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reaction_analyzer 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

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

Analyzer that measures reaction times of the nodes

Additional Links

No additional links.

Maintainers

  • Berkay Karaman

Authors

  • Berkay Karaman

Reaction Analyzer

Description

The main purpose of the reaction analyzer package is to measure the reaction times of various nodes within a ROS-based autonomous driving simulation environment by subscribing to pre-determined topics. This tool is particularly useful for evaluating the performance of perception, planning, and control pipelines in response to dynamic changes in the environment, such as sudden obstacles. To be able to measure both control outputs and perception outputs, it was necessary to divide the node into two running_mode: planning_control and perception_planning.

ReactionAnalyzerDesign.png

Planning Control Mode

In this mode, the reaction analyzer creates a dummy publisher for the PredictedObjects and PointCloud2 topics. In the beginning of the test, it publishes the initial position of the ego vehicle and the goal position to set the test environment. Then, it spawns a sudden obstacle in front of the ego vehicle. After the obstacle is spawned, it starts to search reacted messages of the planning and control nodes in the pre-determined topics. When all the topics are reacted, it calculates the reaction time of the nodes and statistics by comparing reacted_times of each of the nodes with spawn_cmd_time, and it creates a csv file to store the results.

Perception Planning Mode

In this mode, the reaction analyzer reads the rosbag files which are recorded from AWSIM, and it creates a topic publisher for each topic inside the rosbag to replay the rosbag. It reads two rosbag files: path_bag_without_object and path_bag_with_object. Firstly, it replays the path_bag_without_object to set the initial position of the ego vehicle and the goal position. After spawn_time_after_init seconds , it replays the path_bag_with_object to spawn a sudden obstacle in front of the ego vehicle. After the obstacle is spawned, it starts to search the reacted messages of the perception and planning nodes in the pre-determined topics. When all the topics are reacted, it calculates the reaction time of the nodes and statistics by comparing reacted_times of each of the nodes with spawn_cmd_time, and it creates a csv file to store the results.

Point Cloud Publisher Type

To get better analyze for Perception & Sensing pipeline, the reaction analyzer can publish the point cloud messages in 3 different ways: async_header_sync_publish, sync_header_sync_publish or async_publish. (T is the period of the lidar’s output)

PointcloudPublisherType.png

  • async_header_sync_publish: It publishes the point cloud messages synchronously with asynchronous header times. It means that each of the lidar’s output will be published at the same time, but the headers of the point cloud messages includes different timestamps because of the phase difference.
  • sync_header_sync_publish: It publishes the point cloud messages synchronously with synchronous header times. It means that each of the lidar’s output will be published at the same time, and the headers of the point cloud messages includes the same timestamps.
  • async_publish: It publishes the point cloud messages asynchronously. It means that each of the lidar’s output will be published at different times.

Usage

The common parameters you need to define for both running modes are output_file_path, test_iteration, and reaction_chain list. output_file_path is the output file path is the path where the results and statistics will be stored. test_iteration defines how many tests will be performed. The reaction_chain list is the list of the pre-defined topics you want to measure their reaction times.

IMPORTANT: Ensure the reaction_chain list is correctly defined:

  • For perception_planning mode, do not define Control nodes.
  • For planning_control mode, do not define Perception nodes.

Prepared Test Environment

  • Download the demonstration test map from the link here. After downloading, extract the zip file and use its path as [MAP_PATH] in the following commands.

Planning Control Mode

  • You need to define only Planning and Control nodes in the reaction_chain list. With the default parameters, you can start to test with the following command:
ros2 launch reaction_analyzer reaction_analyzer.launch.xml running_mode:=planning_control vehicle_model:=sample_vehicle sensor_model:=sample_sensor_kit map_path:=[MAP_PATH]

After the command, the simple_planning_simulator and the reaction_analyzer will be launched. It will automatically start to test. After the test is completed, the results will be stored in the output_file_path you defined.

Perception Planning Mode

  • Download the rosbag files from the Google Drive link here.
  • Extract the zip file and set the path of the .db3 files to parameters path_bag_without_object and path_bag_with_object.
  • You can start to test with the following command:
ros2 launch reaction_analyzer reaction_analyzer.launch.xml running_mode:=perception_planning vehicle_model:=sample_vehicle sensor_model:=awsim_labs_sensor_kit map_path:=[MAP_PATH]

  • On the first run of the tool in perception_planning mode, initialization might take longer than expected. Please allow some time for the process to complete.

After the command, the e2e_simulator and the reaction_analyzer will be launched. It will automatically start to test. After the test is completed, the results will be stored in the output_file_path you defined.

Prepared Test Environment

Scene without object:

File truncated at 100 lines see the full file

CHANGELOG

Changelog for package reaction_analyzer

0.47.0 (2025-08-11)

  • feat: change planning output topic name to /planning/trajectory (#11135)

    • change planning output topic name to /planning/trajectory

    * style(pre-commit): autofix ---------Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

  • 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>

  • style(pre-commit): autofix (#10982) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

  • Contributors: Mete Fatih Cırıt, Ryohsuke Mitsudome, Yukihiro Saito

0.46.0 (2025-06-20)

0.45.0 (2025-05-22)

0.44.2 (2025-06-10)

0.44.1 (2025-05-01)

0.44.0 (2025-04-18)

  • Merge remote-tracking branch 'origin/main' into humble

  • fix: add missing exec_depend (#10404)

    • fix missing exec depend
    • remove fixed depend

    * remove the removed dependency ---------

  • Contributors: Ryohsuke Mitsudome, Takagi, Isamu

0.43.0 (2025-03-21)

  • Merge remote-tracking branch 'origin/main' into chore/bump-version-0.43
  • chore: rename from [autoware.universe]{.title-ref} to [autoware_universe]{.title-ref} (#10306)
  • Contributors: Hayato Mizushima, Yutaka Kondo

0.42.0 (2025-03-03)

  • Merge remote-tracking branch 'origin/main' into tmp/bot/bump_version_base
  • feat(autoware_utils): replace autoware_universe_utils with autoware_utils (#10191)
  • fix: add missing includes to autoware_universe_utils (#10091)
  • Contributors: Fumiya Watanabe, Ryohsuke Mitsudome, 心刚

0.41.2 (2025-02-19)

  • chore: bump version to 0.41.1 (#10088)
  • Contributors: Ryohsuke Mitsudome

0.41.1 (2025-02-10)

0.41.0 (2025-01-29)

0.40.0 (2024-12-12)

  • Merge branch 'main' into release-0.40.0

  • Revert "chore(package.xml): bump version to 0.39.0 (#9587)" This reverts commit c9f0f2688c57b0f657f5c1f28f036a970682e7f5.

  • fix: fix ticket links in CHANGELOG.rst (#9588)

  • chore(package.xml): bump version to 0.39.0 (#9587)

    • chore(package.xml): bump version to 0.39.0
    • fix: fix ticket links in CHANGELOG.rst

    * fix: remove unnecessary diff ---------Co-authored-by: Yutaka Kondo <<yutaka.kondo@youtalk.jp>>

  • fix: fix ticket links in CHANGELOG.rst (#9588)

File truncated at 100 lines see the full file

Launch files

  • launch/reaction_analyzer.launch.xml
      • reaction_analyzer_param_path [default: $(find-pkg-share reaction_analyzer)/param/reaction_analyzer.param.yaml]
      • launch_simulator_perception_modules [default: false]
      • laserscan_based_occupancy_grid_map_param_path [default: $(find-pkg-share autoware_launch)/config/perception/occupancy_grid_map/laserscan_based_occupancy_grid_map.param.yaml]
      • occupancy_grid_map_updater [default: binary_bayes_filter]
      • occupancy_grid_map_updater_param_path [default: $(find-pkg-share autoware_launch)/config/perception/occupancy_grid_map/$(var occupancy_grid_map_updater)_updater.param.yaml]
      • running_mode [default: planning_control]
      • map_path
      • vehicle_model [default: sample_vehicle]
      • sensor_model [default: sample_sensor_kit]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

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reaction_analyzer 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

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

Analyzer that measures reaction times of the nodes

Additional Links

No additional links.

Maintainers

  • Berkay Karaman

Authors

  • Berkay Karaman

Reaction Analyzer

Description

The main purpose of the reaction analyzer package is to measure the reaction times of various nodes within a ROS-based autonomous driving simulation environment by subscribing to pre-determined topics. This tool is particularly useful for evaluating the performance of perception, planning, and control pipelines in response to dynamic changes in the environment, such as sudden obstacles. To be able to measure both control outputs and perception outputs, it was necessary to divide the node into two running_mode: planning_control and perception_planning.

ReactionAnalyzerDesign.png

Planning Control Mode

In this mode, the reaction analyzer creates a dummy publisher for the PredictedObjects and PointCloud2 topics. In the beginning of the test, it publishes the initial position of the ego vehicle and the goal position to set the test environment. Then, it spawns a sudden obstacle in front of the ego vehicle. After the obstacle is spawned, it starts to search reacted messages of the planning and control nodes in the pre-determined topics. When all the topics are reacted, it calculates the reaction time of the nodes and statistics by comparing reacted_times of each of the nodes with spawn_cmd_time, and it creates a csv file to store the results.

