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obstacle_velocity_limiter package from autodrrt repo

autonomous_emergency_braking control_performance_analysis control_validator external_cmd_selector joy_controller lane_departure_checker mpc_lateral_controller obstacle_collision_checker operation_mode_transition_manager pid_longitudinal_controller predicted_path_checker pure_pursuit shift_decider trajectory_follower_base trajectory_follower_node vehicle_cmd_gate diagnostic_converter kinematic_evaluator localization_evaluator planning_evaluator ekf_localizer geo_pose_projector gyro_odometer ar_tag_based_localizer landmark_manager localization_error_monitor localization_util ndt_scan_matcher pose2twist pose_initializer pose_instability_detector stop_filter tree_structured_parzen_estimator twist2accel yabloc_common yabloc_image_processing yabloc_monitor yabloc_particle_filter yabloc_pose_initializer map_height_fitter map_loader map_projection_loader map_tf_generator lanelet2_map_preprocessor ros2_bevdet ros2_bevformer bevfusion bytetrack cluster_merger compare_map_segmentation crosswalk_traffic_light_estimator detected_object_feature_remover detected_object_validation detection_by_tracker elevation_map_loader euclidean_cluster front_vehicle_velocity_estimator ground_segmentation heatmap_visualizer image_projection_based_fusion lidar_apollo_instance_segmentation lidar_apollo_segmentation_tvm lidar_apollo_segmentation_tvm_nodes lidar_centerpoint lidar_centerpoint_tvm map_based_prediction multi_object_tracker object_merger object_range_splitter object_velocity_splitter occupancy_grid_map_outlier_filter probabilistic_occupancy_grid_map radar_crossing_objects_noise_filter radar_fusion_to_detected_object radar_object_clustering radar_object_tracker radar_tracks_msgs_converter shape_estimation simple_object_merger tensorrt_classifier tensorrt_yolo tensorrt_yolox tracking_object_merger traffic_light_arbiter traffic_light_classifier traffic_light_fine_detector traffic_light_map_based_detector traffic_light_multi_camera_fusion traffic_light_occlusion_predictor traffic_light_ssd_fine_detector traffic_light_visualization behavior_path_avoidance_by_lane_change_module behavior_path_avoidance_module behavior_path_external_request_lane_change_module behavior_path_goal_planner_module behavior_path_lane_change_module behavior_path_planner behavior_path_planner_common behavior_path_side_shift_module behavior_path_start_planner_module behavior_velocity_blind_spot_module behavior_velocity_crosswalk_module behavior_velocity_detection_area_module behavior_velocity_intersection_module behavior_velocity_no_drivable_lane_module behavior_velocity_no_stopping_area_module behavior_velocity_occlusion_spot_module behavior_velocity_out_of_lane_module behavior_velocity_planner behavior_velocity_planner_common behavior_velocity_run_out_module behavior_velocity_speed_bump_module behavior_velocity_stop_line_module behavior_velocity_template_module behavior_velocity_traffic_light_module behavior_velocity_virtual_traffic_light_module behavior_velocity_walkway_module costmap_generator external_velocity_limit_selector freespace_planner freespace_planning_algorithms mission_planner motion_velocity_smoother objects_of_interest_marker_interface obstacle_avoidance_planner obstacle_cruise_planner obstacle_stop_planner obstacle_velocity_limiter path_smoother planning_debug_tools planning_test_utils planning_topic_converter planning_validator route_handler rtc_interface rtc_replayer bezier_sampler frenet_planner path_sampler sampler_common scenario_selector static_centerline_optimizer surround_obstacle_checker gnss_poser image_diagnostics image_transport_decompressor imu_corrector livox_tag_filter pointcloud_preprocessor radar_scan_to_pointcloud2 radar_static_pointcloud_filter radar_threshold_filter radar_tracks_noise_filter tier4_pcl_extensions vehicle_velocity_converter autoware_auto_msgs_adapter bluetooth_monitor component_state_monitor default_ad_api ad_api_adaptors ad_api_visualizers automatic_pose_initializer diagnostic_graph_aggregator dummy_diag_publisher dummy_infrastructure duplicated_node_checker emergency_handler mrm_comfortable_stop_operator mrm_emergency_stop_operator system_error_monitor system_monitor topic_state_monitor velodyne_monitor accel_brake_map_calibrator external_cmd_converter raw_vehicle_cmd_converter steer_offset_estimator vehicle_info_util launch launch_ros autoware_ad_api_specs autoware_adapi_v1_msgs autoware_adapi_version_msgs autoware_auto_common autoware_auto_geometry autoware_auto_control_msgs