    • refactor lanelet selection and filtering
    • update readme
    • set safety factor array in planning factor
    • clean up includes
    • publish planning factor for rear collision checker
    • fix spelling
    • rename variables to avoid shadowing

    * Update

File truncated at 100 lines see the full file

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

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autoware_planning_validator_rear_collision_checker package from autoware_universe repo

autoware_agnocast_wrapper autoware_auto_common autoware_boundary_departure_checker autoware_component_interface_specs_universe autoware_component_interface_tools autoware_component_interface_utils autoware_cuda_dependency_meta autoware_fake_test_node autoware_glog_component autoware_goal_distance_calculator autoware_grid_map_utils autoware_path_distance_calculator autoware_polar_grid autoware_time_utils autoware_traffic_light_recognition_marker_publisher autoware_traffic_light_utils autoware_universe_utils tier4_api_utils autoware_autonomous_emergency_braking autoware_collision_detector autoware_control_command_gate autoware_control_performance_analysis autoware_control_validator autoware_external_cmd_selector autoware_joy_controller autoware_lane_departure_checker autoware_mpc_lateral_controller autoware_obstacle_collision_checker autoware_operation_mode_transition_manager autoware_pid_longitudinal_controller autoware_predicted_path_checker autoware_pure_pursuit autoware_shift_decider autoware_smart_mpc_trajectory_follower autoware_stop_mode_operator autoware_trajectory_follower_base autoware_trajectory_follower_node autoware_vehicle_cmd_gate autoware_control_evaluator autoware_kinematic_evaluator autoware_localization_evaluator autoware_perception_online_evaluator autoware_planning_evaluator autoware_scenario_simulator_v2_adapter autoware_diagnostic_graph_test_examples tier4_autoware_api_launch tier4_control_launch tier4_localization_launch tier4_map_launch tier4_perception_launch tier4_planning_launch tier4_sensing_launch tier4_simulator_launch tier4_system_launch tier4_vehicle_launch autoware_geo_pose_projector autoware_ar_tag_based_localizer autoware_landmark_manager autoware_lidar_marker_localizer autoware_localization_error_monitor autoware_pose2twist autoware_pose_covariance_modifier autoware_pose_estimator_arbiter autoware_pose_instability_detector yabloc_common yabloc_image_processing yabloc_monitor yabloc_particle_filter yabloc_pose_initializer autoware_map_tf_generator autoware_bevfusion autoware_bytetrack autoware_cluster_merger autoware_compare_map_segmentation autoware_crosswalk_traffic_light_estimator autoware_detected_object_feature_remover autoware_detected_object_validation autoware_detection_by_tracker autoware_elevation_map_loader autoware_euclidean_cluster autoware_ground_segmentation autoware_image_projection_based_fusion autoware_lidar_apollo_instance_segmentation autoware_lidar_centerpoint autoware_lidar_transfusion autoware_map_based_prediction autoware_multi_object_tracker autoware_object_merger autoware_object_range_splitter autoware_object_sorter autoware_object_velocity_splitter autoware_occupancy_grid_map_outlier_filter autoware_probabilistic_occupancy_grid_map autoware_radar_fusion_to_detected_object autoware_radar_object_tracker autoware_radar_tracks_msgs_converter autoware_raindrop_cluster_filter autoware_shape_estimation autoware_simpl_prediction autoware_simple_object_merger autoware_tensorrt_bevdet autoware_tensorrt_classifier autoware_tensorrt_common autoware_tensorrt_plugins autoware_tensorrt_yolox autoware_tracking_object_merger autoware_traffic_light_arbiter autoware_traffic_light_category_merger autoware_traffic_light_classifier autoware_traffic_light_fine_detector autoware_traffic_light_map_based_detector autoware_traffic_light_multi_camera_fusion autoware_traffic_light_occlusion_predictor autoware_traffic_light_selector autoware_traffic_light_visualization perception_utils autoware_costmap_generator autoware_diffusion_planner autoware_external_velocity_limit_selector autoware_freespace_planner autoware_freespace_planning_algorithms autoware_hazard_lights_selector autoware_mission_planner_universe autoware_path_optimizer autoware_path_smoother autoware_remaining_distance_time_calculator autoware_rtc_interface autoware_scenario_selector autoware_surround_obstacle_checker autoware_behavior_path_avoidance_by_lane_change_module autoware_behavior_path_bidirectional_traffic_module autoware_behavior_path_dynamic_obstacle_avoidance_module autoware_behavior_path_external_request_lane_change_module autoware_behavior_path_goal_planner_module autoware_behavior_path_lane_change_module autoware_behavior_path_planner autoware_behavior_path_planner_common autoware_behavior_path_sampling_planner_module autoware_behavior_path_side_shift_module autoware_behavior_path_start_planner_module autoware_behavior_path_static_obstacle_avoidance_module autoware_behavior_velocity_blind_spot_module autoware_behavior_velocity_crosswalk_module autoware_behavior_velocity_detection_area_module autoware_behavior_velocity_intersection_module autoware_behavior_velocity_no_drivable_lane_module autoware_behavior_velocity_no_stopping_area_module autoware_behavior_velocity_occlusion_spot_module autoware_behavior_velocity_rtc_interface autoware_behavior_velocity_run_out_module autoware_behavior_velocity_speed_bump_module autoware_behavior_velocity_template_module autoware_behavior_velocity_traffic_light_module autoware_behavior_velocity_virtual_traffic_light_module autoware_behavior_velocity_walkway_module autoware_motion_velocity_boundary_departure_prevention_module autoware_motion_velocity_dynamic_obstacle_stop_module autoware_motion_velocity_obstacle_cruise_module autoware_motion_velocity_obstacle_slow_down_module autoware_motion_velocity_obstacle_velocity_limiter_module autoware_motion_velocity_out_of_lane_module autoware_motion_velocity_road_user_stop_module autoware_motion_velocity_run_out_module autoware_planning_validator autoware_planning_validator_intersection_collision_checker autoware_planning_validator_latency_checker autoware_planning_validator_rear_collision_checker autoware_planning_validator_test_utils autoware_planning_validator_trajectory_checker autoware_bezier_sampler autoware_frenet_planner autoware_path_sampler autoware_sampler_common autoware_cuda_pointcloud_preprocessor autoware_cuda_utils autoware_image_diagnostics autoware_image_transport_decompressor autoware_imu_corrector autoware_pcl_extensions autoware_pointcloud_preprocessor autoware_radar_objects_adapter autoware_radar_scan_to_pointcloud2 autoware_radar_static_pointcloud_filter autoware_radar_threshold_filter autoware_radar_tracks_noise_filter autoware_livox_tag_filter autoware_carla_interface autoware_dummy_perception_publisher autoware_fault_injection autoware_learning_based_vehicle_model autoware_simple_planning_simulator autoware_vehicle_door_simulator tier4_dummy_object_rviz_plugin autoware_bluetooth_monitor autoware_command_mode_decider autoware_command_mode_decider_plugins autoware_command_mode_switcher autoware_command_mode_switcher_plugins autoware_command_mode_types autoware_component_monitor autoware_component_state_monitor autoware_adapi_visualizers autoware_automatic_pose_initializer autoware_default_adapi_universe autoware_diagnostic_graph_aggregator autoware_diagnostic_graph_utils autoware_dummy_diag_publisher autoware_dummy_infrastructure autoware_duplicated_node_checker autoware_hazard_status_converter autoware_mrm_comfortable_stop_operator autoware_mrm_emergency_stop_operator autoware_mrm_handler autoware_pipeline_latency_monitor autoware_processing_time_checker autoware_system_monitor autoware_topic_relay_controller autoware_topic_state_monitor autoware_velodyne_monitor reaction_analyzer autoware_accel_brake_map_calibrator autoware_external_cmd_converter autoware_raw_vehicle_cmd_converter autoware_steer_offset_estimator autoware_bag_time_manager_rviz_plugin autoware_traffic_light_rviz_plugin tier4_adapi_rviz_plugin tier4_camera_view_rviz_plugin tier4_control_mode_rviz_plugin tier4_datetime_rviz_plugin tier4_perception_rviz_plugin tier4_planning_factor_rviz_plugin tier4_state_rviz_plugin tier4_system_rviz_plugin tier4_traffic_light_rviz_plugin tier4_vehicle_rviz_plugin

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Package Summary

Tags No category tags.
Version 0.47.0
License Apache License 2.0
Build type AMENT_CMAKE
Use RECOMMENDED

Repository Summary

Description
Checkout URI https://github.com/autowarefoundation/autoware_universe.git
VCS Type git
VCS Version main
Last Updated 2025-08-16
Dev Status UNKNOWN
Released UNRELEASED
Tags planner ros calibration self-driving-car autonomous-driving autonomous-vehicles ros2 3d-map autoware
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

The autoware_planning_validator_rear_collision_checker package

Additional Links

No additional links.