Perception Planning Mode

In this mode, the reaction analyzer reads the rosbag files which are recorded from AWSIM, and it creates a topic publisher for each topic inside the rosbag to replay the rosbag. It reads two rosbag files: path_bag_without_object and path_bag_with_object. Firstly, it replays the path_bag_without_object to set the initial position of the ego vehicle and the goal position. After spawn_time_after_init seconds , it replays the path_bag_with_object to spawn a sudden obstacle in front of the ego vehicle. After the obstacle is spawned, it starts to search the reacted messages of the perception and planning nodes in the pre-determined topics. When all the topics are reacted, it calculates the reaction time of the nodes and statistics by comparing reacted_times of each of the nodes with spawn_cmd_time, and it creates a csv file to store the results.

Point Cloud Publisher Type

To get better analyze for Perception & Sensing pipeline, the reaction analyzer can publish the point cloud messages in 3 different ways: async_header_sync_publish, sync_header_sync_publish or async_publish. (T is the period of the lidar’s output)

PointcloudPublisherType.png

  • async_header_sync_publish: It publishes the point cloud messages synchronously with asynchronous header times. It means that each of the lidar’s output will be published at the same time, but the headers of the point cloud messages includes different timestamps because of the phase difference.
  • sync_header_sync_publish: It publishes the point cloud messages synchronously with synchronous header times. It means that each of the lidar’s output will be published at the same time, and the headers of the point cloud messages includes the same timestamps.
  • async_publish: It publishes the point cloud messages asynchronously. It means that each of the lidar’s output will be published at different times.

Usage

The common parameters you need to define for both running modes are output_file_path, test_iteration, and reaction_chain list. output_file_path is the output file path is the path where the results and statistics will be stored. test_iteration defines how many tests will be performed. The reaction_chain list is the list of the pre-defined topics you want to measure their reaction times.

IMPORTANT: Ensure the reaction_chain list is correctly defined:

  • For perception_planning mode, do not define Control nodes.
  • For planning_control mode, do not define Perception nodes.

Prepared Test Environment

  • Download the demonstration test map from the link here. After downloading, extract the zip file and use its path as [MAP_PATH] in the following commands.

Planning Control Mode

  • You need to define only Planning and Control nodes in the reaction_chain list. With the default parameters, you can start to test with the following command:
ros2 launch reaction_analyzer reaction_analyzer.launch.xml running_mode:=planning_control vehicle_model:=sample_vehicle sensor_model:=sample_sensor_kit map_path:=[MAP_PATH]

After the command, the simple_planning_simulator and the reaction_analyzer will be launched. It will automatically start to test. After the test is completed, the results will be stored in the output_file_path you defined.

Perception Planning Mode

  • Download the rosbag files from the Google Drive link here.
  • Extract the zip file and set the path of the .db3 files to parameters path_bag_without_object and path_bag_with_object.
  • You can start to test with the following command:
ros2 launch reaction_analyzer reaction_analyzer.launch.xml running_mode:=perception_planning vehicle_model:=sample_vehicle sensor_model:=awsim_labs_sensor_kit map_path:=[MAP_PATH]

  • On the first run of the tool in perception_planning mode, initialization might take longer than expected. Please allow some time for the process to complete.

After the command, the e2e_simulator and the reaction_analyzer will be launched. It will automatically start to test. After the test is completed, the results will be stored in the output_file_path you defined.

Prepared Test Environment

Scene without object:

File truncated at 100 lines see the full file

CHANGELOG

Changelog for package reaction_analyzer

0.47.0 (2025-08-11)

  • feat: change planning output topic name to /planning/trajectory (#11135)

    • change planning output topic name to /planning/trajectory

    * style(pre-commit): autofix ---------Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

  • 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>

  • style(pre-commit): autofix (#10982) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

  • Contributors: Mete Fatih Cırıt, Ryohsuke Mitsudome, Yukihiro Saito

0.46.0 (2025-06-20)

0.45.0 (2025-05-22)

0.44.2 (2025-06-10)

0.44.1 (2025-05-01)

0.44.0 (2025-04-18)

  • Merge remote-tracking branch 'origin/main' into humble

  • fix: add missing exec_depend (#10404)

    • fix missing exec depend
    • remove fixed depend

    * remove the removed dependency ---------

  • Contributors: Ryohsuke Mitsudome, Takagi, Isamu

0.43.0 (2025-03-21)

  • Merge remote-tracking branch 'origin/main' into chore/bump-version-0.43
  • chore: rename from [autoware.universe]{.title-ref} to [autoware_universe]{.title-ref} (#10306)
  • Contributors: Hayato Mizushima, Yutaka Kondo

0.42.0 (2025-03-03)

  • Merge remote-tracking branch 'origin/main' into tmp/bot/bump_version_base
  • feat(autoware_utils): replace autoware_universe_utils with autoware_utils (#10191)
  • fix: add missing includes to autoware_universe_utils (#10091)
  • Contributors: Fumiya Watanabe, Ryohsuke Mitsudome, 心刚

0.41.2 (2025-02-19)

  • chore: bump version to 0.41.1 (#10088)
  • Contributors: Ryohsuke Mitsudome

0.41.1 (2025-02-10)

0.41.0 (2025-01-29)

0.40.0 (2024-12-12)

  • Merge branch 'main' into release-0.40.0

  • Revert "chore(package.xml): bump version to 0.39.0 (#9587)" This reverts commit c9f0f2688c57b0f657f5c1f28f036a970682e7f5.

  • fix: fix ticket links in CHANGELOG.rst (#9588)

  • chore(package.xml): bump version to 0.39.0 (#9587)

    • chore(package.xml): bump version to 0.39.0
    • fix: fix ticket links in CHANGELOG.rst

    * fix: remove unnecessary diff ---------Co-authored-by: Yutaka Kondo <<yutaka.kondo@youtalk.jp>>

  • fix: fix ticket links in CHANGELOG.rst (#9588)

File truncated at 100 lines see the full file

Launch files

  • launch/reaction_analyzer.launch.xml
      • reaction_analyzer_param_path [default: $(find-pkg-share reaction_analyzer)/param/reaction_analyzer.param.yaml]
      • launch_simulator_perception_modules [default: false]
      • laserscan_based_occupancy_grid_map_param_path [default: $(find-pkg-share autoware_launch)/config/perception/occupancy_grid_map/laserscan_based_occupancy_grid_map.param.yaml]
      • occupancy_grid_map_updater [default: binary_bayes_filter]
      • occupancy_grid_map_updater_param_path [default: $(find-pkg-share autoware_launch)/config/perception/occupancy_grid_map/$(var occupancy_grid_map_updater)_updater.param.yaml]
      • running_mode [default: planning_control]
      • map_path
      • vehicle_model [default: sample_vehicle]
      • sensor_model [default: sample_sensor_kit]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged reaction_analyzer at Robotics Stack Exchange

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Package symbol

reaction_analyzer 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

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

Analyzer that measures reaction times of the nodes

Additional Links

No additional links.

Maintainers

  • Berkay Karaman

Authors

  • Berkay Karaman

Reaction Analyzer

Description

The main purpose of the reaction analyzer package is to measure the reaction times of various nodes within a ROS-based autonomous driving simulation environment by subscribing to pre-determined topics. This tool is particularly useful for evaluating the performance of perception, planning, and control pipelines in response to dynamic changes in the environment, such as sudden obstacles. To be able to measure both control outputs and perception outputs, it was necessary to divide the node into two running_mode: planning_control and perception_planning.

ReactionAnalyzerDesign.png

Planning Control Mode

In this mode, the reaction analyzer creates a dummy publisher for the PredictedObjects and PointCloud2 topics. In the beginning of the test, it publishes the initial position of the ego vehicle and the goal position to set the test environment. Then, it spawns a sudden obstacle in front of the ego vehicle. After the obstacle is spawned, it starts to search reacted messages of the planning and control nodes in the pre-determined topics. When all the topics are reacted, it calculates the reaction time of the nodes and statistics by comparing reacted_times of each of the nodes with spawn_cmd_time, and it creates a csv file to store the results.

Perception Planning Mode

In this mode, the reaction analyzer reads the rosbag files which are recorded from AWSIM, and it creates a topic publisher for each topic inside the rosbag to replay the rosbag. It reads two rosbag files: path_bag_without_object and path_bag_with_object. Firstly, it replays the path_bag_without_object to set the initial position of the ego vehicle and the goal position. After spawn_time_after_init seconds , it replays the path_bag_with_object to spawn a sudden obstacle in front of the ego vehicle. After the obstacle is spawned, it starts to search the reacted messages of the perception and planning nodes in the pre-determined topics. When all the topics are reacted, it calculates the reaction time of the nodes and statistics by comparing reacted_times of each of the nodes with spawn_cmd_time, and it creates a csv file to store the results.

