docs(behavior_path_planner): clean up duplicated description (#3441)

* docs(behavior_path_planner): move detail documents

Signed-off-by: satoshi-ota <satoshi.ota928@gmail.com>

* docs(behavior_path_planner): clean up

Signed-off-by: satoshi-ota <satoshi.ota928@gmail.com>

---------

Signed-off-by: satoshi-ota <satoshi.ota928@gmail.com>

Author: satoshi-ota

planning/behavior_path_planner/README.md

@@ -20,7 +20,7 @@ This module executes avoidance over lanes, and the decision requires the lane st
 
 The following figure shows a simple explanation of the logic for avoidance path generation. First, target objects are picked up, and shift requests are generated for each object. These shift requests are generated by taking into account the lateral jerk required for avoidance (red lines). Then these requests are merged and the shift points are created on the reference path (blue line). Filtering operations are performed on the shift points such as removing unnecessary shift points (yellow line), and finally a smooth avoidance path is generated by combining Clothoid-like curve primitives (green line).
 
-![fig1](./image/avoidance/avoidance_design.fig1.drawio.svg)
+![fig1](../image/avoidance/avoidance_design.fig1.drawio.svg)
 
 ### Flowchart
 
@@ -185,7 +185,7 @@ The avoidance target should be limited to stationary objects (you should not avo
   - This means that the vehicle is parked on the edge of the lane. This prevents the vehicle from avoiding a vehicle waiting at a traffic light in the middle of the lane. However, this is not an appropriate implementation for the purpose. Even if a vehicle is in the center of the lane, it should be avoided if it has its hazard lights on, and this is a point that should be improved in the future as the recognition performance improves.
 - Object is not behind ego(default: > -`2.0 m`) or too far(default: < `150.0 m`) and object is not behind the path goal.
 
-![fig1](./image/avoidance/target_vehicle_selection.svg)
+![fig1](../image/avoidance/target_vehicle_selection.svg)
 
 ### Parked-car detection
 
@@ -203,7 +203,7 @@ $$
 
 The closer the object is to the shoulder, the larger the value of $ratio$ (theoretical max value is 1.0), and it compares the value and `object_check_shiftable_ratio` to determine whether the object is a parked-car.
 
-![fig2](./image/avoidance/parked-car-detection.svg)
+![fig2](../image/avoidance/parked-car-detection.svg)
 
 ### Compensation for detection lost
 
@@ -222,9 +222,9 @@ Therefore, in order to reduce the influence of the noise, avoidance module gener
 object_envelope_buffer: 0.3 # [m]
 ```
 
-![fig1](./image/avoidance/envelope_polygon.svg)
+![fig1](../image/avoidance/envelope_polygon.svg)
 
-![fig1](./image/avoidance/shift_line_generation.svg)
+![fig1](../image/avoidance/shift_line_generation.svg)
 
 ### Computing Shift Length and Shift Points
 
@@ -245,7 +245,7 @@ else
 
 The following figure illustrates these variables(This figure just shows the max value of lateral shift length).
 
-![shift_point_and_its_constraints](./image/avoidance/avoidance_module-shift_point_and_its_constraints.drawio.png)
+![shift_point_and_its_constraints](../image/avoidance/avoidance_module-shift_point_and_its_constraints.drawio.png)
 
 ### Rationale of having safety buffer and safety margin
 
@@ -256,7 +256,7 @@ To compute the shift length, additional parameters that can be tune are `lateral
   - It is recommended to set the value to more than half of the ego vehicle's width.
 - The `road_shoulder_safety_margin` will prevent the module from generating a path that might cause the vehicle to go too near the road shoulder or adjacent lane dividing line.
 
-![shift_length_parameters](./image/shift_length_parameters.drawio.svg)
+![shift_length_parameters](../image/shift_length_parameters.drawio.svg)
 
 ### Generating path only within lanelet boundaries
 
@@ -267,7 +267,7 @@ The shift length is set as a constant value before the feature is implemented. S
 
 These elements are used to compute the distance from the object to the road's shoulder (`to_road_shoulder_distance`). The parameters `enable_avoidance_over_same_direction` and `enable_avoidance_over_opposite_direction` allows further configuration of the to `to_road_shoulder_distance`. The following image illustrates the configuration.
 
-![obstacle_to_road_shoulder_distance](./image/avoidance/obstacle_to_road_shoulder_distance.drawio.svg)
+![obstacle_to_road_shoulder_distance](../image/avoidance/obstacle_to_road_shoulder_distance.drawio.svg)
 
 If one of the following conditions is `false`, then the shift point will not be generated.
 
@@ -422,7 +422,7 @@ To solve that, this module provides a parameter for the minimum avoidance speed,
 - If the ego vehicle speed is lower than "nominal" minimum speed, use the minimum speed in the calculation of the jerk.
 - If the ego vehicle speed is lower than "sharp" minimum speed and a nominal lateral jerk is not enough for avoidance (the case where the ego vehicle is stopped close to the obstacle), use the "sharp" minimum speed in the calculation of the jerk (it should be lower than "nominal" speed).
 
-![fig1](./image/avoidance/how_to_decide_path_shape_one_object.drawio.svg)
+![fig1](../image/avoidance/how_to_decide_path_shape_one_object.drawio.svg)
 
 #### Multiple obstacle case (one direction)
 
@@ -432,13 +432,13 @@ Generate shift points for multiple obstacles. All of them are merged to generate
 
 For the details of the shift point filtering, see [filtering for shift points](#filtering-for-shift-points).
 
-![fig1](./image/avoidance/how_to_decide_path_shape_multi_object_one_direction.drawio.svg)
+![fig1](../image/avoidance/how_to_decide_path_shape_multi_object_one_direction.drawio.svg)
 
 #### Multiple obstacle case (both direction)
 
 Generate shift points for multiple obstacles. All of them are merged to generate new shift points. If there are areas where the desired shifts conflict in different directions, the sum of the maximum shift amounts of these areas is used as the final shift amount. The rest of the process is the same as in the case of one direction.
 
-![fig1](./image/avoidance/how_to_decide_path_shape_multi_object_both_direction.drawio.svg)
+![fig1](../image/avoidance/how_to_decide_path_shape_multi_object_both_direction.drawio.svg)
 
 #### Filtering for shift points
 
@@ -465,23 +465,23 @@ safety_check_idling_time: 1.5 # [s]
 safety_check_accel_for_rss: 2.5 # [m/ss]
 ```
 