Maintainers

  • Satoshi Ota
  • Alqudah Mohammad
  • kyoichi sugahara
  • Maxime Clement

Authors

  • Satoshi Ota
planning/planning_validator/autoware_planning_validator_rear_collision_checker/README.md

Rear Collision Checker

The rear_collision_checker is a plugin module of the autoware_planning_validator node. It validates the planned trajectory by verifying that it does not lead to a collision with other road users (primarily vehicles, but also pedestrian/cyclists/motorcycles) approaching from lateral/rear directions. In particular, it is designed to detect potential rear-end collisions and entrapment risks when the ego vehicle is making a right/left turn or merging into an adjacent lane.

Inner Workings

The module operates by:

  1. Identifying conflict lanes
    • Uses the current route and lanelet topology to determine lanes that the ego vehicle’s trajectory may intersect with during right/left turns or lane changes.
    • Focuses on lanes where vehicles, bicycles, or motorcycles could approach from behind or from a lateral direction, posing a potential rear-end or entrapment risk.
    • Considers the turn_direction of the approaching lanelets to filter out irrelevant lanes.
  2. Filtering perception data
    • Subscribes to obstacle pointcloud and first filters by the conflict region, keeping only points that fall within relevant spatial bounds.
    • Performs clustering on the filtered points to form obstacle candidates.
    • Associates clusters with nearby lanelets and computes the nearest face of each obstacle along the lane direction.
    • Applies configurable range gates (forward/backward, lateral, height) and basic outlier rejection to discard distant or irrelevant clusters.
  3. Estimating motion
    • For each selected object, determines its motion relative to the lane direction.
    • Estimates speed and direction based on frame-to-frame position changes along the lane’s centerline.
    • Maintains a per-lane tracking list to stabilize velocity estimation and reduce noise from perception flicker.
  4. Calculating metrics
    • Depending on the selected metric (e.g., TTC, RSS), the calculation method and decision logic differ. The chosen metric is computed, and the result is used to determine whether there is a potential collision risk.
  5. Judging collision risk
    • Evaluates the selected metric results against predefined thresholds to determine whether a collision is likely.
    • Applies hysteresis logic:
      • on_time_buffer: Hazardous state must persist for this duration before marking the trajectory unsafe.
      • off_time_buffer: Safe state must persist for this duration before clearing the unsafe flag.
    • If check_on_unstoppable=false, the module will skip collision warnings in cases where the ego vehicle cannot realistically stop before the conflict area (to prevent unnecessary alerts when stopping is already infeasible).

Flowchart

WIP

General Parameters

Name Unit Type Description Default value
on_time_buffer [s] double Time buffer before enabling detection after a relevant condition is met 0.5
off_time_buffer [s] double Time buffer before disabling detection after the condition clears 1.5
check_on_unstoppable [-] bool If true, the module continues collision checking even when the ego vehicle cannot stop before entering a potential collision area, and outputs an ERROR if a collision risk is detected. If false, checking is skipped in such cases to avoid unnecessary warnings. false

Pointcloud Preprocess

Name Unit Type Description Default value
pointcloud.range.dead_zone [m] double Distance in front of the ego vehicle ignored for collision detection 0.3
pointcloud.range.buffer [m] double Additional margin around detection range 1.0
pointcloud.crop_box_filter.x.max [m] double Maximum X coordinate for cropped detection range 30.0
pointcloud.crop_box_filter.x.min [m] double Minimum X coordinate for cropped detection range -100.0
pointcloud.crop_box_filter.z.max [m] double Maximum Z coordinate for cropped detection range -1.0
pointcloud.crop_box_filter.z.min [m] double Minimum Z coordinate for cropped detection range 0.3
pointcloud.voxel_grid_filter.x [m] double Voxel grid filter size in X direction 0.1
pointcloud.voxel_grid_filter.y [m] double Voxel grid filter size in Y direction 0.1
pointcloud.voxel_grid_filter.z [m] double Voxel grid filter size in Z direction 0.5
pointcloud.clustering.cluster_tolerance [m] double Maximum distance between points to be considered part of the same cluster 0.15
pointcloud.clustering.min_cluster_height [m] double Minimum height of a cluster to be considered valid 0.1
pointcloud.clustering.min_cluster_size [points] int Minimum number of points in a valid cluster 5
pointcloud.clustering.max_cluster_size [points] int Maximum number of points in a valid cluster 10000
pointcloud.velocity_estimation.observation_time [s] double Time window used for velocity estimation 0.3
pointcloud.velocity_estimation.max_acceleration [m/s^2] double Maximum allowed acceleration in velocity estimation 10.0
pointcloud.latency [s] double Assumed system latency for point cloud processing 0.3

Object Filtering

Name Unit Type Description Default value
filter.min_velocity [m/s] double Minimum velocity threshold for objects to be considered moving 1.0
filter.moving_time [s] double Minimum time duration an object must be moving to be considered as such 0.5

TTC

Name Unit Type Description Default value
time_to_collision.margin [s] double Additional margin added to time-to-collision calculation 2.0

Ego Behavior

Name Unit Type Description Default value
ego.reaction_time [s] double Reaction time of the ego vehicle 1.2
ego.min_velocity [m/s] double Minimum considered velocity of the ego vehicle 1.38
ego.max_velocity [m/s] double Maximum considered velocity of the ego vehicle 16.6
ego.max_acceleration [m/s^2] double Maximum considered acceleration of the ego vehicle 1.5
ego.max_deceleration [m/s^2] double Maximum considered deceleration of the ego vehicle (negative value) -4.0
ego.max_positive_jerk [m/s^3] double Maximum allowed positive jerk for the ego vehicle 5.0
ego.max_negative_jerk [m/s^3] double Maximum allowed negative jerk for the ego vehicle -5.0
ego.nominal_deceleration [m/s^2] double Nominal deceleration used for calculations -1.5
ego.nominal_positive_jerk [m/s^3] double Nominal positive jerk used for calculations 0.6
ego.nominal_negative_jerk [m/s^3] double Nominal negative jerk used for calculations -0.6

Collision Check For Blind Spot

Name Unit Type Description Default value
blind_spot.lookahead_time [s] double Lookahead time for blind spot detection 4.0

File truncated at 100 lines see the full file

CHANGELOG

Changelog for package autoware_planning_validator_rear_collision_checker

0.47.0 (2025-08-11)

  • feat(rear_collision_checker): support selecting safety metric from TTC or RSS (#11072)

    • fix: return distance to predicted collision point
    • refactor: move to utils
    • refactor: move to utils
    • refactor: generalize function
    • feat: selectable metric
    • chore: rename variable for readability

    * refactor: not use lambda ---------

  • refactor(planning_validator): refactor planning validator configuration and error handling (#11081)

    • refactor trajectory check error handling
    • define set_diag_status function for each module locally

    * update documentation ---------

  • style(pre-commit): update to clang-format-20 (#11088) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

  • refactor(rear_collision_checker): update parameter structure (#11067)

    • refactor(rear_collision_checker): update parameter structure

    * chore: remove unused msg type ---------

  • chore(rear_collision_checker): add maintainer (#11069)

  • feat(rear_collision_checker): improve collision detection logic (#10992)

    • feat(rear_collision_checker): added a parameter to configure how many seconds ahead to predict collisions

    * feat(rear_collision_checker): add parameter to enable collision check for forward obstacles ---------

  • feat(intersection_collision_checker): improve icc debug markers (#10967)

    • add DebugData struct
    • refactor and publish debug info and markers
    • always publish lanelet debug markers
    • refactor debug markers code
    • remove unused functions
    • pass string by reference
    • set is_safe flag for rear_collision_checker debug data
    • fix for cpp check

    * add maintainer ---------

  • feat(intersection_collision_checker): improve feature to reduce false positive occurrence (#10899)

    • keep a map of already detected target lanelets
    • fix on/off time buffers logic
    • add debug marker to visualize colliding object
    • use resampled trajectory instead of raw trajectory
    • fix overlap index computation
    • fix on/off time buffers logic for rear collision checker
    • fix planning .pages file, fix format
    • update readme
    • ignore not moving pcd object

    * handle case when object is very close to overlap point ---------

  • feat(planning_validator): improve intersection collision checker implementation (#10839)

    • use parameter generator library
    • add pointcloud latency compensation
    • change msg field name
    • add readme file
    • add parameters dection to readme
    • publish planning factor for intersection_collision_checker
    • refactor lanelet selection and filtering
    • update readme
    • set safety factor array in planning factor
    • clean up includes
    • publish planning factor for rear collision checker
    • fix spelling
    • rename variables to avoid shadowing