Point Cloud Publisher Type

To get better analyze for Perception & Sensing pipeline, the reaction analyzer can publish the point cloud messages in 3 different ways: async_header_sync_publish, sync_header_sync_publish or async_publish. (T is the period of the lidar’s output)

PointcloudPublisherType.png

  • async_header_sync_publish: It publishes the point cloud messages synchronously with asynchronous header times. It means that each of the lidar’s output will be published at the same time, but the headers of the point cloud messages includes different timestamps because of the phase difference.
  • sync_header_sync_publish: It publishes the point cloud messages synchronously with synchronous header times. It means that each of the lidar’s output will be published at the same time, and the headers of the point cloud messages includes the same timestamps.
  • async_publish: It publishes the point cloud messages asynchronously. It means that each of the lidar’s output will be published at different times.

Usage

The common parameters you need to define for both running modes are output_file_path, test_iteration, and reaction_chain list. output_file_path is the output file path is the path where the results and statistics will be stored. test_iteration defines how many tests will be performed. The reaction_chain list is the list of the pre-defined topics you want to measure their reaction times.

IMPORTANT: Ensure the reaction_chain list is correctly defined:

  • For perception_planning mode, do not define Control nodes.
  • For planning_control mode, do not define Perception nodes.

Prepared Test Environment

  • Download the demonstration test map from the link here. After downloading, extract the zip file and use its path as [MAP_PATH] in the following commands.

Planning Control Mode

  • You need to define only Planning and Control nodes in the reaction_chain list. With the default parameters, you can start to test with the following command:
ros2 launch reaction_analyzer reaction_analyzer.launch.xml running_mode:=planning_control vehicle_model:=sample_vehicle sensor_model:=sample_sensor_kit map_path:=[MAP_PATH]

After the command, the simple_planning_simulator and the reaction_analyzer will be launched. It will automatically start to test. After the test is completed, the results will be stored in the output_file_path you defined.

Perception Planning Mode

  • Download the rosbag files from the Google Drive link here.
  • Extract the zip file and set the path of the .db3 files to parameters path_bag_without_object and path_bag_with_object.
  • You can start to test with the following command:
ros2 launch reaction_analyzer reaction_analyzer.launch.xml running_mode:=perception_planning vehicle_model:=sample_vehicle sensor_model:=awsim_labs_sensor_kit map_path:=[MAP_PATH]

  • On the first run of the tool in perception_planning mode, initialization might take longer than expected. Please allow some time for the process to complete.

After the command, the e2e_simulator and the reaction_analyzer will be launched. It will automatically start to test. After the test is completed, the results will be stored in the output_file_path you defined.

Prepared Test Environment

Scene without object:

File truncated at 100 lines see the full file

CHANGELOG

Changelog for package reaction_analyzer

0.47.0 (2025-08-11)

  • feat: change planning output topic name to /planning/trajectory (#11135)

    • change planning output topic name to /planning/trajectory

    * style(pre-commit): autofix ---------Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

  • 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>

  • style(pre-commit): autofix (#10982) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

  • Contributors: Mete Fatih Cırıt, Ryohsuke Mitsudome, Yukihiro Saito

0.46.0 (2025-06-20)

0.45.0 (2025-05-22)

0.44.2 (2025-06-10)

0.44.1 (2025-05-01)

0.44.0 (2025-04-18)

  • Merge remote-tracking branch 'origin/main' into humble

  • fix: add missing exec_depend (#10404)

    • fix missing exec depend
    • remove fixed depend

    * remove the removed dependency ---------

  • Contributors: Ryohsuke Mitsudome, Takagi, Isamu

0.43.0 (2025-03-21)

  • Merge remote-tracking branch 'origin/main' into chore/bump-version-0.43
  • chore: rename from [autoware.universe]{.title-ref} to [autoware_universe]{.title-ref} (#10306)
  • Contributors: Hayato Mizushima, Yutaka Kondo

0.42.0 (2025-03-03)

  • Merge remote-tracking branch 'origin/main' into tmp/bot/bump_version_base
  • feat(autoware_utils): replace autoware_universe_utils with autoware_utils (#10191)
  • fix: add missing includes to autoware_universe_utils (#10091)
  • Contributors: Fumiya Watanabe, Ryohsuke Mitsudome, 心刚

0.41.2 (2025-02-19)

  • chore: bump version to 0.41.1 (#10088)
  • Contributors: Ryohsuke Mitsudome

0.41.1 (2025-02-10)

0.41.0 (2025-01-29)

0.40.0 (2024-12-12)

  • Merge branch 'main' into release-0.40.0

  • Revert "chore(package.xml): bump version to 0.39.0 (#9587)" This reverts commit c9f0f2688c57b0f657f5c1f28f036a970682e7f5.

  • fix: fix ticket links in CHANGELOG.rst (#9588)

  • chore(package.xml): bump version to 0.39.0 (#9587)

    • chore(package.xml): bump version to 0.39.0
    • fix: fix ticket links in CHANGELOG.rst

    * fix: remove unnecessary diff ---------Co-authored-by: Yutaka Kondo <<yutaka.kondo@youtalk.jp>>

  • fix: fix ticket links in CHANGELOG.rst (#9588)

File truncated at 100 lines see the full file

Launch files

  • launch/reaction_analyzer.launch.xml
      • reaction_analyzer_param_path [default: $(find-pkg-share reaction_analyzer)/param/reaction_analyzer.param.yaml]
      • launch_simulator_perception_modules [default: false]
      • laserscan_based_occupancy_grid_map_param_path [default: $(find-pkg-share autoware_launch)/config/perception/occupancy_grid_map/laserscan_based_occupancy_grid_map.param.yaml]
      • occupancy_grid_map_updater [default: binary_bayes_filter]
      • occupancy_grid_map_updater_param_path [default: $(find-pkg-share autoware_launch)/config/perception/occupancy_grid_map/$(var occupancy_grid_map_updater)_updater.param.yaml]
      • running_mode [default: planning_control]
      • map_path
      • vehicle_model [default: sample_vehicle]
      • sensor_model [default: sample_sensor_kit]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged reaction_analyzer at Robotics Stack Exchange

No version for distro rolling showing github. Known supported distros are highlighted in the buttons above.
Package symbol

reaction_analyzer 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

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

Analyzer that measures reaction times of the nodes

Additional Links

No additional links.

Maintainers

  • Berkay Karaman

Authors

  • Berkay Karaman

Reaction Analyzer

Description

The main purpose of the reaction analyzer package is to measure the reaction times of various nodes within a ROS-based autonomous driving simulation environment by subscribing to pre-determined topics. This tool is particularly useful for evaluating the performance of perception, planning, and control pipelines in response to dynamic changes in the environment, such as sudden obstacles. To be able to measure both control outputs and perception outputs, it was necessary to divide the node into two running_mode: planning_control and perception_planning.

ReactionAnalyzerDesign.png

Planning Control Mode

In this mode, the reaction analyzer creates a dummy publisher for the PredictedObjects and PointCloud2 topics. In the beginning of the test, it publishes the initial position of the ego vehicle and the goal position to set the test environment. Then, it spawns a sudden obstacle in front of the ego vehicle. After the obstacle is spawned, it starts to search reacted messages of the planning and control nodes in the pre-determined topics. When all the topics are reacted, it calculates the reaction time of the nodes and statistics by comparing reacted_times of each of the nodes with spawn_cmd_time, and it creates a csv file to store the results.

Perception Planning Mode

In this mode, the reaction analyzer reads the rosbag files which are recorded from AWSIM, and it creates a topic publisher for each topic inside the rosbag to replay the rosbag. It reads two rosbag files: path_bag_without_object and path_bag_with_object. Firstly, it replays the path_bag_without_object to set the initial position of the ego vehicle and the goal position. After spawn_time_after_init seconds , it replays the path_bag_with_object to spawn a sudden obstacle in front of the ego vehicle. After the obstacle is spawned, it starts to search the reacted messages of the perception and planning nodes in the pre-determined topics. When all the topics are reacted, it calculates the reaction time of the nodes and statistics by comparing reacted_times of each of the nodes with spawn_cmd_time, and it creates a csv file to store the results.

Point Cloud Publisher Type

To get better analyze for Perception & Sensing pipeline, the reaction analyzer can publish the point cloud messages in 3 different ways: async_header_sync_publish, sync_header_sync_publish or async_publish. (T is the period of the lidar’s output)

PointcloudPublisherType.png

  • async_header_sync_publish: It publishes the point cloud messages synchronously with asynchronous header times. It means that each of the lidar’s output will be published at the same time, but the headers of the point cloud messages includes different timestamps because of the phase difference.
  • sync_header_sync_publish: It publishes the point cloud messages synchronously with synchronous header times. It means that each of the lidar’s output will be published at the same time, and the headers of the point cloud messages includes the same timestamps.
  • async_publish: It publishes the point cloud messages asynchronously. It means that each of the lidar’s output will be published at different times.

Usage

The common parameters you need to define for both running modes are output_file_path, test_iteration, and reaction_chain list. output_file_path is the output file path is the path where the results and statistics will be stored. test_iteration defines how many tests will be performed. The reaction_chain list is the list of the pre-defined topics you want to measure their reaction times.