-![fig1](./image/avoidance/safety_check_flowchart.svg)
+![fig1](../image/avoidance/safety_check_flowchart.svg)
 
 `safety_check_backward_distance` is the parameter related to the safety check area. The module checks a collision risk for all vehicle that is within shift side lane and between object `object_check_forward_distance` ahead and `safety_check_backward_distance` behind.
 
-![fig1](./image/avoidance/safety_check_step_1.svg)
+![fig1](../image/avoidance/safety_check_step_1.svg)
 
 **NOTE**: Even if a part of an object polygon overlaps the detection area, if the center of gravity of the object does not exist on the lane, the vehicle is excluded from the safety check target.
 
 ---
 
 Judge the risk of collision based on ego future position and object prediction path. The module calculates Ego's future position in the time horizon (`safety_check_time_horizon`), and use object's prediction path as object future position.
 
-![fig1](./image/avoidance/safety_check_step_2.svg)
+![fig1](../image/avoidance/safety_check_step_2.svg)
 
 After calculating the future position of Ego and object, the module calculates the lateral/longitudinal deviation of Ego and the object. The module also calculates the lateral/longitudinal margin necessary to determine that it is safe to execute avoidance maneuver, and if both the lateral and longitudinal distances are less than the margins, it determines that there is a risk of a collision at that time.
 
-![fig1](./image/avoidance/safety_check_margin.svg)
+![fig1](../image/avoidance/safety_check_margin.svg)
 
 The value of the longitudinal margin is calculated based on Responsibility-Sensitive Safety theory ([RSS](https://newsroom.intel.com/articles/rss-explained-five-rules-autonomous-vehicle-safety/#gs.ljzofv)). The `safety_check_idling_time` represents $T_{idle}$, and `safety_check_accel_for_rss` represents $a_{max}$.
 
@@ -491,7 +491,7 @@ $$
 
 The lateral margin is changeable based on ego longitudinal velocity. If the vehicle is driving at a high speed, the lateral margin should be larger, and if the vehicle is driving at a low speed, the value of the lateral margin should be set to a smaller value. Thus, the lateral margin for each vehicle speed is set as a parameter, and the module determines the lateral margin from the current vehicle speed as shown in the following figure.
 
-![fig1](./image/avoidance/dynamic_lateral_margin.svg)
+![fig1](../image/avoidance/dynamic_lateral_margin.svg)
 
 ```yaml
 target_velocity_matrix:
@@ -513,7 +513,7 @@ If an avoidance path can be generated and it is determined that avoidance maneuv
 yield_velocity: 2.78 # [m/s]
 ```
 
-![fig1](./image/avoidance/yield_maneuver.svg)
+![fig1](../image/avoidance/yield_maneuver.svg)
 
 **NOTE**: In yield maneuver, the vehicle decelerates target velocity under constraints.
 
@@ -554,9 +554,9 @@ $$
 SHIFT_{current} > L_{threshold}
 $$
 
-![fig1](./image/avoidance/yield_limitation.svg)
+![fig1](../image/avoidance/yield_limitation.svg)
 
-![fig1](./image/avoidance/yield_maneuver_flowchart.svg)
+![fig1](../image/avoidance/yield_maneuver_flowchart.svg)
 
 ---
 
@@ -718,7 +718,7 @@ namespace: `avoidance.constraints.longitudinal.`
 - **Planning on the intersection**
   - If it is known that the ego vehicle is going to stop in the middle of avoidance execution (for example, at a red traffic light), sometimes the avoidance should not be executed until the vehicle is ready to move. This is because it is impossible to predict how the environment will change during the stop.　 This is especially important at intersections.
 