    * Update

File truncated at 100 lines see the full file

Launch files

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autoware_planning_validator_rear_collision_checker package from autoware_universe repo

autoware_agnocast_wrapper autoware_auto_common autoware_boundary_departure_checker autoware_component_interface_specs_universe autoware_component_interface_tools autoware_component_interface_utils autoware_cuda_dependency_meta autoware_fake_test_node autoware_glog_component autoware_goal_distance_calculator autoware_grid_map_utils autoware_path_distance_calculator autoware_polar_grid autoware_time_utils autoware_traffic_light_recognition_marker_publisher autoware_traffic_light_utils autoware_universe_utils tier4_api_utils autoware_autonomous_emergency_braking autoware_collision_detector autoware_control_command_gate autoware_control_performance_analysis autoware_control_validator autoware_external_cmd_selector autoware_joy_controller autoware_lane_departure_checker autoware_mpc_lateral_controller autoware_obstacle_collision_checker autoware_operation_mode_transition_manager autoware_pid_longitudinal_controller autoware_predicted_path_checker autoware_pure_pursuit autoware_shift_decider autoware_smart_mpc_trajectory_follower autoware_stop_mode_operator autoware_trajectory_follower_base autoware_trajectory_follower_node autoware_vehicle_cmd_gate autoware_control_evaluator autoware_kinematic_evaluator autoware_localization_evaluator autoware_perception_online_evaluator autoware_planning_evaluator autoware_scenario_simulator_v2_adapter autoware_diagnostic_graph_test_examples tier4_autoware_api_launch tier4_control_launch tier4_localization_launch tier4_map_launch tier4_perception_launch tier4_planning_launch tier4_sensing_launch tier4_simulator_launch tier4_system_launch tier4_vehicle_launch autoware_geo_pose_projector autoware_ar_tag_based_localizer autoware_landmark_manager autoware_lidar_marker_localizer autoware_localization_error_monitor autoware_pose2twist autoware_pose_covariance_modifier autoware_pose_estimator_arbiter autoware_pose_instability_detector yabloc_common yabloc_image_processing yabloc_monitor yabloc_particle_filter yabloc_pose_initializer autoware_map_tf_generator autoware_bevfusion autoware_bytetrack autoware_cluster_merger autoware_compare_map_segmentation autoware_crosswalk_traffic_light_estimator autoware_detected_object_feature_remover autoware_detected_object_validation autoware_detection_by_tracker autoware_elevation_map_loader autoware_euclidean_cluster autoware_ground_segmentation autoware_image_projection_based_fusion autoware_lidar_apollo_instance_segmentation autoware_lidar_centerpoint autoware_lidar_transfusion autoware_map_based_prediction autoware_multi_object_tracker autoware_object_merger autoware_object_range_splitter autoware_object_sorter autoware_object_velocity_splitter autoware_occupancy_grid_map_outlier_filter autoware_probabilistic_occupancy_grid_map autoware_radar_fusion_to_detected_object autoware_radar_object_tracker autoware_radar_tracks_msgs_converter autoware_raindrop_cluster_filter autoware_shape_estimation autoware_simpl_prediction autoware_simple_object_merger autoware_tensorrt_bevdet autoware_tensorrt_classifier autoware_tensorrt_common autoware_tensorrt_plugins autoware_tensorrt_yolox autoware_tracking_object_merger autoware_traffic_light_arbiter autoware_traffic_light_category_merger autoware_traffic_light_classifier autoware_traffic_light_fine_detector autoware_traffic_light_map_based_detector autoware_traffic_light_multi_camera_fusion autoware_traffic_light_occlusion_predictor autoware_traffic_light_selector autoware_traffic_light_visualization perception_utils autoware_costmap_generator autoware_diffusion_planner autoware_external_velocity_limit_selector autoware_freespace_planner autoware_freespace_planning_algorithms autoware_hazard_lights_selector autoware_mission_planner_universe autoware_path_optimizer autoware_path_smoother autoware_remaining_distance_time_calculator autoware_rtc_interface autoware_scenario_selector autoware_surround_obstacle_checker autoware_behavior_path_avoidance_by_lane_change_module autoware_behavior_path_bidirectional_traffic_module autoware_behavior_path_dynamic_obstacle_avoidance_module autoware_behavior_path_external_request_lane_change_module autoware_behavior_path_goal_planner_module autoware_behavior_path_lane_change_module autoware_behavior_path_planner autoware_behavior_path_planner_common autoware_behavior_path_sampling_planner_module autoware_behavior_path_side_shift_module autoware_behavior_path_start_planner_module autoware_behavior_path_static_obstacle_avoidance_module autoware_behavior_velocity_blind_spot_module autoware_behavior_velocity_crosswalk_module autoware_behavior_velocity_detection_area_module autoware_behavior_velocity_intersection_module autoware_behavior_velocity_no_drivable_lane_module autoware_behavior_velocity_no_stopping_area_module autoware_behavior_velocity_occlusion_spot_module autoware_behavior_velocity_rtc_interface autoware_behavior_velocity_run_out_module autoware_behavior_velocity_speed_bump_module autoware_behavior_velocity_template_module autoware_behavior_velocity_traffic_light_module autoware_behavior_velocity_virtual_traffic_light_module autoware_behavior_velocity_walkway_module autoware_motion_velocity_boundary_departure_prevention_module autoware_motion_velocity_dynamic_obstacle_stop_module autoware_motion_velocity_obstacle_cruise_module autoware_motion_velocity_obstacle_slow_down_module autoware_motion_velocity_obstacle_velocity_limiter_module autoware_motion_velocity_out_of_lane_module autoware_motion_velocity_road_user_stop_module autoware_motion_velocity_run_out_module autoware_planning_validator autoware_planning_validator_intersection_collision_checker autoware_planning_validator_latency_checker autoware_planning_validator_rear_collision_checker autoware_planning_validator_test_utils autoware_planning_validator_trajectory_checker autoware_bezier_sampler autoware_frenet_planner autoware_path_sampler autoware_sampler_common autoware_cuda_pointcloud_preprocessor autoware_cuda_utils autoware_image_diagnostics autoware_image_transport_decompressor autoware_imu_corrector autoware_pcl_extensions autoware_pointcloud_preprocessor autoware_radar_objects_adapter autoware_radar_scan_to_pointcloud2 autoware_radar_static_pointcloud_filter autoware_radar_threshold_filter autoware_radar_tracks_noise_filter autoware_livox_tag_filter autoware_carla_interface autoware_dummy_perception_publisher autoware_fault_injection autoware_learning_based_vehicle_model autoware_simple_planning_simulator autoware_vehicle_door_simulator tier4_dummy_object_rviz_plugin autoware_bluetooth_monitor autoware_command_mode_decider autoware_command_mode_decider_plugins autoware_command_mode_switcher autoware_command_mode_switcher_plugins autoware_command_mode_types autoware_component_monitor autoware_component_state_monitor autoware_adapi_visualizers autoware_automatic_pose_initializer autoware_default_adapi_universe autoware_diagnostic_graph_aggregator autoware_diagnostic_graph_utils autoware_dummy_diag_publisher autoware_dummy_infrastructure autoware_duplicated_node_checker autoware_hazard_status_converter autoware_mrm_comfortable_stop_operator autoware_mrm_emergency_stop_operator autoware_mrm_handler autoware_pipeline_latency_monitor autoware_processing_time_checker autoware_system_monitor autoware_topic_relay_controller autoware_topic_state_monitor autoware_velodyne_monitor reaction_analyzer autoware_accel_brake_map_calibrator autoware_external_cmd_converter autoware_raw_vehicle_cmd_converter autoware_steer_offset_estimator autoware_bag_time_manager_rviz_plugin autoware_traffic_light_rviz_plugin tier4_adapi_rviz_plugin tier4_camera_view_rviz_plugin tier4_control_mode_rviz_plugin tier4_datetime_rviz_plugin tier4_perception_rviz_plugin tier4_planning_factor_rviz_plugin tier4_state_rviz_plugin tier4_system_rviz_plugin tier4_traffic_light_rviz_plugin tier4_vehicle_rviz_plugin

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Package Summary

Tags No category tags.
Version 0.47.0
License Apache License 2.0
Build type AMENT_CMAKE
Use RECOMMENDED

Repository Summary

Description
Checkout URI https://github.com/autowarefoundation/autoware_universe.git
VCS Type git
VCS Version main
Last Updated 2025-08-16
Dev Status UNKNOWN
Released UNRELEASED
Tags planner ros calibration self-driving-car autonomous-driving autonomous-vehicles ros2 3d-map autoware
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

The autoware_planning_validator_rear_collision_checker package

Additional Links

No additional links.