IMPORTANT: Ensure the reaction_chain list is correctly defined:

  • For perception_planning mode, do not define Control nodes.
  • For planning_control mode, do not define Perception nodes.

Prepared Test Environment

  • Download the demonstration test map from the link here. After downloading, extract the zip file and use its path as [MAP_PATH] in the following commands.

Planning Control Mode

  • You need to define only Planning and Control nodes in the reaction_chain list. With the default parameters, you can start to test with the following command:
ros2 launch reaction_analyzer reaction_analyzer.launch.xml running_mode:=planning_control vehicle_model:=sample_vehicle sensor_model:=sample_sensor_kit map_path:=[MAP_PATH]

After the command, the simple_planning_simulator and the reaction_analyzer will be launched. It will automatically start to test. After the test is completed, the results will be stored in the output_file_path you defined.

Perception Planning Mode

  • Download the rosbag files from the Google Drive link here.
  • Extract the zip file and set the path of the .db3 files to parameters path_bag_without_object and path_bag_with_object.
  • You can start to test with the following command:
ros2 launch reaction_analyzer reaction_analyzer.launch.xml running_mode:=perception_planning vehicle_model:=sample_vehicle sensor_model:=awsim_labs_sensor_kit map_path:=[MAP_PATH]

  • On the first run of the tool in perception_planning mode, initialization might take longer than expected. Please allow some time for the process to complete.

After the command, the e2e_simulator and the reaction_analyzer will be launched. It will automatically start to test. After the test is completed, the results will be stored in the output_file_path you defined.

Prepared Test Environment

Scene without object:

File truncated at 100 lines see the full file

CHANGELOG

Changelog for package reaction_analyzer

0.47.0 (2025-08-11)

  • feat: change planning output topic name to /planning/trajectory (#11135)

    • change planning output topic name to /planning/trajectory

    * style(pre-commit): autofix ---------Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

  • 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>

  • style(pre-commit): autofix (#10982) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

  • Contributors: Mete Fatih Cırıt, Ryohsuke Mitsudome, Yukihiro Saito

0.46.0 (2025-06-20)

0.45.0 (2025-05-22)

0.44.2 (2025-06-10)

0.44.1 (2025-05-01)

0.44.0 (2025-04-18)

  • Merge remote-tracking branch 'origin/main' into humble

  • fix: add missing exec_depend (#10404)

    • fix missing exec depend
    • remove fixed depend

    * remove the removed dependency ---------

  • Contributors: Ryohsuke Mitsudome, Takagi, Isamu

0.43.0 (2025-03-21)

  • Merge remote-tracking branch 'origin/main' into chore/bump-version-0.43
  • chore: rename from [autoware.universe]{.title-ref} to [autoware_universe]{.title-ref} (#10306)
  • Contributors: Hayato Mizushima, Yutaka Kondo

0.42.0 (2025-03-03)

  • Merge remote-tracking branch 'origin/main' into tmp/bot/bump_version_base
  • feat(autoware_utils): replace autoware_universe_utils with autoware_utils (#10191)
  • fix: add missing includes to autoware_universe_utils (#10091)
  • Contributors: Fumiya Watanabe, Ryohsuke Mitsudome, 心刚

0.41.2 (2025-02-19)

  • chore: bump version to 0.41.1 (#10088)
  • Contributors: Ryohsuke Mitsudome

0.41.1 (2025-02-10)

0.41.0 (2025-01-29)

0.40.0 (2024-12-12)

  • Merge branch 'main' into release-0.40.0

  • Revert "chore(package.xml): bump version to 0.39.0 (#9587)" This reverts commit c9f0f2688c57b0f657f5c1f28f036a970682e7f5.

  • fix: fix ticket links in CHANGELOG.rst (#9588)

  • chore(package.xml): bump version to 0.39.0 (#9587)

    • chore(package.xml): bump version to 0.39.0
    • fix: fix ticket links in CHANGELOG.rst

    * fix: remove unnecessary diff ---------Co-authored-by: Yutaka Kondo <<yutaka.kondo@youtalk.jp>>

  • fix: fix ticket links in CHANGELOG.rst (#9588)

File truncated at 100 lines see the full file

Launch files

  • launch/reaction_analyzer.launch.xml
      • reaction_analyzer_param_path [default: $(find-pkg-share reaction_analyzer)/param/reaction_analyzer.param.yaml]
      • launch_simulator_perception_modules [default: false]
      • laserscan_based_occupancy_grid_map_param_path [default: $(find-pkg-share autoware_launch)/config/perception/occupancy_grid_map/laserscan_based_occupancy_grid_map.param.yaml]
      • occupancy_grid_map_updater [default: binary_bayes_filter]
      • occupancy_grid_map_updater_param_path [default: $(find-pkg-share autoware_launch)/config/perception/occupancy_grid_map/$(var occupancy_grid_map_updater)_updater.param.yaml]
      • running_mode [default: planning_control]
      • map_path
      • vehicle_model [default: sample_vehicle]
      • sensor_model [default: sample_sensor_kit]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged reaction_analyzer at Robotics Stack Exchange

Package symbol

reaction_analyzer 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

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

Analyzer that measures reaction times of the nodes

Additional Links

No additional links.

Maintainers

  • Berkay Karaman

Authors

  • Berkay Karaman

Reaction Analyzer

Description

The main purpose of the reaction analyzer package is to measure the reaction times of various nodes within a ROS-based autonomous driving simulation environment by subscribing to pre-determined topics. This tool is particularly useful for evaluating the performance of perception, planning, and control pipelines in response to dynamic changes in the environment, such as sudden obstacles. To be able to measure both control outputs and perception outputs, it was necessary to divide the node into two running_mode: planning_control and perception_planning.

ReactionAnalyzerDesign.png

Planning Control Mode

In this mode, the reaction analyzer creates a dummy publisher for the PredictedObjects and PointCloud2 topics. In the beginning of the test, it publishes the initial position of the ego vehicle and the goal position to set the test environment. Then, it spawns a sudden obstacle in front of the ego vehicle. After the obstacle is spawned, it starts to search reacted messages of the planning and control nodes in the pre-determined topics. When all the topics are reacted, it calculates the reaction time of the nodes and statistics by comparing reacted_times of each of the nodes with spawn_cmd_time, and it creates a csv file to store the results.

Perception Planning Mode

In this mode, the reaction analyzer reads the rosbag files which are recorded from AWSIM, and it creates a topic publisher for each topic inside the rosbag to replay the rosbag. It reads two rosbag files: path_bag_without_object and path_bag_with_object. Firstly, it replays the path_bag_without_object to set the initial position of the ego vehicle and the goal position. After spawn_time_after_init seconds , it replays the path_bag_with_object to spawn a sudden obstacle in front of the ego vehicle. After the obstacle is spawned, it starts to search the reacted messages of the perception and planning nodes in the pre-determined topics. When all the topics are reacted, it calculates the reaction time of the nodes and statistics by comparing reacted_times of each of the nodes with spawn_cmd_time, and it creates a csv file to store the results.

Point Cloud Publisher Type

To get better analyze for Perception & Sensing pipeline, the reaction analyzer can publish the point cloud messages in 3 different ways: async_header_sync_publish, sync_header_sync_publish or async_publish. (T is the period of the lidar’s output)

PointcloudPublisherType.png

  • async_header_sync_publish: It publishes the point cloud messages synchronously with asynchronous header times. It means that each of the lidar’s output will be published at the same time, but the headers of the point cloud messages includes different timestamps because of the phase difference.
  • sync_header_sync_publish: It publishes the point cloud messages synchronously with synchronous header times. It means that each of the lidar’s output will be published at the same time, and the headers of the point cloud messages includes the same timestamps.
  • async_publish: It publishes the point cloud messages asynchronously. It means that each of the lidar’s output will be published at different times.

Usage

The common parameters you need to define for both running modes are output_file_path, test_iteration, and reaction_chain list. output_file_path is the output file path is the path where the results and statistics will be stored. test_iteration defines how many tests will be performed. The reaction_chain list is the list of the pre-defined topics you want to measure their reaction times.

IMPORTANT: Ensure the reaction_chain list is correctly defined:

  • For perception_planning mode, do not define Control nodes.
  • For planning_control mode, do not define Perception nodes.

Prepared Test Environment

  • Download the demonstration test map from the link here. After downloading, extract the zip file and use its path as [MAP_PATH] in the following commands.

Planning Control Mode

  • You need to define only Planning and Control nodes in the reaction_chain list. With the default parameters, you can start to test with the following command:
ros2 launch reaction_analyzer reaction_analyzer.launch.xml running_mode:=planning_control vehicle_model:=sample_vehicle sensor_model:=sample_sensor_kit map_path:=[MAP_PATH]

After the command, the simple_planning_simulator and the reaction_analyzer will be launched. It will automatically start to test. After the test is completed, the results will be stored in the output_file_path you defined.

