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autoware_motion_velocity_obstacle_velocity_limiter_module package from autoware_universe repo

autoware_adapi_specs autoware_agnocast_wrapper autoware_auto_common 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_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_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 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_gyro_odometer autoware_ar_tag_based_localizer autoware_landmark_manager autoware_lidar_marker_localizer autoware_localization_error_monitor autoware_ndt_scan_matcher autoware_pose2twist autoware_pose_covariance_modifier autoware_pose_estimator_arbiter autoware_pose_initializer autoware_pose_instability_detector yabloc_common yabloc_image_processing yabloc_monitor yabloc_particle_filter yabloc_pose_initializer autoware_lanelet2_map_visualizer autoware_map_height_fitter autoware_map_tf_generator 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_velocity_splitter autoware_occupancy_grid_map_outlier_filter autoware_probabilistic_occupancy_grid_map autoware_radar_crossing_objects_noise_filter autoware_radar_fusion_to_detected_object autoware_radar_object_clustering autoware_radar_object_tracker autoware_radar_tracks_msgs_converter autoware_raindrop_cluster_filter autoware_shape_estimation 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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_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_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_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 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autoware_mission_details_overlay_rviz_plugin autoware_overlay_rviz_plugin autoware_string_stamped_rviz_plugin autoware_perception_rviz_plugin tier4_adapi_rviz_plugin tier4_camera_view_rviz_plugin tier4_datetime_rviz_plugin tier4_localization_rviz_plugin tier4_planning_factor_rviz_plugin tier4_planning_rviz_plugin tier4_state_rviz_plugin tier4_system_rviz_plugin tier4_traffic_light_rviz_plugin tier4_vehicle_rviz_plugin

Package Summary

Tags No category tags.
Version 0.43.0
License Apache License 2.0
Build type AMENT_CMAKE
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/autowarefoundation/autoware_universe.git
VCS Type git
VCS Version main
Last Updated 2025-04-03
Dev Status UNMAINTAINED
CI status No Continuous Integration
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Package Description

Package to adjust velocities of a trajectory in order for the ride to feel safe

Additional Links

No additional links.

Maintainers

  • Maxime CLEMENT
  • Alqudah Mohammad

Authors

No additional authors.

Obstacle Velocity Limiter

Purpose

This node limits the velocity when driving in the direction of an obstacle. For example, it allows to reduce the velocity when driving close to a guard rail in a curve.

Without this node With this node
obstacle_velocity_limiter_off obstacle_velocity_limiter_on

Inner-workings / Algorithms

Using a parameter min_ttc (minimum time to collision), the node set velocity limits such that no collision with an obstacle would occur, even without new control inputs for a duration of min_ttc.

To achieve this, the motion of the ego vehicle is simulated forward in time at each point of the trajectory to create a corresponding footprint. If the footprint collides with some obstacle, the velocity at the trajectory point is reduced such that the new simulated footprint do not have any collision.

Simulated Motion, Footprint, and Collision Distance

The motion of the ego vehicle is simulated at each trajectory point using the heading, velocity, and steering defined at the point. Footprints are then constructed from these simulations and checked for collision. If a collision is found, the distance from the trajectory point is used to calculate the adjusted velocity that would produce a collision-free footprint. Parameter simulation.distance_method allow to switch between an exact distance calculation and a less expensive approximation using a simple euclidean distance.

Two models can be selected with parameter simulation.model for simulating the motion of the vehicle: a simple particle model and a more complicated bicycle model.

Particle Model

The particle model uses the constant heading and velocity of the vehicle at a trajectory point to simulate the future motion. The simulated forward motion corresponds to a straight line and the footprint to a rectangle.

Footprint

The rectangle footprint is built from 2 lines parallel to the simulated forward motion and at a distance of half the vehicle width.

particle_footprint_image

Distance

When a collision point is found within the footprint, the distance is calculated as described in the following figure.

particle_collision_distance_image

Bicycle Model

The bicycle model uses the constant heading, velocity, and steering of the vehicle at a trajectory point to simulate the future motion. The simulated forward motion corresponds to an arc around the circle of curvature associated with the steering. Uncertainty in the steering can be introduced with the simulation.steering_offset parameter which will generate a range of motion from a left-most to a right-most steering. This results in 3 curved lines starting from the same trajectory point. A parameter simulation.nb_points is used to adjust the precision of these lines, with a minimum of 2 resulting in straight lines and higher values increasing the precision of the curves.