Maintainers

  • Satoshi Ota
  • Alqudah Mohammad
  • kyoichi sugahara
  • Maxime Clement

Authors

  • Satoshi Ota
planning/planning_validator/autoware_planning_validator_rear_collision_checker/README.md

Rear Collision Checker

The rear_collision_checker is a plugin module of the autoware_planning_validator node. It validates the planned trajectory by verifying that it does not lead to a collision with other road users (primarily vehicles, but also pedestrian/cyclists/motorcycles) approaching from lateral/rear directions. In particular, it is designed to detect potential rear-end collisions and entrapment risks when the ego vehicle is making a right/left turn or merging into an adjacent lane.

Inner Workings

The module operates by:

  1. Identifying conflict lanes
    • Uses the current route and lanelet topology to determine lanes that the ego vehicle’s trajectory may intersect with during right/left turns or lane changes.
    • Focuses on lanes where vehicles, bicycles, or motorcycles could approach from behind or from a lateral direction, posing a potential rear-end or entrapment risk.
    • Considers the turn_direction of the approaching lanelets to filter out irrelevant lanes.
  2. Filtering perception data
    • Subscribes to obstacle pointcloud and first filters by the conflict region, keeping only points that fall within relevant spatial bounds.
    • Performs clustering on the filtered points to form obstacle candidates.
    • Associates clusters with nearby lanelets and computes the nearest face of each obstacle along the lane direction.
    • Applies configurable range gates (forward/backward, lateral, height) and basic outlier rejection to discard distant or irrelevant clusters.
  3. Estimating motion
    • For each selected object, determines its motion relative to the lane direction.
    • Estimates speed and direction based on frame-to-frame position changes along the lane’s centerline.
    • Maintains a per-lane tracking list to stabilize velocity estimation and reduce noise from perception flicker.
  4. Calculating metrics
    • Depending on the selected metric (e.g., TTC, RSS), the calculation method and decision logic differ. The chosen metric is computed, and the result is used to determine whether there is a potential collision risk.
  5. Judging collision risk
    • Evaluates the selected metric results against predefined thresholds to determine whether a collision is likely.
    • Applies hysteresis logic:
      • on_time_buffer: Hazardous state must persist for this duration before marking the trajectory unsafe.
      • off_time_buffer: Safe state must persist for this duration before clearing the unsafe flag.
    • If check_on_unstoppable=false, the module will skip collision warnings in cases where the ego vehicle cannot realistically stop before the conflict area (to prevent unnecessary alerts when stopping is already infeasible).

Flowchart

WIP

General Parameters

Name Unit Type Description Default value
on_time_buffer [s] double Time buffer before enabling detection after a relevant condition is met 0.5
off_time_buffer [s] double Time buffer before disabling detection after the condition clears 1.5
check_on_unstoppable [-] bool If true, the module continues collision checking even when the ego vehicle cannot stop before entering a potential collision area, and outputs an ERROR if a collision risk is detected. If false, checking is skipped in such cases to avoid unnecessary warnings. false

Pointcloud Preprocess

Name Unit Type Description Default value
pointcloud.range.dead_zone [m] double Distance in front of the ego vehicle ignored for collision detection 0.3
pointcloud.range.buffer [m] double Additional margin around detection range 1.0
pointcloud.crop_box_filter.x.max [m] double Maximum X coordinate for cropped detection range 30.0
pointcloud.crop_box_filter.x.min [m] double Minimum X coordinate for cropped detection range -100.0
pointcloud.crop_box_filter.z.max [m] double Maximum Z coordinate for cropped detection range -1.0
pointcloud.crop_box_filter.z.min [m] double Minimum Z coordinate for cropped detection range 0.3
pointcloud.voxel_grid_filter.x [m] double Voxel grid filter size in X direction 0.1
pointcloud.voxel_grid_filter.y [m] double Voxel grid filter size in Y direction 0.1
pointcloud.voxel_grid_filter.z [m] double Voxel grid filter size in Z direction 0.5
pointcloud.clustering.cluster_tolerance [m] double Maximum distance between points to be considered part of the same cluster 0.15
pointcloud.clustering.min_cluster_height [m] double Minimum height of a cluster to be considered valid 0.1
pointcloud.clustering.min_cluster_size [points] int Minimum number of points in a valid cluster 5
pointcloud.clustering.max_cluster_size [points] int Maximum number of points in a valid cluster 10000
pointcloud.velocity_estimation.observation_time [s] double Time window used for velocity estimation 0.3
pointcloud.velocity_estimation.max_acceleration [m/s^2] double Maximum allowed acceleration in velocity estimation 10.0
pointcloud.latency [s] double Assumed system latency for point cloud processing 0.3

Object Filtering

Name Unit Type Description Default value
filter.min_velocity [m/s] double Minimum velocity threshold for objects to be considered moving 1.0
filter.moving_time [s] double Minimum time duration an object must be moving to be considered as such 0.5

TTC

Name Unit Type Description Default value
time_to_collision.margin [s] double Additional margin added to time-to-collision calculation 2.0

Ego Behavior

Name Unit Type Description Default value
ego.reaction_time [s] double Reaction time of the ego vehicle 1.2
ego.min_velocity [m/s] double Minimum considered velocity of the ego vehicle 1.38
ego.max_velocity [m/s] double Maximum considered velocity of the ego vehicle 16.6
ego.max_acceleration [m/s^2] double Maximum considered acceleration of the ego vehicle 1.5
ego.max_deceleration [m/s^2] double Maximum considered deceleration of the ego vehicle (negative value) -4.0
ego.max_positive_jerk [m/s^3] double Maximum allowed positive jerk for the ego vehicle 5.0
ego.max_negative_jerk [m/s^3] double Maximum allowed negative jerk for the ego vehicle -5.0
ego.nominal_deceleration [m/s^2] double Nominal deceleration used for calculations -1.5
ego.nominal_positive_jerk [m/s^3] double Nominal positive jerk used for calculations 0.6
ego.nominal_negative_jerk [m/s^3] double Nominal negative jerk used for calculations -0.6

Collision Check For Blind Spot

Name Unit Type Description Default value
blind_spot.lookahead_time [s] double Lookahead time for blind spot detection 4.0

File truncated at 100 lines see the full file

CHANGELOG

Changelog for package autoware_planning_validator_rear_collision_checker

0.47.0 (2025-08-11)

  • feat(rear_collision_checker): support selecting safety metric from TTC or RSS (#11072)

    • fix: return distance to predicted collision point
    • refactor: move to utils
    • refactor: move to utils
    • refactor: generalize function
    • feat: selectable metric
    • chore: rename variable for readability

    * refactor: not use lambda ---------

  • refactor(planning_validator): refactor planning validator configuration and error handling (#11081)

    • refactor trajectory check error handling
    • define set_diag_status function for each module locally

    * update documentation ---------

  • style(pre-commit): update to clang-format-20 (#11088) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

  • refactor(rear_collision_checker): update parameter structure (#11067)

    • refactor(rear_collision_checker): update parameter structure

    * chore: remove unused msg type ---------

  • chore(rear_collision_checker): add maintainer (#11069)

  • feat(rear_collision_checker): improve collision detection logic (#10992)

    • feat(rear_collision_checker): added a parameter to configure how many seconds ahead to predict collisions

    * feat(rear_collision_checker): add parameter to enable collision check for forward obstacles ---------

  • feat(intersection_collision_checker): improve icc debug markers (#10967)

    • add DebugData struct
    • refactor and publish debug info and markers
    • always publish lanelet debug markers
    • refactor debug markers code
    • remove unused functions
    • pass string by reference
    • set is_safe flag for rear_collision_checker debug data
    • fix for cpp check

    * add maintainer ---------

  • feat(intersection_collision_checker): improve feature to reduce false positive occurrence (#10899)

    • keep a map of already detected target lanelets
    • fix on/off time buffers logic
    • add debug marker to visualize colliding object
    • use resampled trajectory instead of raw trajectory
    • fix overlap index computation
    • fix on/off time buffers logic for rear collision checker
    • fix planning .pages file, fix format
    • update readme
    • ignore not moving pcd object

    * handle case when object is very close to overlap point ---------

  • feat(planning_validator): improve intersection collision checker implementation (#10839)

    • use parameter generator library
    • add pointcloud latency compensation
    • change msg field name
    • add readme file
    • add parameters dection to readme
    • publish planning factor for intersection_collision_checker
    • refactor lanelet selection and filtering
    • update readme
    • set safety factor array in planning factor
    • clean up includes
    • publish planning factor for rear collision checker
    • fix spelling
    • rename variables to avoid shadowing

