Merge branch 'main' into fix/lane_change_params

autoware_launch/config/localization/ndt_scan_matcher.param.yaml

@@ -1,8 +1,5 @@
 /**:
   ros__parameters:
-    # Use dynamic map loading
-    use_dynamic_map_loading: true
-
     # Vehicle reference frame
     base_frame: "base_link"
 

autoware_launch/config/map/pointcloud_map_loader.param.yaml

@@ -3,7 +3,6 @@
     enable_whole_load: true
     enable_downsampled_whole_load: false
     enable_partial_load: true
-    enable_differential_load: true
     enable_selected_load: false
 
     # only used when downsample_whole_load enabled

autoware_launch/config/perception/object_recognition/prediction/map_based_prediction.param.yaml

@@ -13,6 +13,9 @@
     sigma_yaw_angle_deg: 5.0 #[angle degree]
     object_buffer_time_length: 2.0 #[s]
     history_time_length: 1.0 #[s]
+    check_lateral_acceleration_constraints: false # whether to check if the predicted path complies with lateral acceleration constraints
+    max_lateral_accel: 2.0 # [m/ss] max acceptable lateral acceleration for predicted vehicle paths
+    min_acceleration_before_curve: -2.0 # [m/ss] min acceleration a vehicle might take to decelerate before a curve
     # parameter for shoulder lane prediction
     prediction_time_horizon_rate_for_validate_shoulder_lane_length: 0.8
 

autoware_launch/config/planning/scenario_planning/lane_driving/behavior_planning/behavior_path_planner/dynamic_avoidance/dynamic_avoidance.param.yaml

@@ -38,7 +38,7 @@
         crossing_object:
           min_overtaking_object_vel: 1.0
           max_overtaking_object_angle: 1.05
-          min_oncoming_object_vel: 0.0
+          min_oncoming_object_vel: 1.0
           max_oncoming_object_angle: 0.523
 
         front_object:
@@ -54,20 +54,24 @@
         object_path_base:
           min_longitudinal_polygon_margin: 3.0 # [m]
 
-        lat_offset_from_obstacle: 0.8 # [m]
+        lat_offset_from_obstacle: 1.0 # [m]
         max_lat_offset_to_avoid: 0.5 # [m]
         max_time_for_object_lat_shift: 0.0 # [s]
         lpf_gain_for_lat_avoid_to_offset: 0.9 # [-]
 
+        max_ego_lat_acc: 0.3        # [m/ss]
+        max_ego_lat_jerk: 0.3       # [m/sss]
+        delay_time_ego_shift: 1.0   # [s]
+
         # for same directional object
         overtaking_object:
           max_time_to_collision: 40.0 # [s]
-          start_duration_to_avoid: 2.0  # [s]
-          end_duration_to_avoid: 4.0  # [s]
+          start_duration_to_avoid: 1.0  # [s]
+          end_duration_to_avoid: 1.0  # [s]
           duration_to_hold_avoidance: 3.0 # [s]
 
         # for opposite directional object
         oncoming_object:
           max_time_to_collision: 40.0 # [s] This value should be the same as overtaking_object's one to suppress chattering of this value for parked vehicles
-          start_duration_to_avoid: 12.0  # [s]
+          start_duration_to_avoid: 1.0  # [s]
           end_duration_to_avoid: 0.0  # [s]

autoware_launch/config/planning/scenario_planning/lane_driving/behavior_planning/behavior_velocity_planner/behavior_velocity_planner.param.yaml

@@ -2,6 +2,7 @@
   ros__parameters:
     forward_path_length: 1000.0
     backward_path_length: 5.0
+    behavior_output_path_interval: 1.0
     stop_line_extend_length: 5.0
     max_accel: -2.8
     max_jerk: -5.0

autoware_launch/config/planning/scenario_planning/lane_driving/behavior_planning/behavior_velocity_planner/crosswalk.param.yaml

@@ -53,8 +53,8 @@
         stop_object_velocity_threshold: 0.28 # [m/s] velocity threshold for the module to judge whether the objects is stopped (0.28 m/s = 1.0 kmph)
         min_object_velocity: 1.39 # [m/s] minimum object velocity (compare the estimated velocity by perception module with this parameter and adopt the larger one to calculate TTV. 1.39 m/s = 5.0 kmph)
         ## param for yielding
-        disable_stop_for_yield_cancel: false # for the crosswalks with traffic signal
-        disable_yield_for_new_stopped_object: false # for the crosswalks with traffic signal
+        disable_stop_for_yield_cancel: true # for the crosswalks with traffic signal
+        disable_yield_for_new_stopped_object: true # for the crosswalks with traffic signal
         # If the pedestrian does not move for X seconds after the ego has stopped in front the crosswalk, the module judge that the pedestrian has no intention to walk and allows the ego to proceed.
         distance_map_for_no_intention_to_walk: [1.0, 5.0] # [m] ascending order
         timeout_map_for_no_intention_to_walk: [3.0, 0.0] # [s]

autoware_launch/config/planning/scenario_planning/lane_driving/motion_planning/obstacle_stop_planner/obstacle_stop_planner.param.yaml

@@ -17,7 +17,7 @@
       # params for stop position
       stop_position:
         max_longitudinal_margin: 5.0             # stop margin distance from obstacle on the path [m]
-        max_longitudinal_margin_behind_goal: 3.0 # stop margin distance from obstacle behind goal on the path [m]
+        max_longitudinal_margin_behind_goal: 2.5 # stop margin distance from obstacle behind goal on the path [m]
         min_longitudinal_margin: 5.0             # stop margin distance when any other stop point is inserted in stop margin [m]
         hold_stop_margin_distance: 0.0           # the ego keeps stopping if the ego is in this margin [m]
 

autoware_launch/launch/components/tier4_perception_component.launch.xml

@@ -127,8 +127,9 @@
     <!-- traffic light recognition -->
     <arg name="traffic_light_arbiter_param_path" value="$(find-pkg-share autoware_launch)/config/perception/traffic_light_arbiter/traffic_light_arbiter.param.yaml"/>
     <arg name="traffic_light_fine_detector_model_path" value="$(var data_path)/traffic_light_fine_detector"/>
-    <arg name="traffic_light_fine_detector_model_name" value="tlr_yolox_s_batch_6"/>
+    <arg name="traffic_light_fine_detector_model_name" value="tlr_car_ped_yolox_s_batch_6"/>
     <arg name="traffic_light_classifier_model_path" value="$(var data_path)/traffic_light_classifier"/>
-    <arg name="traffic_light_classifier_model_name" value="traffic_light_classifier_mobilenetv2_batch_6"/>
+    <arg name="car_traffic_light_classifier_model_name" value="traffic_light_classifier_mobilenetv2_batch_6"/>
+    <arg name="pedestrian_traffic_light_classifier_model_name" value="ped_traffic_light_classifier_mobilenetv2_batch_4"/>
   </include>
 </launch>