By default, the steering values contained in the trajectory message are used. Parameter trajectory_preprocessing.calculate_steering_angles allows to recalculate these values when set to true.

Footprint

The footprint of the bicycle model is created from lines parallel to the left and right simulated motion at a distance of half the vehicle width. In addition, the two points on the left and right of the end point of the central simulated motion are used to complete the polygon.

bicycle_footprint_image

Distance

The distance to a collision point is calculated by finding the curvature circle passing through the trajectory point and the collision point.

bicycle_collision_distance_image

Obstacle Detection

Obstacles are represented as points or linestrings (i.e., sequence of points) around the obstacles and are constructed from an occupancy grid, a pointcloud, or the lanelet map. The lanelet map is always checked for obstacles but the other source is switched using parameter obstacles.dynamic_source.

To efficiently find obstacles intersecting with a footprint, they are stored in a R-tree. Two trees are used, one for the obstacle points, and one for the obstacle linestrings (which are decomposed into segments to simplify the R-tree).

Obstacle masks

Dynamic obstacles

Moving obstacles such as other cars should not be considered by this module. These obstacles are detected by the perception modules and represented as polygons. Obstacles inside these polygons are ignored.

Only dynamic obstacles with a velocity above parameter obstacles.dynamic_obstacles_min_vel are removed.

To deal with delays and precision errors, the polygons can be enlarged with parameter obstacles.dynamic_obstacles_buffer.

Obstacles outside of the safety envelope

Obstacles that are not inside any forward simulated footprint are ignored if parameter obstacles.filter_envelope is set to true. The safety envelope polygon is built from all the footprints and used as a positive mask on the occupancy grid or pointcloud.

This option can reduce the total number of obstacles which reduces the cost of collision detection. However, the cost of masking the envelope is usually too high to be interesting.

Obstacles on the ego path

If parameter obstacles.ignore_obstacles_on_path is set to true, a polygon mask is built from the trajectory and the vehicle dimension. Any obstacle in this polygon is ignored.

The size of the polygon can be increased using parameter obstacles.ignore_extra_distance which is added to the vehicle lateral offset.

This option is a bit expensive and should only be used in case of noisy dynamic obstacles where obstacles are wrongly detected on the ego path, causing unwanted velocity limits.

Lanelet Map

Information about static obstacles can be stored in the Lanelet map using the value of the type tag of linestrings. If any linestring has a type with one of the value from parameter obstacles.static_map_tags, then it will be used as an obstacle.

Obstacles from the lanelet map are not impacted by the masks.

Occupancy Grid

Masking is performed by iterating through the cells inside each polygon mask using the autoware::grid_map_utils::PolygonIterator function. A threshold is then applied to only keep cells with an occupancy value above parameter obstacles.occupancy_grid_threshold. Finally, the image is converted to an image and obstacle linestrings are extracted using the opencv function findContour.

Pointcloud

Masking is performed using the pcl::CropHull function. Points from the pointcloud are then directly used as obstacles.

Velocity Adjustment

If a collision is found, the velocity at the trajectory point is adjusted such that the resulting footprint would no longer collide with an obstacle: $velocity = \frac{dist_to_collision}{min_ttc}$

To prevent sudden deceleration of the ego vehicle, the parameter max_deceleration limits the deceleration relative to the current ego velocity. For a trajectory point occurring at a duration t in the future (calculated from the original velocity profile), the adjusted velocity cannot be set lower than $v_{current} - t * max_deceleration$.

Furthermore, a parameter min_adjusted_velocity provides a lower bound on the modified velocity.

Trajectory preprocessing

The node only modifies part of the input trajectory, starting from the current ego position. Parameter trajectory_preprocessing.start_distance is used to adjust how far ahead of the ego position the velocities will start being modified. Parameters trajectory_preprocessing.max_length and trajectory_preprocessing.max_duration are used to control how much of the trajectory will see its velocity adjusted.

To reduce computation cost at the cost of precision, the trajectory can be downsampled using parameter trajectory_preprocessing.downsample_factor. For example a value of 1 means all trajectory points will be evaluated while a value of 10 means only 1/10th of the points will be evaluated.