    * Update

File truncated at 100 lines see the full file

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autoware_planning_validator_rear_collision_checker package from autoware_universe repo

autoware_agnocast_wrapper autoware_auto_common autoware_boundary_departure_checker autoware_component_interface_specs_universe autoware_component_interface_tools autoware_component_interface_utils autoware_cuda_dependency_meta autoware_fake_test_node autoware_glog_component autoware_goal_distance_calculator autoware_grid_map_utils autoware_path_distance_calculator autoware_polar_grid autoware_time_utils autoware_traffic_light_recognition_marker_publisher autoware_traffic_light_utils autoware_universe_utils tier4_api_utils autoware_autonomous_emergency_braking autoware_collision_detector autoware_control_command_gate autoware_control_performance_analysis autoware_control_validator autoware_external_cmd_selector autoware_joy_controller autoware_lane_departure_checker autoware_mpc_lateral_controller autoware_obstacle_collision_checker autoware_operation_mode_transition_manager autoware_pid_longitudinal_controller autoware_predicted_path_checker autoware_pure_pursuit autoware_shift_decider autoware_smart_mpc_trajectory_follower autoware_stop_mode_operator autoware_trajectory_follower_base autoware_trajectory_follower_node autoware_vehicle_cmd_gate autoware_control_evaluator autoware_kinematic_evaluator autoware_localization_evaluator autoware_perception_online_evaluator autoware_planning_evaluator autoware_scenario_simulator_v2_adapter autoware_diagnostic_graph_test_examples tier4_autoware_api_launch tier4_control_launch tier4_localization_launch tier4_map_launch tier4_perception_launch tier4_planning_launch tier4_sensing_launch tier4_simulator_launch tier4_system_launch tier4_vehicle_launch autoware_geo_pose_projector autoware_ar_tag_based_localizer autoware_landmark_manager autoware_lidar_marker_localizer autoware_localization_error_monitor autoware_pose2twist autoware_pose_covariance_modifier autoware_pose_estimator_arbiter autoware_pose_instability_detector yabloc_common yabloc_image_processing yabloc_monitor yabloc_particle_filter yabloc_pose_initializer autoware_map_tf_generator autoware_bevfusion autoware_bytetrack autoware_cluster_merger autoware_compare_map_segmentation autoware_crosswalk_traffic_light_estimator autoware_detected_object_feature_remover autoware_detected_object_validation autoware_detection_by_tracker autoware_elevation_map_loader autoware_euclidean_cluster autoware_ground_segmentation autoware_image_projection_based_fusion autoware_lidar_apollo_instance_segmentation autoware_lidar_centerpoint autoware_lidar_transfusion autoware_map_based_prediction autoware_multi_object_tracker autoware_object_merger autoware_object_range_splitter autoware_object_sorter autoware_object_velocity_splitter autoware_occupancy_grid_map_outlier_filter autoware_probabilistic_occupancy_grid_map autoware_radar_fusion_to_detected_object autoware_radar_object_tracker autoware_radar_tracks_msgs_converter autoware_raindrop_cluster_filter autoware_shape_estimation autoware_simpl_prediction autoware_simple_object_merger autoware_tensorrt_bevdet autoware_tensorrt_classifier autoware_tensorrt_common autoware_tensorrt_plugins autoware_tensorrt_yolox autoware_tracking_object_merger autoware_traffic_light_arbiter autoware_traffic_light_category_merger autoware_traffic_light_classifier autoware_traffic_light_fine_detector autoware_traffic_light_map_based_detector autoware_traffic_light_multi_camera_fusion autoware_traffic_light_occlusion_predictor autoware_traffic_light_selector autoware_traffic_light_visualization perception_utils autoware_costmap_generator autoware_diffusion_planner autoware_external_velocity_limit_selector autoware_freespace_planner autoware_freespace_planning_algorithms autoware_hazard_lights_selector autoware_mission_planner_universe autoware_path_optimizer autoware_path_smoother autoware_remaining_distance_time_calculator autoware_rtc_interface autoware_scenario_selector autoware_surround_obstacle_checker autoware_behavior_path_avoidance_by_lane_change_module autoware_behavior_path_bidirectional_traffic_module autoware_behavior_path_dynamic_obstacle_avoidance_module autoware_behavior_path_external_request_lane_change_module autoware_behavior_path_goal_planner_module autoware_behavior_path_lane_change_module autoware_behavior_path_planner autoware_behavior_path_planner_common autoware_behavior_path_sampling_planner_module autoware_behavior_path_side_shift_module autoware_behavior_path_start_planner_module autoware_behavior_path_static_obstacle_avoidance_module autoware_behavior_velocity_blind_spot_module autoware_behavior_velocity_crosswalk_module autoware_behavior_velocity_detection_area_module autoware_behavior_velocity_intersection_module autoware_behavior_velocity_no_drivable_lane_module autoware_behavior_velocity_no_stopping_area_module autoware_behavior_velocity_occlusion_spot_module autoware_behavior_velocity_rtc_interface autoware_behavior_velocity_run_out_module autoware_behavior_velocity_speed_bump_module autoware_behavior_velocity_template_module autoware_behavior_velocity_traffic_light_module autoware_behavior_velocity_virtual_traffic_light_module autoware_behavior_velocity_walkway_module autoware_motion_velocity_boundary_departure_prevention_module autoware_motion_velocity_dynamic_obstacle_stop_module autoware_motion_velocity_obstacle_cruise_module autoware_motion_velocity_obstacle_slow_down_module autoware_motion_velocity_obstacle_velocity_limiter_module autoware_motion_velocity_out_of_lane_module autoware_motion_velocity_road_user_stop_module autoware_motion_velocity_run_out_module autoware_planning_validator autoware_planning_validator_intersection_collision_checker autoware_planning_validator_latency_checker autoware_planning_validator_rear_collision_checker autoware_planning_validator_test_utils autoware_planning_validator_trajectory_checker autoware_bezier_sampler autoware_frenet_planner autoware_path_sampler autoware_sampler_common autoware_cuda_pointcloud_preprocessor autoware_cuda_utils autoware_image_diagnostics autoware_image_transport_decompressor autoware_imu_corrector autoware_pcl_extensions autoware_pointcloud_preprocessor autoware_radar_objects_adapter autoware_radar_scan_to_pointcloud2 autoware_radar_static_pointcloud_filter autoware_radar_threshold_filter autoware_radar_tracks_noise_filter autoware_livox_tag_filter autoware_carla_interface autoware_dummy_perception_publisher autoware_fault_injection autoware_learning_based_vehicle_model autoware_simple_planning_simulator autoware_vehicle_door_simulator tier4_dummy_object_rviz_plugin autoware_bluetooth_monitor autoware_command_mode_decider autoware_command_mode_decider_plugins autoware_command_mode_switcher autoware_command_mode_switcher_plugins autoware_command_mode_types autoware_component_monitor autoware_component_state_monitor autoware_adapi_visualizers autoware_automatic_pose_initializer autoware_default_adapi_universe autoware_diagnostic_graph_aggregator autoware_diagnostic_graph_utils autoware_dummy_diag_publisher autoware_dummy_infrastructure autoware_duplicated_node_checker autoware_hazard_status_converter autoware_mrm_comfortable_stop_operator autoware_mrm_emergency_stop_operator autoware_mrm_handler autoware_pipeline_latency_monitor autoware_processing_time_checker autoware_system_monitor autoware_topic_relay_controller autoware_topic_state_monitor autoware_velodyne_monitor reaction_analyzer autoware_accel_brake_map_calibrator autoware_external_cmd_converter autoware_raw_vehicle_cmd_converter autoware_steer_offset_estimator autoware_bag_time_manager_rviz_plugin autoware_traffic_light_rviz_plugin tier4_adapi_rviz_plugin tier4_camera_view_rviz_plugin tier4_control_mode_rviz_plugin tier4_datetime_rviz_plugin tier4_perception_rviz_plugin tier4_planning_factor_rviz_plugin tier4_state_rviz_plugin tier4_system_rviz_plugin tier4_traffic_light_rviz_plugin tier4_vehicle_rviz_plugin

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Package Summary

Tags No category tags.
Version 0.47.0
License Apache License 2.0
Build type AMENT_CMAKE
Use RECOMMENDED

Repository Summary

Description
Checkout URI https://github.com/autowarefoundation/autoware_universe.git
VCS Type git
VCS Version main
Last Updated 2025-08-16
Dev Status UNKNOWN
Released UNRELEASED
Tags planner ros calibration self-driving-car autonomous-driving autonomous-vehicles ros2 3d-map autoware
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

The autoware_planning_validator_rear_collision_checker package

Additional Links

No additional links.