autoware_auto_geometry_msgs autoware_auto_mapping_msgs autoware_auto_msgs autoware_auto_perception_msgs autoware_auto_planning_msgs autoware_auto_system_msgs autoware_auto_vehicle_msgs autoware_auto_perception_rviz_plugin autoware_auto_tf2 autoware_cmake autoware_lint_common autoware_utils lanelet2_extension autoware_common_msgs autoware_control_msgs autoware_localization_msgs autoware_map_msgs autoware_perception_msgs autoware_planning_msgs autoware_sensing_msgs autoware_system_msgs autoware_vehicle_msgs autoware_point_types autoware_testing bag_time_manager_rviz_plugin component_interface_specs component_interface_tools component_interface_utils cuda_utils fake_test_node geography_utils global_parameter_loader glog_component goal_distance_calculator grid_map_utils interpolation kalman_filter motion_utils object_recognition_utils osqp_interface path_distance_calculator perception_utils polar_grid qp_interface rtc_manager_rviz_plugin signal_processing tensorrt_common tier4_adapi_rviz_plugin tier4_api_utils tier4_automatic_goal_rviz_plugin tier4_autoware_utils tier4_calibration_rviz_plugin tier4_camera_view_rviz_plugin tier4_control_rviz_plugin tier4_datetime_rviz_plugin tier4_debug_rviz_plugin tier4_debug_tools tier4_localization_rviz_plugin tier4_perception_rviz_plugin tier4_planning_rviz_plugin tier4_screen_capture_rviz_plugin tier4_simulated_clock_rviz_plugin tier4_state_rviz_plugin tier4_system_rviz_plugin tier4_target_object_type_rviz_plugin tier4_traffic_light_rviz_plugin tier4_vehicle_rviz_plugin time_utils simulator_compatibility_test traffic_light_recognition_marker_publisher traffic_light_utils tvm_utility dma_customer_msg dma_transfer eagleye_coordinate eagleye_navigation eagleye_msgs eagleye_rt eagleye_can_velocity_converter eagleye_fix2kml eagleye_geo_pose_converter eagleye_geo_pose_fusion eagleye_gnss_converter eagleye_tf llh_converter morai_msgs mussp ndt_omp orocos_kdl python_orocos_kdl pointcloud_to_laserscan rtklib_bridge rtklib_msgs autoware_external_api_msgs autoware_iv_external_api_adaptor autoware_iv_internal_api_adaptor awapi_awiv_adapter tier4_api_msgs tier4_auto_msgs_converter tier4_control_msgs tier4_debug_msgs tier4_external_api_msgs tier4_hmi_msgs tier4_localization_msgs tier4_map_msgs tier4_perception_msgs tier4_planning_msgs tier4_rtc_msgs tier4_simulation_msgs tier4_system_msgs tier4_v2x_msgs tier4_vehicle_msgs io_opt 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 fastrtps cyclonedds lanelet2 lanelet2_core lanelet2_examples lanelet2_io lanelet2_maps lanelet2_matching lanelet2_projection lanelet2_python lanelet2_routing lanelet2_traffic_rules lanelet2_validation sophus angles behaviortree_cpp_v3 bond bond_core bondcpp bondpy smclib test_bond cudnn_cmake_module diagnostic_aggregator diagnostic_common_diagnostics diagnostic_updater diagnostics self_test filters geodesy geographic_info geographic_msgs grid_map grid_map_cmake_helpers grid_map_core grid_map_costmap_2d grid_map_cv grid_map_demos grid_map_filters grid_map_loader grid_map_msgs grid_map_octomap grid_map_pcl grid_map_ros grid_map_rviz_plugin grid_map_sdf grid_map_visualization mrt_cmake_modules nav2_amcl nav2_behavior_tree nav2_behaviors nav2_bringup nav2_bt_navigator nav2_collision_monitor nav2_common nav2_controller nav2_core nav2_costmap_2d costmap_queue dwb_core dwb_critics dwb_msgs dwb_plugins nav2_dwb_controller nav_2d_msgs nav_2d_utils nav2_lifecycle_manager nav2_map_server nav2_msgs nav2_navfn_planner nav2_planner nav2_regulated_pure_pursuit_controller nav2_rotation_shim_controller nav2_rviz_plugins nav2_simple_commander nav2_smac_planner nav2_smoother nav2_system_tests nav2_theta_star_planner nav2_util nav2_velocity_smoother nav2_voxel_grid nav2_waypoint_follower navigation2 dynamic_edt_3d octomap octovis octomap_msgs osqp_vendor pacmod3_msgs pcl_msgs pcl_conversions pcl_ros perception_pcl point_cloud_msg_wrapper radar_msgs can_msgs rqt_tf_tree tensorrt_cmake_module topic_tools topic_tools_interfaces tvm_vendor cv_bridge image_geometry opencv_tests vision_opencv xacro rviz2 rviz_assimp_vendor rviz_common rviz_default_plugins rviz_ogre_vendor rviz_rendering rviz_rendering_tests rviz_visual_testing_framework dummy_perception_publisher fault_injection simple_planning_simulator classformsg node_v2x image_view v4l2_camera can_interface_custom cgi430_can_driver cgi610_driver ARS408_driver data_format_dump data_preprocess_launch lidar_centerpoint_collect lidar_saver message_sync time_cal camera_calibration direct_visual_lidar_calibration multi_lidar_calibration