Parameters

Name Type Description
min_ttc float [s] required minimum time with no collision at each point of the trajectory assuming constant heading and velocity.
distance_buffer float [m] required distance buffer with the obstacles.
min_adjusted_velocity float [m/s] minimum adjusted velocity this node can set.
max_deceleration float [m/s²] maximum deceleration an adjusted velocity can cause.
trajectory_preprocessing.start_distance float [m] controls from which part of the trajectory (relative to the current ego pose) the velocity is adjusted.
trajectory_preprocessing.max_length float [m] controls the maximum length (starting from the start_distance) where the velocity is adjusted.
trajectory_preprocessing.max_distance float [s] controls the maximum duration (measured from the start_distance) where the velocity is adjusted.
trajectory_preprocessing.downsample_factor int trajectory downsampling factor to allow tradeoff between precision and performance.
trajectory_preprocessing.calculate_steering_angle bool if true, the steering angles of the trajectory message are not used but are recalculated.
simulation.model string model to use for forward simulation. Either “particle” or “bicycle”.
simulation.distance_method string method to use for calculating distance to collision. Either “exact” or “approximation”.
simulation.steering_offset float offset around the steering used by the bicycle model.
simulation.nb_points int number of points used to simulate motion with the bicycle model.
obstacles.dynamic_source string source of dynamic obstacle used for collision checking. Can be “occupancy_grid”, “point_cloud”, or “static_only” (no dynamic obstacle).
obstacles.occupancy_grid_threshold int value in the occupancy grid above which a cell is considered an obstacle.
obstacles.dynamic_obstacles_buffer float buffer around dynamic obstacles used when masking an obstacle in order to prevent noise.
obstacles.dynamic_obstacles_min_vel float velocity above which to mask a dynamic obstacle.
obstacles.static_map_tags string list linestring of the lanelet map with this tags are used as obstacles.
obstacles.filter_envelope bool wether to use the safety envelope to filter the dynamic obstacles source.

Assumptions / Known limits

The velocity profile produced by this node is not meant to be a realistic velocity profile and can contain sudden jumps of velocity with no regard for acceleration and jerk. This velocity profile is meant to be used as an upper bound on the actual velocity of the vehicle.

(Optional) Error detection and handling

The critical case for this node is when an obstacle is falsely detected very close to the trajectory such that the corresponding velocity suddenly becomes very low. This can cause a sudden brake and two mechanisms can be used to mitigate these errors.

Parameter min_adjusted_velocity allow to set a minimum to the adjusted velocity, preventing the node to slow down the vehicle too much. Parameter max_deceleration allow to set a maximum deceleration (relative to the current ego velocity) that the adjusted velocity would incur.

(Optional) Performance characterization

(Optional) Future extensions / Unimplemented parts

CHANGELOG

Changelog for package autoware_motion_velocity_obstacle_velocity_limiter_module

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)
  • feat(motion_velocity_planner): common implementation for motion_velocity_obstacle_<stop/slow_down/cruise>_module (#10035)
    • feat(motion_velocity_planner): prepare for motion_velocity_<stop/slow_down/cruise>_module

    * update launch ---------

  • Contributors: Fumiya Watanabe, Takayuki Murooka, 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)

  • Merge remote-tracking branch 'origin/main' into tmp/bot/bump_version_base
  • feat(motion_velocity_planner)!: add _universe suffix to autoware_motion_velocity_planner_common and autoware_motion_velocity_planner_node (#9942)
  • feat(planning_factor)!: remove velocity_factor, steering_factor and introduce planning_factor (#9927) Co-authored-by: Satoshi OTA <<44889564+satoshi-ota@users.noreply.github.com>> Co-authored-by: Ryohsuke Mitsudome <<43976834+mitsudome-r@users.noreply.github.com>> Co-authored-by: satoshi-ota <<satoshi.ota928@gmail.com>>
  • fix(autoware_motion_velocity_obstacle_velocity_limiter_module): remove cppcheck suppressions (#9843)
  • feat(motion_velocity_planner): introduce Object/Pointcloud structure in PlannerData (#9812)
    • feat: new object/pointcloud struct in motion velocity planner
    • update planner_data
    • modify modules

    * fix

  • fix(autoware_motion_velocity_obstacle_velocity_limiter_module): fix bugprone-exception-escape (#9779)
    • fix: bugprone-error
    • fix: cppcheck