Maintainers

  • Satoshi Ota
  • Alqudah Mohammad
  • kyoichi sugahara
  • Maxime Clement

Authors

  • Satoshi Ota
planning/planning_validator/autoware_planning_validator_rear_collision_checker/README.md

Rear Collision Checker

The rear_collision_checker is a plugin module of the autoware_planning_validator node. It validates the planned trajectory by verifying that it does not lead to a collision with other road users (primarily vehicles, but also pedestrian/cyclists/motorcycles) approaching from lateral/rear directions. In particular, it is designed to detect potential rear-end collisions and entrapment risks when the ego vehicle is making a right/left turn or merging into an adjacent lane.

Inner Workings

The module operates by:

  1. Identifying conflict lanes
    • Uses the current route and lanelet topology to determine lanes that the ego vehicle’s trajectory may intersect with during right/left turns or lane changes.
    • Focuses on lanes where vehicles, bicycles, or motorcycles could approach from behind or from a lateral direction, posing a potential rear-end or entrapment risk.
    • Considers the turn_direction of the approaching lanelets to filter out irrelevant lanes.
  2. Filtering perception data
    • Subscribes to obstacle pointcloud and first filters by the conflict region, keeping only points that fall within relevant spatial bounds.
    • Performs clustering on the filtered points to form obstacle candidates.
    • Associates clusters with nearby lanelets and computes the nearest face of each obstacle along the lane direction.
    • Applies configurable range gates (forward/backward, lateral, height) and basic outlier rejection to discard distant or irrelevant clusters.
  3. Estimating motion
    • For each selected object, determines its motion relative to the lane direction.
    • Estimates speed and direction based on frame-to-frame position changes along the lane’s centerline.
    • Maintains a per-lane tracking list to stabilize velocity estimation and reduce noise from perception flicker.
  4. Calculating metrics
    • Depending on the selected metric (e.g., TTC, RSS), the calculation method and decision logic differ. The chosen metric is computed, and the result is used to determine whether there is a potential collision risk.
  5. Judging collision risk
    • Evaluates the selected metric results against predefined thresholds to determine whether a collision is likely.
    • Applies hysteresis logic:
      • on_time_buffer: Hazardous state must persist for this duration before marking the trajectory unsafe.
      • off_time_buffer: Safe state must persist for this duration before clearing the unsafe flag.
    • If check_on_unstoppable=false, the module will skip collision warnings in cases where the ego vehicle cannot realistically stop before the conflict area (to prevent unnecessary alerts when stopping is already infeasible).

Flowchart

WIP

General Parameters

Name Unit Type Description Default value
on_time_buffer [s] double Time buffer before enabling detection after a relevant condition is met 0.5
off_time_buffer [s] double Time buffer before disabling detection after the condition clears 1.5
check_on_unstoppable [-] bool If true, the module continues collision checking even when the ego vehicle cannot stop before entering a potential collision area, and outputs an ERROR if a collision risk is detected. If false, checking is skipped in such cases to avoid unnecessary warnings. false

Pointcloud Preprocess

Name Unit Type Description Default value
pointcloud.range.dead_zone [m] double Distance in front of the ego vehicle ignored for collision detection 0.3
pointcloud.range.buffer [m] double Additional margin around detection range 1.0
pointcloud.crop_box_filter.x.max [m] double Maximum X coordinate for cropped detection range 30.0
pointcloud.crop_box_filter.x.min [m] double Minimum X coordinate for cropped detection range -100.0
pointcloud.crop_box_filter.z.max [m] double Maximum Z coordinate for cropped detection range -1.0
pointcloud.crop_box_filter.z.min [m] double Minimum Z coordinate for cropped detection range 0.3
pointcloud.voxel_grid_filter.x [m] double Voxel grid filter size in X direction 0.1
pointcloud.voxel_grid_filter.y [m] double Voxel grid filter size in Y direction 0.1
pointcloud.voxel_grid_filter.z [m] double Voxel grid filter size in Z direction 0.5
pointcloud.clustering.cluster_tolerance [m] double Maximum distance between points to be considered part of the same cluster 0.15
pointcloud.clustering.min_cluster_height [m] double Minimum height of a cluster to be considered valid 0.1
pointcloud.clustering.min_cluster_size [points] int Minimum number of points in a valid cluster 5
pointcloud.clustering.max_cluster_size [points] int Maximum number of points in a valid cluster 10000
pointcloud.velocity_estimation.observation_time [s] double Time window used for velocity estimation 0.3
pointcloud.velocity_estimation.max_acceleration [m/s^2] double Maximum allowed acceleration in velocity estimation 10.0
pointcloud.latency [s] double Assumed system latency for point cloud processing 0.3

Object Filtering

Name Unit Type Description Default value
filter.min_velocity [m/s] double Minimum velocity threshold for objects to be considered moving 1.0
filter.moving_time [s] double Minimum time duration an object must be moving to be considered as such 0.5

TTC

Name Unit Type Description Default value
time_to_collision.margin [s] double Additional margin added to time-to-collision calculation 2.0

Ego Behavior

Name Unit Type Description Default value
ego.reaction_time [s] double Reaction time of the ego vehicle 1.2
ego.min_velocity [m/s] double Minimum considered velocity of the ego vehicle 1.38
ego.max_velocity [m/s] double Maximum considered velocity of the ego vehicle 16.6
ego.max_acceleration [m/s^2] double Maximum considered acceleration of the ego vehicle 1.5
ego.max_deceleration [m/s^2] double Maximum considered deceleration of the ego vehicle (negative value) -4.0
ego.max_positive_jerk [m/s^3] double Maximum allowed positive jerk for the ego vehicle 5.0
ego.max_negative_jerk [m/s^3] double Maximum allowed negative jerk for the ego vehicle -5.0
ego.nominal_deceleration [m/s^2] double Nominal deceleration used for calculations -1.5
ego.nominal_positive_jerk [m/s^3] double Nominal positive jerk used for calculations 0.6
ego.nominal_negative_jerk [m/s^3] double Nominal negative jerk used for calculations -0.6

Collision Check For Blind Spot

Name Unit Type Description Default value
blind_spot.lookahead_time [s] double Lookahead time for blind spot detection 4.0

File truncated at 100 lines see the full file

CHANGELOG

Changelog for package autoware_planning_validator_rear_collision_checker

0.47.0 (2025-08-11)

  • feat(rear_collision_checker): support selecting safety metric from TTC or RSS (#11072)

    • fix: return distance to predicted collision point
    • refactor: move to utils
    • refactor: move to utils
    • refactor: generalize function
    • feat: selectable metric
    • chore: rename variable for readability

    * refactor: not use lambda ---------

  • refactor(planning_validator): refactor planning validator configuration and error handling (#11081)

    • refactor trajectory check error handling
    • define set_diag_status function for each module locally

    * update documentation ---------

  • style(pre-commit): update to clang-format-20 (#11088) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

  • refactor(rear_collision_checker): update parameter structure (#11067)

    • refactor(rear_collision_checker): update parameter structure

    * chore: remove unused msg type ---------

  • chore(rear_collision_checker): add maintainer (#11069)

  • feat(rear_collision_checker): improve collision detection logic (#10992)

    • feat(rear_collision_checker): added a parameter to configure how many seconds ahead to predict collisions

    * feat(rear_collision_checker): add parameter to enable collision check for forward obstacles ---------

  • feat(intersection_collision_checker): improve icc debug markers (#10967)

    • add DebugData struct
    • refactor and publish debug info and markers
    • always publish lanelet debug markers
    • refactor debug markers code
    • remove unused functions
    • pass string by reference
    • set is_safe flag for rear_collision_checker debug data
    • fix for cpp check

    * add maintainer ---------

  • feat(intersection_collision_checker): improve feature to reduce false positive occurrence (#10899)

    • keep a map of already detected target lanelets
    • fix on/off time buffers logic
    • add debug marker to visualize colliding object
    • use resampled trajectory instead of raw trajectory
    • fix overlap index computation
    • fix on/off time buffers logic for rear collision checker
    • fix planning .pages file, fix format
    • update readme
    • ignore not moving pcd object

    * handle case when object is very close to overlap point ---------

  • feat(planning_validator): improve intersection collision checker implementation (#10839)

    • use parameter generator library
    • add pointcloud latency compensation
    • change msg field name
    • add readme file
    • add parameters dection to readme
    • publish planning factor for intersection_collision_checker
    • refactor lanelet selection and filtering
    • update readme
    • set safety factor array in planning factor
    • clean up includes
    • publish planning factor for rear collision checker
    • fix spelling
    • rename variables to avoid shadowing