Package Summary

Tags No category tags.
Version 0.1.0
License Apache License 2.0
Build type AMENT_CMAKE
Use RECOMMENDED

Repository Summary

Checkout URI https://github.com/ieiauto/autodrrt.git
VCS Type git
VCS Version main
Last Updated 2024-09-19
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

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 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.

Inputs / Outputs

Inputs

Name Type Description
~/input/trajectory autoware_auto_planning_msgs/Trajectory Reference trajectory
~/input/occupancy_grid nav_msgs/OccupancyGrid Occupancy grid with obstacle information
~/input/obstacle_pointcloud sensor_msgs/PointCloud2 Pointcloud containing only obstacle points
~/input/dynamic_obstacles autoware_auto_perception_msgs/PredictedObjects Dynamic objects
~/input/odometry nav_msgs/Odometry Odometry used to retrieve the current ego velocity
~/input/map autoware_auto_mapping_msgs/HADMapBin Vector map used to retrieve static obstacles

Outputs

Name Type Description
~/output/trajectory autoware_auto_planning_msgs/Trajectory Trajectory with adjusted velocities
~/output/debug_markers visualization_msgs/MarkerArray Debug markers (envelopes, obstacle polygons)
~/output/runtime_microseconds tier4_debug_msgs/Float64 Time taken to calculate the trajectory (in microseconds)

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
No CHANGELOG found.

Wiki Tutorials

This package does not provide any links to tutorials in it's rosindex metadata. You can check on the ROS Wiki Tutorials page for the package.

Launch files

  • launch/obstacle_velocity_limiter.launch.xml
      • input_trajectory [default: /planning/scenario_planning/scenario_selector/trajectory]
      • input_dynamic_obstacles [default: /perception/object_recognition/objects]
      • input_occupancy_grid [default: /perception/occupancy_grid_map/map]
      • input_obstacle_pointcloud [default: /perception/obstacle_segmentation/pointcloud]
      • input_odometry [default: /localization/kinematic_state]
      • input_map [default: /map/vector_map]
      • output_trajectory [default: ~/output/trajectory]
      • output_debug_markers [default: ~/output/debug_markers]
      • param_path [default: $(find-pkg-share obstacle_velocity_limiter)/config/default_obstacle_velocity_limiter.param.yaml]
      • vehicle_info_param_file [default: $(find-pkg-share vehicle_info_util)/config/vehicle_info.param.yaml]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

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