-![fig1](./image/avoidance/intersection_problem.drawio.svg)
+![fig1](../image/avoidance/intersection_problem.drawio.svg)
 
 - **Safety Check**
 
@@ -746,15 +746,15 @@ namespace: `avoidance.constraints.longitudinal.`
 
 Developers can see what is going on in each process by visualizing all the avoidance planning process outputs. The example includes target vehicles, shift points for each object, shift points after each filtering process, etc.
 
-![fig1](./image/avoidance/avoidance-debug-marker.png)
+![fig1](../image/avoidance/avoidance-debug-marker.png)
 
 To enable the debug marker, execute `ros2 param set /planning/scenario_planning/lane_driving/behavior_planning/behavior_path_planner avoidance.publish_debug_marker true` (no restart is needed) or simply set the `publish_debug_marker` to `true` in the `avoidance.param.yaml` for permanent effect (restart is needed). Then add the marker `/planning/scenario_planning/lane_driving/behavior_planning/behavior_path_planner/debug/avoidance` in `rviz2`.
 
 ### Echoing debug message to find out why the objects were ignored
 
 If for some reason, no shift point is generated for your object, you can check for the failure reason via `ros2 topic echo`.
 
-![avoidance_debug_message_array](./image/avoidance/avoidance_debug_message_array.png)
+![avoidance_debug_message_array](../image/avoidance/avoidance_debug_message_array.png)
 
 To print the debug message, just run the following
 

planning/behavior_path_planner/behavior_path_planner_avoidance_design.md planning/behavior_path_planner/docs/behavior_path_planner_avoidance_design.md

@@ -70,7 +70,7 @@ struct DrivalbleLanes
 
 The image of the sorted drivable lanes is depicted in the following picture.
 
-![sorted_lanes](./image/drivable_area/sorted_lanes.drawio.svg)
+![sorted_lanes](../image/drivable_area/sorted_lanes.drawio.svg)
 
 Note that, the order of drivable lanes become
 
@@ -89,7 +89,7 @@ std::vector<geometry_msgs::msg::Point> right_bound;
 
 and each point of right bound and left bound has a position in the absolute coordinate system.
 
-![drivable_lines](./image/drivable_area/drivable_lines.drawio.svg)
+![drivable_lines](../image/drivable_area/drivable_lines.drawio.svg)
 
 ### Drivable Area Expansion
 
@@ -98,7 +98,7 @@ and each point of right bound and left bound has a position in the absolute coor
 Each module can statically expand the left and right bounds of the target lanes by the parameter defined values.
 This enables large vehicles to pass narrow curve. The image of this process can be described as
 
-![expanded_lanes](./image/drivable_area/expanded_lanes.drawio.svg)
+![expanded_lanes](../image/drivable_area/expanded_lanes.drawio.svg)
 
 Note that we only expand right bound of the rightmost lane and left bound of the leftmost lane.
 
@@ -113,11 +113,11 @@ This expansion can be summarized with the following steps:
 4. Remove the footprints from step 2 and the lines from step 3 from the ego path footprint from step 1.
 5. Expand the drivable area with the result of step 4.
 
-|                                  |                                                                                                     |
-| :------------------------------- | :-------------------------------------------------------------------------------------------------- |
-| Inputs                           | ![drivable_area_expansion_inputs](./image/drivable_area/drivable_area_expansion_inputs.png)         |
-| Footprints and uncrossable lines | ![drivable_area_expansion_footprints](./image/drivable_area/drivable_area_expansion_footprints.png) |
-| Expanded drivable area           | ![drivable_area_expansion_result](./image/drivable_area/drivable_area_expansion_result.png)         |
+|                                  |                                                                                                      |
+| :------------------------------- | :--------------------------------------------------------------------------------------------------- |
+| Inputs                           | ![drivable_area_expansion_inputs](../image/drivable_area/drivable_area_expansion_inputs.png)         |
+| Footprints and uncrossable lines | ![drivable_area_expansion_footprints](../image/drivable_area/drivable_area_expansion_footprints.png) |
+| Expanded drivable area           | ![drivable_area_expansion_result](../image/drivable_area/drivable_area_expansion_result.png)         |
 
 Please note that the dynamic expansion can only increase the size of the drivable area and cannot remove any part from the original drivable area.
 
@@ -129,8 +129,8 @@ For example, in the same area, one can perform avoidance and another cannot. Thi
 
 To debug the issue, the maximum drivable area boundary can be visualized.
 
-![drivable_area_boundary_marker1](./image/drivable_area/drivable_area_boundary_marker_example1.png)
+![drivable_area_boundary_marker1](../image/drivable_area/drivable_area_boundary_marker_example1.png)
 
-![drivable_area_boundary_marker2](./image/drivable_area/drivable_area_boundary_marker_example2.png)
+![drivable_area_boundary_marker2](../image/drivable_area/drivable_area_boundary_marker_example2.png)
 
 The maximum drivable area can be visualize by adding the marker from `/planning/scenario_planning/lane_driving/behavior_planning/behavior_path_planner/maximum_drivable_area`