    * Update

File truncated at 100 lines see the full file

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autoware_agnocast_wrapper autoware_auto_common autoware_boundary_departure_checker autoware_component_interface_specs_universe autoware_component_interface_tools autoware_component_interface_utils autoware_cuda_dependency_meta autoware_fake_test_node autoware_glog_component autoware_goal_distance_calculator autoware_grid_map_utils autoware_path_distance_calculator autoware_polar_grid autoware_time_utils autoware_traffic_light_recognition_marker_publisher autoware_traffic_light_utils autoware_universe_utils tier4_api_utils autoware_autonomous_emergency_braking autoware_collision_detector autoware_control_command_gate autoware_control_performance_analysis autoware_control_validator autoware_external_cmd_selector autoware_joy_controller autoware_lane_departure_checker autoware_mpc_lateral_controller autoware_obstacle_collision_checker autoware_operation_mode_transition_manager autoware_pid_longitudinal_controller autoware_predicted_path_checker autoware_pure_pursuit autoware_shift_decider autoware_smart_mpc_trajectory_follower autoware_stop_mode_operator autoware_trajectory_follower_base autoware_trajectory_follower_node autoware_vehicle_cmd_gate autoware_control_evaluator autoware_kinematic_evaluator autoware_localization_evaluator autoware_perception_online_evaluator autoware_planning_evaluator autoware_scenario_simulator_v2_adapter autoware_diagnostic_graph_test_examples tier4_autoware_api_launch tier4_control_launch tier4_localization_launch tier4_map_launch tier4_perception_launch tier4_planning_launch tier4_sensing_launch tier4_simulator_launch tier4_system_launch tier4_vehicle_launch autoware_geo_pose_projector autoware_ar_tag_based_localizer autoware_landmark_manager autoware_lidar_marker_localizer autoware_localization_error_monitor autoware_pose2twist autoware_pose_covariance_modifier autoware_pose_estimator_arbiter autoware_pose_instability_detector yabloc_common yabloc_image_processing yabloc_monitor yabloc_particle_filter yabloc_pose_initializer autoware_map_tf_generator autoware_bevfusion autoware_bytetrack autoware_cluster_merger autoware_compare_map_segmentation autoware_crosswalk_traffic_light_estimator autoware_detected_object_feature_remover autoware_detected_object_validation autoware_detection_by_tracker autoware_elevation_map_loader autoware_euclidean_cluster autoware_ground_segmentation autoware_image_projection_based_fusion autoware_lidar_apollo_instance_segmentation autoware_lidar_centerpoint autoware_lidar_transfusion autoware_map_based_prediction autoware_multi_object_tracker autoware_object_merger autoware_object_range_splitter autoware_object_sorter autoware_object_velocity_splitter autoware_occupancy_grid_map_outlier_filter autoware_probabilistic_occupancy_grid_map autoware_radar_fusion_to_detected_object autoware_radar_object_tracker autoware_radar_tracks_msgs_converter autoware_raindrop_cluster_filter autoware_shape_estimation autoware_simpl_prediction autoware_simple_object_merger autoware_tensorrt_bevdet autoware_tensorrt_classifier autoware_tensorrt_common autoware_tensorrt_plugins autoware_tensorrt_yolox autoware_tracking_object_merger autoware_traffic_light_arbiter autoware_traffic_light_category_merger autoware_traffic_light_classifier autoware_traffic_light_fine_detector autoware_traffic_light_map_based_detector autoware_traffic_light_multi_camera_fusion autoware_traffic_light_occlusion_predictor autoware_traffic_light_selector autoware_traffic_light_visualization perception_utils autoware_costmap_generator autoware_diffusion_planner autoware_external_velocity_limit_selector autoware_freespace_planner autoware_freespace_planning_algorithms autoware_hazard_lights_selector autoware_mission_planner_universe autoware_path_optimizer autoware_path_smoother autoware_remaining_distance_time_calculator autoware_rtc_interface autoware_scenario_selector autoware_surround_obstacle_checker autoware_behavior_path_avoidance_by_lane_change_module autoware_behavior_path_bidirectional_traffic_module autoware_behavior_path_dynamic_obstacle_avoidance_module autoware_behavior_path_external_request_lane_change_module autoware_behavior_path_goal_planner_module autoware_behavior_path_lane_change_module autoware_behavior_path_planner autoware_behavior_path_planner_common autoware_behavior_path_sampling_planner_module autoware_behavior_path_side_shift_module autoware_behavior_path_start_planner_module autoware_behavior_path_static_obstacle_avoidance_module autoware_behavior_velocity_blind_spot_module autoware_behavior_velocity_crosswalk_module autoware_behavior_velocity_detection_area_module autoware_behavior_velocity_intersection_module autoware_behavior_velocity_no_drivable_lane_module autoware_behavior_velocity_no_stopping_area_module autoware_behavior_velocity_occlusion_spot_module autoware_behavior_velocity_rtc_interface autoware_behavior_velocity_run_out_module autoware_behavior_velocity_speed_bump_module autoware_behavior_velocity_template_module autoware_behavior_velocity_traffic_light_module autoware_behavior_velocity_virtual_traffic_light_module autoware_behavior_velocity_walkway_module autoware_motion_velocity_boundary_departure_prevention_module autoware_motion_velocity_dynamic_obstacle_stop_module autoware_motion_velocity_obstacle_cruise_module autoware_motion_velocity_obstacle_slow_down_module autoware_motion_velocity_obstacle_velocity_limiter_module autoware_motion_velocity_out_of_lane_module autoware_motion_velocity_road_user_stop_module autoware_motion_velocity_run_out_module autoware_planning_validator autoware_planning_validator_intersection_collision_checker autoware_planning_validator_latency_checker autoware_planning_validator_rear_collision_checker autoware_planning_validator_test_utils autoware_planning_validator_trajectory_checker autoware_bezier_sampler autoware_frenet_planner autoware_path_sampler autoware_sampler_common autoware_cuda_pointcloud_preprocessor autoware_cuda_utils autoware_image_diagnostics autoware_image_transport_decompressor autoware_imu_corrector autoware_pcl_extensions autoware_pointcloud_preprocessor autoware_radar_objects_adapter autoware_radar_scan_to_pointcloud2 autoware_radar_static_pointcloud_filter autoware_radar_threshold_filter autoware_radar_tracks_noise_filter autoware_livox_tag_filter autoware_carla_interface autoware_dummy_perception_publisher autoware_fault_injection autoware_learning_based_vehicle_model autoware_simple_planning_simulator autoware_vehicle_door_simulator tier4_dummy_object_rviz_plugin autoware_bluetooth_monitor autoware_command_mode_decider autoware_command_mode_decider_plugins autoware_command_mode_switcher autoware_command_mode_switcher_plugins autoware_command_mode_types autoware_component_monitor autoware_component_state_monitor autoware_adapi_visualizers autoware_automatic_pose_initializer autoware_default_adapi_universe autoware_diagnostic_graph_aggregator autoware_diagnostic_graph_utils autoware_dummy_diag_publisher autoware_dummy_infrastructure autoware_duplicated_node_checker autoware_hazard_status_converter autoware_mrm_comfortable_stop_operator autoware_mrm_emergency_stop_operator autoware_mrm_handler autoware_pipeline_latency_monitor autoware_processing_time_checker autoware_system_monitor autoware_topic_relay_controller autoware_topic_state_monitor autoware_velodyne_monitor reaction_analyzer autoware_accel_brake_map_calibrator autoware_external_cmd_converter autoware_raw_vehicle_cmd_converter autoware_steer_offset_estimator autoware_bag_time_manager_rviz_plugin autoware_traffic_light_rviz_plugin tier4_adapi_rviz_plugin tier4_camera_view_rviz_plugin tier4_control_mode_rviz_plugin tier4_datetime_rviz_plugin tier4_perception_rviz_plugin tier4_planning_factor_rviz_plugin tier4_state_rviz_plugin tier4_system_rviz_plugin tier4_traffic_light_rviz_plugin tier4_vehicle_rviz_plugin

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Package Summary

Tags No category tags.
Version 0.47.0
License Apache License 2.0
Build type AMENT_CMAKE
Use RECOMMENDED

Repository Summary

Description
Checkout URI https://github.com/autowarefoundation/autoware_universe.git
VCS Type git
VCS Version main
Last Updated 2025-08-16
Dev Status UNKNOWN
Released UNRELEASED
Tags planner ros calibration self-driving-car autonomous-driving autonomous-vehicles ros2 3d-map autoware
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

The autoware_planning_validator_rear_collision_checker package

Additional Links

No additional links.