    * fix: cpplint ---------

  • feat(motion_velocity_planner): remove unnecessary tier4_planning_msgs dependency (#9757)
    • feat(motion_velocity_planner): remove unnecessary tier4_planning_msgs dependency

    * fix

  • feat(motion_velocity_planner): use Float64Stamped in autoware_internal_debug_msgs (#9745)
  • Contributors: Fumiya Watanabe, Mamoru Sobue, Ryohsuke Mitsudome, Ryuta Kambe, Takayuki Murooka, kobayu858

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)
  • fix(cpplint): include what you use - planning (#9570)
  • 0.39.0
  • update changelog
  • fix: fix ticket links to point to https://github.com/autowarefoundation/autoware_universe (#9304)
  • fix: fix ticket links to point to https://github.com/autowarefoundation/autoware_universe (#9304)
  • chore(package.xml): bump version to 0.38.0 (#9266) (#9284)
    • unify package.xml version to 0.37.0
    • remove system_monitor/CHANGELOG.rst
    • add changelog

    * 0.38.0

  • Contributors: Esteve Fernandez, Fumiya Watanabe, M. Fatih Cırıt, Ryohsuke Mitsudome, Yutaka Kondo

0.39.0 (2024-11-25)

0.38.0 (2024-11-08)

  • unify package.xml version to 0.37.0
  • refactor(autoware_grid_map_utils): prefix folder structure with autoware/ (#9170)
  • fix(obstacle_velocity_limiter): more stable virtual wall (#8499)
  • feat(out_of_lane): redesign to improve accuracy and performance (#8453)
  • chore(obstacle_velocity_limiter): add Alqudah Mohammad as codeowner (#8516)
  • fix(autoware_motion_velocity_obstacle_velocity_limiter_module): fix functionStatic (#8483) fix:functionStatic
  • fix(autoware_motion_velocity_obstacle_velocity_limiter_module): fix unreadVariable (#8366)
    • fix:unreadVariable

    * fix:unreadVariable ---------

  • fix(autoware_motion_velocity_obstacle_velocity_limiter_module): fix uninitMemberVar (#8314) fix:funinitMemberVar
  • fix(autoware_motion_velocity_obstacle_velocity_limiter_module): fix funcArgNamesDifferent (#8025) fix:funcArgNamesDifferent
  • fix(autoware_motion_velocity_obstacle_velocity_limiter_module): fix shadowVariable (#7977)
    • fix:shadowVariable

    * fix:shadowVariable ---------

  • perf(motion_velocity_planner): resample trajectory after vel smoothing (#7732)
    • perf(dynamic_obstacle_stop): create rtree with packing algorithm

    * Revert "perf(out_of_lane): downsample the trajectory to improve performance (#7691)" This reverts commit 8444a9eb29b32f500be3724dd5662013b9b81060. * perf(motion_velocity_planner): resample trajectory after vel smoothing ---------

  • feat: add [autoware_]{.title-ref} prefix to [lanelet2_extension]{.title-ref} (#7640)
  • perf(out_of_lane): downsample the trajectory to improve performance (#7691)
  • feat(motion_velocity_planner, lane_departure_checker): add processing time Float64 publishers (#7683)
  • feat(motion_velocity_planner): publish processing times (#7633)
  • fix(autoware_motion_velocity_obstacle_velocity_limiter_module): fix unreadVariable warning (#7625)
  • refactor(universe_utils/motion_utils)!: add autoware namespace (#7594)
  • refactor(motion_utils)!: add autoware prefix and include dir (#7539) refactor(motion_utils): add autoware prefix and include dir
  • feat(autoware_universe_utils)!: rename from tier4_autoware_utils (#7538) Co-authored-by: kosuke55 <<kosuke.tnp@gmail.com>>
  • feat(motion_velocity_planner): rename include directories (#7523)
  • refactor(grid_map_utils): add autoware prefix and namespace (#7487)
  • feat(obstacle_velocity_limiter): move to motion_velocity_planner (#7439)
  • Contributors: Esteve Fernandez, Kosuke Takeuchi, Maxime CLEMENT, Ryuta Kambe, Takayuki Murooka, Yutaka Kondo, kobayu858

0.26.0 (2024-04-03)

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