Perception Planning Mode

  • Download the rosbag files from the Google Drive link here.
  • Extract the zip file and set the path of the .db3 files to parameters path_bag_without_object and path_bag_with_object.
  • You can start to test with the following command:
ros2 launch reaction_analyzer reaction_analyzer.launch.xml running_mode:=perception_planning vehicle_model:=sample_vehicle sensor_model:=awsim_labs_sensor_kit map_path:=[MAP_PATH]

  • On the first run of the tool in perception_planning mode, initialization might take longer than expected. Please allow some time for the process to complete.

After the command, the e2e_simulator and the reaction_analyzer will be launched. It will automatically start to test. After the test is completed, the results will be stored in the output_file_path you defined.

Prepared Test Environment

Scene without object:

File truncated at 100 lines see the full file

CHANGELOG

Changelog for package reaction_analyzer

0.47.0 (2025-08-11)

  • feat: change planning output topic name to /planning/trajectory (#11135)

    • change planning output topic name to /planning/trajectory

    * style(pre-commit): autofix ---------Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

  • 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>

  • style(pre-commit): autofix (#10982) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

  • Contributors: Mete Fatih Cırıt, Ryohsuke Mitsudome, Yukihiro Saito

0.46.0 (2025-06-20)

0.45.0 (2025-05-22)

0.44.2 (2025-06-10)

0.44.1 (2025-05-01)

0.44.0 (2025-04-18)

  • Merge remote-tracking branch 'origin/main' into humble

  • fix: add missing exec_depend (#10404)

    • fix missing exec depend
    • remove fixed depend

    * remove the removed dependency ---------

  • Contributors: Ryohsuke Mitsudome, Takagi, Isamu

0.43.0 (2025-03-21)

  • Merge remote-tracking branch 'origin/main' into chore/bump-version-0.43
  • chore: rename from [autoware.universe]{.title-ref} to [autoware_universe]{.title-ref} (#10306)
  • Contributors: Hayato Mizushima, Yutaka Kondo

0.42.0 (2025-03-03)

  • Merge remote-tracking branch 'origin/main' into tmp/bot/bump_version_base
  • feat(autoware_utils): replace autoware_universe_utils with autoware_utils (#10191)
  • fix: add missing includes to autoware_universe_utils (#10091)
  • Contributors: Fumiya Watanabe, Ryohsuke Mitsudome, 心刚

0.41.2 (2025-02-19)

  • chore: bump version to 0.41.1 (#10088)
  • Contributors: Ryohsuke Mitsudome

0.41.1 (2025-02-10)

0.41.0 (2025-01-29)

0.40.0 (2024-12-12)

  • Merge branch 'main' into release-0.40.0

  • Revert "chore(package.xml): bump version to 0.39.0 (#9587)" This reverts commit c9f0f2688c57b0f657f5c1f28f036a970682e7f5.

  • fix: fix ticket links in CHANGELOG.rst (#9588)

  • chore(package.xml): bump version to 0.39.0 (#9587)

    • chore(package.xml): bump version to 0.39.0
    • fix: fix ticket links in CHANGELOG.rst

    * fix: remove unnecessary diff ---------Co-authored-by: Yutaka Kondo <<yutaka.kondo@youtalk.jp>>

  • fix: fix ticket links in CHANGELOG.rst (#9588)

File truncated at 100 lines see the full file

Launch files

  • launch/reaction_analyzer.launch.xml
      • reaction_analyzer_param_path [default: $(find-pkg-share reaction_analyzer)/param/reaction_analyzer.param.yaml]
      • launch_simulator_perception_modules [default: false]
      • laserscan_based_occupancy_grid_map_param_path [default: $(find-pkg-share autoware_launch)/config/perception/occupancy_grid_map/laserscan_based_occupancy_grid_map.param.yaml]
      • occupancy_grid_map_updater [default: binary_bayes_filter]
      • occupancy_grid_map_updater_param_path [default: $(find-pkg-share autoware_launch)/config/perception/occupancy_grid_map/$(var occupancy_grid_map_updater)_updater.param.yaml]
      • running_mode [default: planning_control]
      • map_path
      • vehicle_model [default: sample_vehicle]
      • sensor_model [default: sample_sensor_kit]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged reaction_analyzer at Robotics Stack Exchange

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Package symbol

reaction_analyzer 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

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

Analyzer that measures reaction times of the nodes

Additional Links

No additional links.

Maintainers

  • Berkay Karaman

Authors

  • Berkay Karaman

Reaction Analyzer

Description

The main purpose of the reaction analyzer package is to measure the reaction times of various nodes within a ROS-based autonomous driving simulation environment by subscribing to pre-determined topics. This tool is particularly useful for evaluating the performance of perception, planning, and control pipelines in response to dynamic changes in the environment, such as sudden obstacles. To be able to measure both control outputs and perception outputs, it was necessary to divide the node into two running_mode: planning_control and perception_planning.

ReactionAnalyzerDesign.png

Planning Control Mode

In this mode, the reaction analyzer creates a dummy publisher for the PredictedObjects and PointCloud2 topics. In the beginning of the test, it publishes the initial position of the ego vehicle and the goal position to set the test environment. Then, it spawns a sudden obstacle in front of the ego vehicle. After the obstacle is spawned, it starts to search reacted messages of the planning and control nodes in the pre-determined topics. When all the topics are reacted, it calculates the reaction time of the nodes and statistics by comparing reacted_times of each of the nodes with spawn_cmd_time, and it creates a csv file to store the results.

Perception Planning Mode

In this mode, the reaction analyzer reads the rosbag files which are recorded from AWSIM, and it creates a topic publisher for each topic inside the rosbag to replay the rosbag. It reads two rosbag files: path_bag_without_object and path_bag_with_object. Firstly, it replays the path_bag_without_object to set the initial position of the ego vehicle and the goal position. After spawn_time_after_init seconds , it replays the path_bag_with_object to spawn a sudden obstacle in front of the ego vehicle. After the obstacle is spawned, it starts to search the reacted messages of the perception and planning nodes in the pre-determined topics. When all the topics are reacted, it calculates the reaction time of the nodes and statistics by comparing reacted_times of each of the nodes with spawn_cmd_time, and it creates a csv file to store the results.

Point Cloud Publisher Type

To get better analyze for Perception & Sensing pipeline, the reaction analyzer can publish the point cloud messages in 3 different ways: async_header_sync_publish, sync_header_sync_publish or async_publish. (T is the period of the lidar’s output)

PointcloudPublisherType.png

  • async_header_sync_publish: It publishes the point cloud messages synchronously with asynchronous header times. It means that each of the lidar’s output will be published at the same time, but the headers of the point cloud messages includes different timestamps because of the phase difference.
  • sync_header_sync_publish: It publishes the point cloud messages synchronously with synchronous header times. It means that each of the lidar’s output will be published at the same time, and the headers of the point cloud messages includes the same timestamps.
  • async_publish: It publishes the point cloud messages asynchronously. It means that each of the lidar’s output will be published at different times.

Usage

The common parameters you need to define for both running modes are output_file_path, test_iteration, and reaction_chain list. output_file_path is the output file path is the path where the results and statistics will be stored. test_iteration defines how many tests will be performed. The reaction_chain list is the list of the pre-defined topics you want to measure their reaction times.

IMPORTANT: Ensure the reaction_chain list is correctly defined:

  • For perception_planning mode, do not define Control nodes.
  • For planning_control mode, do not define Perception nodes.

Prepared Test Environment

  • Download the demonstration test map from the link here. After downloading, extract the zip file and use its path as [MAP_PATH] in the following commands.

Planning Control Mode

  • You need to define only Planning and Control nodes in the reaction_chain list. With the default parameters, you can start to test with the following command:
ros2 launch reaction_analyzer reaction_analyzer.launch.xml running_mode:=planning_control vehicle_model:=sample_vehicle sensor_model:=sample_sensor_kit map_path:=[MAP_PATH]

After the command, the simple_planning_simulator and the reaction_analyzer will be launched. It will automatically start to test. After the test is completed, the results will be stored in the output_file_path you defined.

Perception Planning Mode

  • Download the rosbag files from the Google Drive link here.
  • Extract the zip file and set the path of the .db3 files to parameters path_bag_without_object and path_bag_with_object.
  • You can start to test with the following command:
ros2 launch reaction_analyzer reaction_analyzer.launch.xml running_mode:=perception_planning vehicle_model:=sample_vehicle sensor_model:=awsim_labs_sensor_kit map_path:=[MAP_PATH]

  • On the first run of the tool in perception_planning mode, initialization might take longer than expected. Please allow some time for the process to complete.

After the command, the e2e_simulator and the reaction_analyzer will be launched. It will automatically start to test. After the test is completed, the results will be stored in the output_file_path you defined.