Maintainers

  • Satoshi Ota
  • Alqudah Mohammad
  • kyoichi sugahara
  • Maxime Clement

Authors

  • Satoshi Ota
planning/planning_validator/autoware_planning_validator_rear_collision_checker/README.md

Rear Collision Checker

The rear_collision_checker is a plugin module of the autoware_planning_validator node. It validates the planned trajectory by verifying that it does not lead to a collision with other road users (primarily vehicles, but also pedestrian/cyclists/motorcycles) approaching from lateral/rear directions. In particular, it is designed to detect potential rear-end collisions and entrapment risks when the ego vehicle is making a right/left turn or merging into an adjacent lane.

Inner Workings

The module operates by:

  1. Identifying conflict lanes
    • Uses the current route and lanelet topology to determine lanes that the ego vehicle’s trajectory may intersect with during right/left turns or lane changes.
    • Focuses on lanes where vehicles, bicycles, or motorcycles could approach from behind or from a lateral direction, posing a potential rear-end or entrapment risk.
    • Considers the turn_direction of the approaching lanelets to filter out irrelevant lanes.
  2. Filtering perception data
    • Subscribes to obstacle pointcloud and first filters by the conflict region, keeping only points that fall within relevant spatial bounds.
    • Performs clustering on the filtered points to form obstacle candidates.
    • Associates clusters with nearby lanelets and computes the nearest face of each obstacle along the lane direction.
    • Applies configurable range gates (forward/backward, lateral, height) and basic outlier rejection to discard distant or irrelevant clusters.
  3. Estimating motion
    • For each selected object, determines its motion relative to the lane direction.
    • Estimates speed and direction based on frame-to-frame position changes along the lane’s centerline.
    • Maintains a per-lane tracking list to stabilize velocity estimation and reduce noise from perception flicker.
  4. Calculating metrics
    • Depending on the selected metric (e.g., TTC, RSS), the calculation method and decision logic differ. The chosen metric is computed, and the result is used to determine whether there is a potential collision risk.
  5. Judging collision risk
    • Evaluates the selected metric results against predefined thresholds to determine whether a collision is likely.
    • Applies hysteresis logic:
      • on_time_buffer: Hazardous state must persist for this duration before marking the trajectory unsafe.
      • off_time_buffer: Safe state must persist for this duration before clearing the unsafe flag.
    • If check_on_unstoppable=false, the module will skip collision warnings in cases where the ego vehicle cannot realistically stop before the conflict area (to prevent unnecessary alerts when stopping is already infeasible).

Flowchart

WIP

General Parameters

Name Unit Type Description Default value
on_time_buffer [s] double Time buffer before enabling detection after a relevant condition is met 0.5
off_time_buffer [s] double Time buffer before disabling detection after the condition clears 1.5
check_on_unstoppable [-] bool If true, the module continues collision checking even when the ego vehicle cannot stop before entering a potential collision area, and outputs an ERROR if a collision risk is detected. If false, checking is skipped in such cases to avoid unnecessary warnings. false

Pointcloud Preprocess

Name Unit Type Description Default value
pointcloud.range.dead_zone [m] double Distance in front of the ego vehicle ignored for collision detection 0.3
pointcloud.range.buffer [m] double Additional margin around detection range 1.0
pointcloud.crop_box_filter.x.max [m] double Maximum X coordinate for cropped detection range 30.0
pointcloud.crop_box_filter.x.min [m] double Minimum X coordinate for cropped detection range -100.0
pointcloud.crop_box_filter.z.max [m] double Maximum Z coordinate for cropped detection range -1.0
pointcloud.crop_box_filter.z.min [m] double Minimum Z coordinate for cropped detection range 0.3
pointcloud.voxel_grid_filter.x [m] double Voxel grid filter size in X direction 0.1
pointcloud.voxel_grid_filter.y [m] double Voxel grid filter size in Y direction 0.1
pointcloud.voxel_grid_filter.z [m] double Voxel grid filter size in Z direction 0.5
pointcloud.clustering.cluster_tolerance [m] double Maximum distance between points to be considered part of the same cluster 0.15
pointcloud.clustering.min_cluster_height [m] double Minimum height of a cluster to be considered valid 0.1
pointcloud.clustering.min_cluster_size [points] int Minimum number of points in a valid cluster 5
pointcloud.clustering.max_cluster_size [points] int Maximum number of points in a valid cluster 10000
pointcloud.velocity_estimation.observation_time [s] double Time window used for velocity estimation 0.3
pointcloud.velocity_estimation.max_acceleration [m/s^2] double Maximum allowed acceleration in velocity estimation 10.0
pointcloud.latency [s] double Assumed system latency for point cloud processing 0.3

Object Filtering

Name Unit Type Description Default value
filter.min_velocity [m/s] double Minimum velocity threshold for objects to be considered moving 1.0
filter.moving_time [s] double Minimum time duration an object must be moving to be considered as such 0.5

TTC

Name Unit Type Description Default value
time_to_collision.margin [s] double Additional margin added to time-to-collision calculation 2.0

Ego Behavior

Name Unit Type Description Default value
ego.reaction_time [s] double Reaction time of the ego vehicle 1.2
ego.min_velocity [m/s] double Minimum considered velocity of the ego vehicle 1.38
ego.max_velocity [m/s] double Maximum considered velocity of the ego vehicle 16.6
ego.max_acceleration [m/s^2] double Maximum considered acceleration of the ego vehicle 1.5
ego.max_deceleration [m/s^2] double Maximum considered deceleration of the ego vehicle (negative value) -4.0
ego.max_positive_jerk [m/s^3] double Maximum allowed positive jerk for the ego vehicle 5.0
ego.max_negative_jerk [m/s^3] double Maximum allowed negative jerk for the ego vehicle -5.0
ego.nominal_deceleration [m/s^2] double Nominal deceleration used for calculations -1.5
ego.nominal_positive_jerk [m/s^3] double Nominal positive jerk used for calculations 0.6
ego.nominal_negative_jerk [m/s^3] double Nominal negative jerk used for calculations -0.6

Collision Check For Blind Spot

Name Unit Type Description Default value
blind_spot.lookahead_time [s] double Lookahead time for blind spot detection 4.0

File truncated at 100 lines see the full file

CHANGELOG

Changelog for package autoware_planning_validator_rear_collision_checker

0.47.0 (2025-08-11)

  • feat(rear_collision_checker): support selecting safety metric from TTC or RSS (#11072)

    • fix: return distance to predicted collision point
    • refactor: move to utils
    • refactor: move to utils
    • refactor: generalize function
    • feat: selectable metric
    • chore: rename variable for readability

    * refactor: not use lambda ---------

  • refactor(planning_validator): refactor planning validator configuration and error handling (#11081)

    • refactor trajectory check error handling
    • define set_diag_status function for each module locally

    * update documentation ---------

  • style(pre-commit): update to clang-format-20 (#11088) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

  • refactor(rear_collision_checker): update parameter structure (#11067)

    • refactor(rear_collision_checker): update parameter structure

    * chore: remove unused msg type ---------

  • chore(rear_collision_checker): add maintainer (#11069)

  • feat(rear_collision_checker): improve collision detection logic (#10992)

    • feat(rear_collision_checker): added a parameter to configure how many seconds ahead to predict collisions

    * feat(rear_collision_checker): add parameter to enable collision check for forward obstacles ---------

  • feat(intersection_collision_checker): improve icc debug markers (#10967)

    • add DebugData struct
    • refactor and publish debug info and markers
    • always publish lanelet debug markers
    • refactor debug markers code
    • remove unused functions
    • pass string by reference
    • set is_safe flag for rear_collision_checker debug data
    • fix for cpp check

    * add maintainer ---------

  • feat(intersection_collision_checker): improve feature to reduce false positive occurrence (#10899)

    • keep a map of already detected target lanelets
    • fix on/off time buffers logic
    • add debug marker to visualize colliding object
    • use resampled trajectory instead of raw trajectory
    • fix overlap index computation
    • fix on/off time buffers logic for rear collision checker
    • fix planning .pages file, fix format
    • update readme
    • ignore not moving pcd object

    * handle case when object is very close to overlap point ---------

  • feat(planning_validator): improve intersection collision checker implementation (#10839)

    • use parameter generator library
    • add pointcloud latency compensation
    • change msg field name
    • add readme file
    • add parameters dection to readme
    • publish planning factor for intersection_collision_checker
    • refactor lanelet selection and filtering
    • update readme
    • set safety factor array in planning factor
    • clean up includes
    • publish planning factor for rear collision checker
    • fix spelling
    • rename variables to avoid shadowing

    * Update

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