Prepared Test Environment

Scene without object:

File truncated at 100 lines see the full file

CHANGELOG

Changelog for package reaction_analyzer

0.47.0 (2025-08-11)

  • feat: change planning output topic name to /planning/trajectory (#11135)

    • change planning output topic name to /planning/trajectory

    * style(pre-commit): autofix ---------Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

  • 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>

  • style(pre-commit): autofix (#10982) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

  • Contributors: Mete Fatih Cırıt, Ryohsuke Mitsudome, Yukihiro Saito

0.46.0 (2025-06-20)

0.45.0 (2025-05-22)

0.44.2 (2025-06-10)

0.44.1 (2025-05-01)

0.44.0 (2025-04-18)

  • Merge remote-tracking branch 'origin/main' into humble

  • fix: add missing exec_depend (#10404)

    • fix missing exec depend
    • remove fixed depend

    * remove the removed dependency ---------

  • Contributors: Ryohsuke Mitsudome, Takagi, Isamu

0.43.0 (2025-03-21)

  • Merge remote-tracking branch 'origin/main' into chore/bump-version-0.43
  • chore: rename from [autoware.universe]{.title-ref} to [autoware_universe]{.title-ref} (#10306)
  • Contributors: Hayato Mizushima, Yutaka Kondo

0.42.0 (2025-03-03)

  • Merge remote-tracking branch 'origin/main' into tmp/bot/bump_version_base
  • feat(autoware_utils): replace autoware_universe_utils with autoware_utils (#10191)
  • fix: add missing includes to autoware_universe_utils (#10091)
  • Contributors: Fumiya Watanabe, Ryohsuke Mitsudome, 心刚

0.41.2 (2025-02-19)

  • chore: bump version to 0.41.1 (#10088)
  • Contributors: Ryohsuke Mitsudome

0.41.1 (2025-02-10)

0.41.0 (2025-01-29)

0.40.0 (2024-12-12)

  • Merge branch 'main' into release-0.40.0

  • Revert "chore(package.xml): bump version to 0.39.0 (#9587)" This reverts commit c9f0f2688c57b0f657f5c1f28f036a970682e7f5.

  • fix: fix ticket links in CHANGELOG.rst (#9588)

  • chore(package.xml): bump version to 0.39.0 (#9587)

    • chore(package.xml): bump version to 0.39.0
    • fix: fix ticket links in CHANGELOG.rst

    * fix: remove unnecessary diff ---------Co-authored-by: Yutaka Kondo <<yutaka.kondo@youtalk.jp>>

  • fix: fix ticket links in CHANGELOG.rst (#9588)

File truncated at 100 lines see the full file

Launch files

  • launch/reaction_analyzer.launch.xml
      • reaction_analyzer_param_path [default: $(find-pkg-share reaction_analyzer)/param/reaction_analyzer.param.yaml]
      • launch_simulator_perception_modules [default: false]
      • laserscan_based_occupancy_grid_map_param_path [default: $(find-pkg-share autoware_launch)/config/perception/occupancy_grid_map/laserscan_based_occupancy_grid_map.param.yaml]
      • occupancy_grid_map_updater [default: binary_bayes_filter]
      • occupancy_grid_map_updater_param_path [default: $(find-pkg-share autoware_launch)/config/perception/occupancy_grid_map/$(var occupancy_grid_map_updater)_updater.param.yaml]
      • running_mode [default: planning_control]
      • map_path
      • vehicle_model [default: sample_vehicle]
      • sensor_model [default: sample_sensor_kit]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged reaction_analyzer at Robotics Stack Exchange

No version for distro iron showing github. Known supported distros are highlighted in the buttons above.
Package symbol

reaction_analyzer 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

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

Analyzer that measures reaction times of the nodes

Additional Links

No additional links.

Maintainers

  • Berkay Karaman

Authors

  • Berkay Karaman

Reaction Analyzer

Description

The main purpose of the reaction analyzer package is to measure the reaction times of various nodes within a ROS-based autonomous driving simulation environment by subscribing to pre-determined topics. This tool is particularly useful for evaluating the performance of perception, planning, and control pipelines in response to dynamic changes in the environment, such as sudden obstacles. To be able to measure both control outputs and perception outputs, it was necessary to divide the node into two running_mode: planning_control and perception_planning.

ReactionAnalyzerDesign.png

Planning Control Mode

In this mode, the reaction analyzer creates a dummy publisher for the PredictedObjects and PointCloud2 topics. In the beginning of the test, it publishes the initial position of the ego vehicle and the goal position to set the test environment. Then, it spawns a sudden obstacle in front of the ego vehicle. After the obstacle is spawned, it starts to search reacted messages of the planning and control nodes in the pre-determined topics. When all the topics are reacted, it calculates the reaction time of the nodes and statistics by comparing reacted_times of each of the nodes with spawn_cmd_time, and it creates a csv file to store the results.

Perception Planning Mode

In this mode, the reaction analyzer reads the rosbag files which are recorded from AWSIM, and it creates a topic publisher for each topic inside the rosbag to replay the rosbag. It reads two rosbag files: path_bag_without_object and path_bag_with_object. Firstly, it replays the path_bag_without_object to set the initial position of the ego vehicle and the goal position. After spawn_time_after_init seconds , it replays the path_bag_with_object to spawn a sudden obstacle in front of the ego vehicle. After the obstacle is spawned, it starts to search the reacted messages of the perception and planning nodes in the pre-determined topics. When all the topics are reacted, it calculates the reaction time of the nodes and statistics by comparing reacted_times of each of the nodes with spawn_cmd_time, and it creates a csv file to store the results.

Point Cloud Publisher Type

To get better analyze for Perception & Sensing pipeline, the reaction analyzer can publish the point cloud messages in 3 different ways: async_header_sync_publish, sync_header_sync_publish or async_publish. (T is the period of the lidar’s output)

PointcloudPublisherType.png

  • async_header_sync_publish: It publishes the point cloud messages synchronously with asynchronous header times. It means that each of the lidar’s output will be published at the same time, but the headers of the point cloud messages includes different timestamps because of the phase difference.
  • sync_header_sync_publish: It publishes the point cloud messages synchronously with synchronous header times. It means that each of the lidar’s output will be published at the same time, and the headers of the point cloud messages includes the same timestamps.
  • async_publish: It publishes the point cloud messages asynchronously. It means that each of the lidar’s output will be published at different times.

Usage

The common parameters you need to define for both running modes are output_file_path, test_iteration, and reaction_chain list. output_file_path is the output file path is the path where the results and statistics will be stored. test_iteration defines how many tests will be performed. The reaction_chain list is the list of the pre-defined topics you want to measure their reaction times.

IMPORTANT: Ensure the reaction_chain list is correctly defined:

  • For perception_planning mode, do not define Control nodes.
  • For planning_control mode, do not define Perception nodes.

Prepared Test Environment

  • Download the demonstration test map from the link here. After downloading, extract the zip file and use its path as [MAP_PATH] in the following commands.

Planning Control Mode

  • You need to define only Planning and Control nodes in the reaction_chain list. With the default parameters, you can start to test with the following command:
ros2 launch reaction_analyzer reaction_analyzer.launch.xml running_mode:=planning_control vehicle_model:=sample_vehicle sensor_model:=sample_sensor_kit map_path:=[MAP_PATH]

After the command, the simple_planning_simulator and the reaction_analyzer will be launched. It will automatically start to test. After the test is completed, the results will be stored in the output_file_path you defined.

Perception Planning Mode

  • Download the rosbag files from the Google Drive link here.
  • Extract the zip file and set the path of the .db3 files to parameters path_bag_without_object and path_bag_with_object.
  • You can start to test with the following command:
ros2 launch reaction_analyzer reaction_analyzer.launch.xml running_mode:=perception_planning vehicle_model:=sample_vehicle sensor_model:=awsim_labs_sensor_kit map_path:=[MAP_PATH]

  • On the first run of the tool in perception_planning mode, initialization might take longer than expected. Please allow some time for the process to complete.

After the command, the e2e_simulator and the reaction_analyzer will be launched. It will automatically start to test. After the test is completed, the results will be stored in the output_file_path you defined.

Prepared Test Environment

Scene without object:

File truncated at 100 lines see the full file

CHANGELOG

Changelog for package reaction_analyzer

0.47.0 (2025-08-11)

  • feat: change planning output topic name to /planning/trajectory (#11135)

    • change planning output topic name to /planning/trajectory

    * style(pre-commit): autofix ---------Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

  • 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>

  • style(pre-commit): autofix (#10982) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

  • Contributors: Mete Fatih Cırıt, Ryohsuke Mitsudome, Yukihiro Saito

0.46.0 (2025-06-20)

0.45.0 (2025-05-22)

0.44.2 (2025-06-10)

0.44.1 (2025-05-01)

0.44.0 (2025-04-18)

  • Merge remote-tracking branch 'origin/main' into humble

  • fix: add missing exec_depend (#10404)

    • fix missing exec depend
    • remove fixed depend

    * remove the removed dependency ---------

  • Contributors: Ryohsuke Mitsudome, Takagi, Isamu

0.43.0 (2025-03-21)

  • Merge remote-tracking branch 'origin/main' into chore/bump-version-0.43
  • chore: rename from [autoware.universe]{.title-ref} to [autoware_universe]{.title-ref} (#10306)
  • Contributors: Hayato Mizushima, Yutaka Kondo

0.42.0 (2025-03-03)

  • Merge remote-tracking branch 'origin/main' into tmp/bot/bump_version_base
  • feat(autoware_utils): replace autoware_universe_utils with autoware_utils (#10191)
  • fix: add missing includes to autoware_universe_utils (#10091)
  • Contributors: Fumiya Watanabe, Ryohsuke Mitsudome, 心刚

0.41.2 (2025-02-19)

  • chore: bump version to 0.41.1 (#10088)
  • Contributors: Ryohsuke Mitsudome

0.41.1 (2025-02-10)

0.41.0 (2025-01-29)

0.40.0 (2024-12-12)

  • Merge branch 'main' into release-0.40.0

  • Revert "chore(package.xml): bump version to 0.39.0 (#9587)" This reverts commit c9f0f2688c57b0f657f5c1f28f036a970682e7f5.

  • fix: fix ticket links in CHANGELOG.rst (#9588)

  • chore(package.xml): bump version to 0.39.0 (#9587)

    • chore(package.xml): bump version to 0.39.0
    • fix: fix ticket links in CHANGELOG.rst

    * fix: remove unnecessary diff ---------Co-authored-by: Yutaka Kondo <<yutaka.kondo@youtalk.jp>>

  • fix: fix ticket links in CHANGELOG.rst (#9588)

File truncated at 100 lines see the full file

Launch files

  • launch/reaction_analyzer.launch.xml
      • reaction_analyzer_param_path [default: $(find-pkg-share reaction_analyzer)/param/reaction_analyzer.param.yaml]
      • launch_simulator_perception_modules [default: false]
      • laserscan_based_occupancy_grid_map_param_path [default: $(find-pkg-share autoware_launch)/config/perception/occupancy_grid_map/laserscan_based_occupancy_grid_map.param.yaml]
      • occupancy_grid_map_updater [default: binary_bayes_filter]
      • occupancy_grid_map_updater_param_path [default: $(find-pkg-share autoware_launch)/config/perception/occupancy_grid_map/$(var occupancy_grid_map_updater)_updater.param.yaml]
      • running_mode [default: planning_control]
      • map_path
      • vehicle_model [default: sample_vehicle]
      • sensor_model [default: sample_sensor_kit]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

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Package symbol

reaction_analyzer 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

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

Analyzer that measures reaction times of the nodes

Additional Links

No additional links.

Maintainers

  • Berkay Karaman

Authors

  • Berkay Karaman

Reaction Analyzer

Description

The main purpose of the reaction analyzer package is to measure the reaction times of various nodes within a ROS-based autonomous driving simulation environment by subscribing to pre-determined topics. This tool is particularly useful for evaluating the performance of perception, planning, and control pipelines in response to dynamic changes in the environment, such as sudden obstacles. To be able to measure both control outputs and perception outputs, it was necessary to divide the node into two running_mode: planning_control and perception_planning.

ReactionAnalyzerDesign.png

Planning Control Mode

In this mode, the reaction analyzer creates a dummy publisher for the PredictedObjects and PointCloud2 topics. In the beginning of the test, it publishes the initial position of the ego vehicle and the goal position to set the test environment. Then, it spawns a sudden obstacle in front of the ego vehicle. After the obstacle is spawned, it starts to search reacted messages of the planning and control nodes in the pre-determined topics. When all the topics are reacted, it calculates the reaction time of the nodes and statistics by comparing reacted_times of each of the nodes with spawn_cmd_time, and it creates a csv file to store the results.

Perception Planning Mode

In this mode, the reaction analyzer reads the rosbag files which are recorded from AWSIM, and it creates a topic publisher for each topic inside the rosbag to replay the rosbag. It reads two rosbag files: path_bag_without_object and path_bag_with_object. Firstly, it replays the path_bag_without_object to set the initial position of the ego vehicle and the goal position. After spawn_time_after_init seconds , it replays the path_bag_with_object to spawn a sudden obstacle in front of the ego vehicle. After the obstacle is spawned, it starts to search the reacted messages of the perception and planning nodes in the pre-determined topics. When all the topics are reacted, it calculates the reaction time of the nodes and statistics by comparing reacted_times of each of the nodes with spawn_cmd_time, and it creates a csv file to store the results.

Point Cloud Publisher Type

To get better analyze for Perception & Sensing pipeline, the reaction analyzer can publish the point cloud messages in 3 different ways: async_header_sync_publish, sync_header_sync_publish or async_publish. (T is the period of the lidar’s output)

PointcloudPublisherType.png

  • async_header_sync_publish: It publishes the point cloud messages synchronously with asynchronous header times. It means that each of the lidar’s output will be published at the same time, but the headers of the point cloud messages includes different timestamps because of the phase difference.
  • sync_header_sync_publish: It publishes the point cloud messages synchronously with synchronous header times. It means that each of the lidar’s output will be published at the same time, and the headers of the point cloud messages includes the same timestamps.
  • async_publish: It publishes the point cloud messages asynchronously. It means that each of the lidar’s output will be published at different times.

Usage

The common parameters you need to define for both running modes are output_file_path, test_iteration, and reaction_chain list. output_file_path is the output file path is the path where the results and statistics will be stored. test_iteration defines how many tests will be performed. The reaction_chain list is the list of the pre-defined topics you want to measure their reaction times.

IMPORTANT: Ensure the reaction_chain list is correctly defined:

  • For perception_planning mode, do not define Control nodes.
  • For planning_control mode, do not define Perception nodes.

Prepared Test Environment

  • Download the demonstration test map from the link here. After downloading, extract the zip file and use its path as [MAP_PATH] in the following commands.

Planning Control Mode

  • You need to define only Planning and Control nodes in the reaction_chain list. With the default parameters, you can start to test with the following command:
ros2 launch reaction_analyzer reaction_analyzer.launch.xml running_mode:=planning_control vehicle_model:=sample_vehicle sensor_model:=sample_sensor_kit map_path:=[MAP_PATH]

After the command, the simple_planning_simulator and the reaction_analyzer will be launched. It will automatically start to test. After the test is completed, the results will be stored in the output_file_path you defined.

Perception Planning Mode

  • Download the rosbag files from the Google Drive link here.
  • Extract the zip file and set the path of the .db3 files to parameters path_bag_without_object and path_bag_with_object.
  • You can start to test with the following command:
ros2 launch reaction_analyzer reaction_analyzer.launch.xml running_mode:=perception_planning vehicle_model:=sample_vehicle sensor_model:=awsim_labs_sensor_kit map_path:=[MAP_PATH]

  • On the first run of the tool in perception_planning mode, initialization might take longer than expected. Please allow some time for the process to complete.

After the command, the e2e_simulator and the reaction_analyzer will be launched. It will automatically start to test. After the test is completed, the results will be stored in the output_file_path you defined.

Prepared Test Environment

Scene without object:

File truncated at 100 lines see the full file

CHANGELOG

Changelog for package reaction_analyzer

0.47.0 (2025-08-11)

  • feat: change planning output topic name to /planning/trajectory (#11135)

    • change planning output topic name to /planning/trajectory

    * style(pre-commit): autofix ---------Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

  • 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>

  • style(pre-commit): autofix (#10982) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

  • Contributors: Mete Fatih Cırıt, Ryohsuke Mitsudome, Yukihiro Saito

0.46.0 (2025-06-20)

0.45.0 (2025-05-22)

0.44.2 (2025-06-10)

0.44.1 (2025-05-01)

0.44.0 (2025-04-18)

  • Merge remote-tracking branch 'origin/main' into humble

  • fix: add missing exec_depend (#10404)

    • fix missing exec depend
    • remove fixed depend

    * remove the removed dependency ---------

  • Contributors: Ryohsuke Mitsudome, Takagi, Isamu

0.43.0 (2025-03-21)

  • Merge remote-tracking branch 'origin/main' into chore/bump-version-0.43
  • chore: rename from [autoware.universe]{.title-ref} to [autoware_universe]{.title-ref} (#10306)
  • Contributors: Hayato Mizushima, Yutaka Kondo

0.42.0 (2025-03-03)

  • Merge remote-tracking branch 'origin/main' into tmp/bot/bump_version_base
  • feat(autoware_utils): replace autoware_universe_utils with autoware_utils (#10191)
  • fix: add missing includes to autoware_universe_utils (#10091)
  • Contributors: Fumiya Watanabe, Ryohsuke Mitsudome, 心刚

0.41.2 (2025-02-19)

  • chore: bump version to 0.41.1 (#10088)
  • Contributors: Ryohsuke Mitsudome

0.41.1 (2025-02-10)

0.41.0 (2025-01-29)

0.40.0 (2024-12-12)

  • Merge branch 'main' into release-0.40.0

  • Revert "chore(package.xml): bump version to 0.39.0 (#9587)" This reverts commit c9f0f2688c57b0f657f5c1f28f036a970682e7f5.

  • fix: fix ticket links in CHANGELOG.rst (#9588)

  • chore(package.xml): bump version to 0.39.0 (#9587)

    • chore(package.xml): bump version to 0.39.0
    • fix: fix ticket links in CHANGELOG.rst

    * fix: remove unnecessary diff ---------Co-authored-by: Yutaka Kondo <<yutaka.kondo@youtalk.jp>>

  • fix: fix ticket links in CHANGELOG.rst (#9588)

File truncated at 100 lines see the full file

Launch files

  • launch/reaction_analyzer.launch.xml
      • reaction_analyzer_param_path [default: $(find-pkg-share reaction_analyzer)/param/reaction_analyzer.param.yaml]
      • launch_simulator_perception_modules [default: false]
      • laserscan_based_occupancy_grid_map_param_path [default: $(find-pkg-share autoware_launch)/config/perception/occupancy_grid_map/laserscan_based_occupancy_grid_map.param.yaml]
      • occupancy_grid_map_updater [default: binary_bayes_filter]
      • occupancy_grid_map_updater_param_path [default: $(find-pkg-share autoware_launch)/config/perception/occupancy_grid_map/$(var occupancy_grid_map_updater)_updater.param.yaml]
      • running_mode [default: planning_control]
      • map_path
      • vehicle_model [default: sample_vehicle]
      • sensor_model [default: sample_sensor_kit]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged reaction_analyzer at Robotics Stack Exchange

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reaction_analyzer 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

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

Analyzer that measures reaction times of the nodes

Additional Links

No additional links.

Maintainers

  • Berkay Karaman

Authors

  • Berkay Karaman

Reaction Analyzer

Description

The main purpose of the reaction analyzer package is to measure the reaction times of various nodes within a ROS-based autonomous driving simulation environment by subscribing to pre-determined topics. This tool is particularly useful for evaluating the performance of perception, planning, and control pipelines in response to dynamic changes in the environment, such as sudden obstacles. To be able to measure both control outputs and perception outputs, it was necessary to divide the node into two running_mode: planning_control and perception_planning.

ReactionAnalyzerDesign.png

Planning Control Mode

In this mode, the reaction analyzer creates a dummy publisher for the PredictedObjects and PointCloud2 topics. In the beginning of the test, it publishes the initial position of the ego vehicle and the goal position to set the test environment. Then, it spawns a sudden obstacle in front of the ego vehicle. After the obstacle is spawned, it starts to search reacted messages of the planning and control nodes in the pre-determined topics. When all the topics are reacted, it calculates the reaction time of the nodes and statistics by comparing reacted_times of each of the nodes with spawn_cmd_time, and it creates a csv file to store the results.

Perception Planning Mode

In this mode, the reaction analyzer reads the rosbag files which are recorded from AWSIM, and it creates a topic publisher for each topic inside the rosbag to replay the rosbag. It reads two rosbag files: path_bag_without_object and path_bag_with_object. Firstly, it replays the path_bag_without_object to set the initial position of the ego vehicle and the goal position. After spawn_time_after_init seconds , it replays the path_bag_with_object to spawn a sudden obstacle in front of the ego vehicle. After the obstacle is spawned, it starts to search the reacted messages of the perception and planning nodes in the pre-determined topics. When all the topics are reacted, it calculates the reaction time of the nodes and statistics by comparing reacted_times of each of the nodes with spawn_cmd_time, and it creates a csv file to store the results.

Point Cloud Publisher Type

To get better analyze for Perception & Sensing pipeline, the reaction analyzer can publish the point cloud messages in 3 different ways: async_header_sync_publish, sync_header_sync_publish or async_publish. (T is the period of the lidar’s output)

PointcloudPublisherType.png

  • async_header_sync_publish: It publishes the point cloud messages synchronously with asynchronous header times. It means that each of the lidar’s output will be published at the same time, but the headers of the point cloud messages includes different timestamps because of the phase difference.
  • sync_header_sync_publish: It publishes the point cloud messages synchronously with synchronous header times. It means that each of the lidar’s output will be published at the same time, and the headers of the point cloud messages includes the same timestamps.
  • async_publish: It publishes the point cloud messages asynchronously. It means that each of the lidar’s output will be published at different times.

Usage

The common parameters you need to define for both running modes are output_file_path, test_iteration, and reaction_chain list. output_file_path is the output file path is the path where the results and statistics will be stored. test_iteration defines how many tests will be performed. The reaction_chain list is the list of the pre-defined topics you want to measure their reaction times.

IMPORTANT: Ensure the reaction_chain list is correctly defined:

  • For perception_planning mode, do not define Control nodes.
  • For planning_control mode, do not define Perception nodes.

Prepared Test Environment

  • Download the demonstration test map from the link here. After downloading, extract the zip file and use its path as [MAP_PATH] in the following commands.

Planning Control Mode

  • You need to define only Planning and Control nodes in the reaction_chain list. With the default parameters, you can start to test with the following command:
ros2 launch reaction_analyzer reaction_analyzer.launch.xml running_mode:=planning_control vehicle_model:=sample_vehicle sensor_model:=sample_sensor_kit map_path:=[MAP_PATH]

After the command, the simple_planning_simulator and the reaction_analyzer will be launched. It will automatically start to test. After the test is completed, the results will be stored in the output_file_path you defined.

Perception Planning Mode

  • Download the rosbag files from the Google Drive link here.
  • Extract the zip file and set the path of the .db3 files to parameters path_bag_without_object and path_bag_with_object.
  • You can start to test with the following command:
ros2 launch reaction_analyzer reaction_analyzer.launch.xml running_mode:=perception_planning vehicle_model:=sample_vehicle sensor_model:=awsim_labs_sensor_kit map_path:=[MAP_PATH]

  • On the first run of the tool in perception_planning mode, initialization might take longer than expected. Please allow some time for the process to complete.

After the command, the e2e_simulator and the reaction_analyzer will be launched. It will automatically start to test. After the test is completed, the results will be stored in the output_file_path you defined.

Prepared Test Environment

Scene without object:

File truncated at 100 lines see the full file

CHANGELOG

Changelog for package reaction_analyzer

0.47.0 (2025-08-11)

  • feat: change planning output topic name to /planning/trajectory (#11135)

    • change planning output topic name to /planning/trajectory

    * style(pre-commit): autofix ---------Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

  • 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>

  • style(pre-commit): autofix (#10982) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

  • Contributors: Mete Fatih Cırıt, Ryohsuke Mitsudome, Yukihiro Saito

0.46.0 (2025-06-20)

0.45.0 (2025-05-22)

0.44.2 (2025-06-10)

0.44.1 (2025-05-01)

0.44.0 (2025-04-18)

  • Merge remote-tracking branch 'origin/main' into humble

  • fix: add missing exec_depend (#10404)

    • fix missing exec depend
    • remove fixed depend

    * remove the removed dependency ---------

  • Contributors: Ryohsuke Mitsudome, Takagi, Isamu

0.43.0 (2025-03-21)

  • Merge remote-tracking branch 'origin/main' into chore/bump-version-0.43
  • chore: rename from [autoware.universe]{.title-ref} to [autoware_universe]{.title-ref} (#10306)
  • Contributors: Hayato Mizushima, Yutaka Kondo

0.42.0 (2025-03-03)

  • Merge remote-tracking branch 'origin/main' into tmp/bot/bump_version_base
  • feat(autoware_utils): replace autoware_universe_utils with autoware_utils (#10191)
  • fix: add missing includes to autoware_universe_utils (#10091)
  • Contributors: Fumiya Watanabe, Ryohsuke Mitsudome, 心刚

0.41.2 (2025-02-19)

  • chore: bump version to 0.41.1 (#10088)
  • Contributors: Ryohsuke Mitsudome

0.41.1 (2025-02-10)

0.41.0 (2025-01-29)

0.40.0 (2024-12-12)

  • Merge branch 'main' into release-0.40.0

  • Revert "chore(package.xml): bump version to 0.39.0 (#9587)" This reverts commit c9f0f2688c57b0f657f5c1f28f036a970682e7f5.

  • fix: fix ticket links in CHANGELOG.rst (#9588)

  • chore(package.xml): bump version to 0.39.0 (#9587)

    • chore(package.xml): bump version to 0.39.0
    • fix: fix ticket links in CHANGELOG.rst

    * fix: remove unnecessary diff ---------Co-authored-by: Yutaka Kondo <<yutaka.kondo@youtalk.jp>>

  • fix: fix ticket links in CHANGELOG.rst (#9588)

File truncated at 100 lines see the full file

Launch files

  • launch/reaction_analyzer.launch.xml
      • reaction_analyzer_param_path [default: $(find-pkg-share reaction_analyzer)/param/reaction_analyzer.param.yaml]
      • launch_simulator_perception_modules [default: false]
      • laserscan_based_occupancy_grid_map_param_path [default: $(find-pkg-share autoware_launch)/config/perception/occupancy_grid_map/laserscan_based_occupancy_grid_map.param.yaml]
      • occupancy_grid_map_updater [default: binary_bayes_filter]
      • occupancy_grid_map_updater_param_path [default: $(find-pkg-share autoware_launch)/config/perception/occupancy_grid_map/$(var occupancy_grid_map_updater)_updater.param.yaml]
      • running_mode [default: planning_control]
      • map_path
      • vehicle_model [default: sample_vehicle]
      • sensor_model [default: sample_sensor_kit]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged reaction_analyzer at Robotics Stack Exchange