Behavior Path Planner

The Behavior Path Planner’s main objective is to significantly enhance the safety of autonomous vehicles by minimizing the risk of accidents. It improves driving efficiency through time conservation and underpins reliability with its rule-based approach. Additionally, it allows users to integrate their own custom behavior modules or use it with different types of vehicles, such as cars, buses, and delivery robots, as well as in various environments, from busy urban streets to open highways.

The module begins by thoroughly analyzing the ego vehicle’s current situation, including its position, speed, and surrounding environment. This analysis leads to essential driving decisions about lane changes or stopping and subsequently generates a path that is both safe and efficient. It considers road geometry, traffic rules, and dynamic conditions while also incorporating obstacle avoidance to respond to static and dynamic obstacles such as other vehicles, pedestrians, or unexpected roadblocks, ensuring safe navigation.

Moreover, the planner actively interacts with other traffic participants, predicting their actions and accordingly adjusting the vehicle’s path. This ensures not only the safety of the autonomous vehicle but also contributes to smooth traffic flow. Its adherence to traffic laws, including speed limits and traffic signals, further guarantees lawful and predictable driving behavior. The planner is also designed to minimize sudden or abrupt maneuvers, aiming for a comfortable and natural driving experience.

!!! note

The [Planning Component Design](https://autowarefoundation.github.io/autoware-documentation/v1.0/design/autoware-architecture/planning/) Document outlines the foundational philosophy guiding the design and future development of the Behavior Path Planner module. We strongly encourage readers to consult this document to understand the rationale behind its current configuration and the direction of its ongoing development.

Purpose / Use Cases

Essentially, the module has three primary responsibilities:

1. Creating a path based on the traffic situation.
2. Generating drivable area, i.e. the area within which the vehicle can maneuver.
3. Generating turn signal commands to be relayed to the vehicle interface.

Features

Supported Scene Modules

Behavior Path Planner has following scene modules

!!! Note

click on the following images to view the video of their execution

<div align="center">
    <table>
        <tr>
            <td><img src="./image/supported_module_lane_following.svg" alt="Lane Following Module" width="300"></td>
            <td><a href="https://www.youtube.com/watch?v=A_V9yvfKZ4E"><img src="./image/supported_module_avoidance.svg" alt="Avoidance Module" width="300"></a></td>
            <td><img src="./image/supported_module_avoidance_by_lane_change.svg" alt="Avoidance by Lane Change Module" width="300"></td>
        </tr>
        <tr>
            <td><a href="https://www.youtube.com/watch?v=0jRDGQ84cD4"><img src="./image/supported_module_lane_change.svg" alt="Lane Change Module" width="300"></a></td>
            <td><a href="https://www.youtube.com/watch?v=xOjnPqoHup4"><img src="./image/supported_module_start_planner.svg" alt="Start Planner Module" width="300"></a></td>
            <td><a href="https://www.youtube.com/watch?v=ornbzkWxRWU"><img src="./image/supported_module_goal_planner.svg" alt="Goal Planner Module" width="300"></a></td>
        </tr>
    </table>
</div>

!!! Note

Users can refer to [Planning component design](https://autowarefoundation.github.io/autoware-documentation/v1.0/design/autoware-architecture/planning/#supported-functions) for some additional behavior.

How to add or implement new module?

All scene modules are implemented by inheriting base class scene_module_interface.hpp.

!!! Warning

The remainder of this subsection is work in progress (WIP).

Planner Manager

The Planner Manager’s responsibilities include:

1. Activating the relevant scene module in response to the specific situation faced by the autonomous vehicle. For example, when a parked vehicle blocks the ego vehicle’s driving lane, the manager would engage the avoidance module.
2. Managing the execution order when multiple modules are running simultaneously. For instance, if both the lane-changing and avoidance modules are operational, the manager decides which should take precedence.
3. Merging paths from multiple modules when they are activated simultaneously and each generates its own path, thereby creating a single functional path.

!!! note

To check the scene module's transition, i.e.: registered, approved and candidate modules, set `verbose: true` in the [behavior path planner configuration file](https://github.com/autowarefoundation/autoware_launch/blob/0cd5d891a36ac34a32a417205905c109f2bafe7b/autoware_launch/config/planning/scenario_planning/lane_driving/behavior_planning/behavior_path_planner/behavior_path_planner.param.yaml#L3).

![Scene module's transition table](./image/checking_module_transition.png)

!!! note

For more in-depth information, refer to [Manager design](./docs/behavior_path_planner_manager_design.md) document.

Inputs / Outputs / API

Input

• ○ Mandatory: Planning Module would not work if anyone of this is not present.
• △ Optional: Some module would not work, but Planning Module can still be operated.

Output

Debug

!!! note

For specific information of which topics are being subscribed and published, refer to [behavior_path_planner.xml](https://github.com/autowarefoundation/autoware.universe/blob/9000f430c937764c14e43109539302f1f878ed70/planning/behavior_path_planner/launch/behavior_path_planner.launch.xml#L36-L49).

How to enable or disable the modules

Enabling and disabling the modules in the behavior path planner is primarily managed through two key files: default_preset.yaml and behavior_path_planner.launch.xml.

The default_preset.yaml file acts as a configuration file for enabling or disabling specific modules within the planner. It contains a series of arguments which represent the behavior path planner’s modules or features. For example:

• launch_avoidance_module: Set to true to enable the avoidance module, or false to disable it.
• use_experimental_lane_change_function: Set to true to enable experimental features in the lane change module.

!!! note

Click [here](https://github.com/autowarefoundation/autoware_launch/blob/v1.0/autoware_launch/config/planning/preset/default_preset.yaml) to view the `default_preset.yaml`.

The behavior_path_planner.launch.xml file references the settings defined in default_preset.yaml to apply the configurations when the behavior path planner’s node is running. For instance, the parameter avoidance.enable_module in

<param name="avoidance.enable_module" value="$(var launch_avoidance_module)"/>

corresponds to launch_avoidance_module from default_preset.yaml.

Therefore, to enable or disable a module, simply set the corresponding module in default_preset.yaml to true or false. These changes will be applied upon the next launch of Autoware.

Generating Path

A sophisticated methodology is used for path generation, particularly focusing on maneuvers like lane changes and avoidance. At the core of this design is the smooth lateral shifting of the reference path, achieved through a constant-jerk profile. This approach ensures a consistent rate of change in acceleration, facilitating smooth transitions and minimizing abrupt changes in lateral dynamics, crucial for passenger comfort and safety.

The design involves complex mathematical formulations for calculating the lateral shift of the vehicle’s path over time. These calculations include determining lateral displacement, velocity, and acceleration, while considering the vehicle’s lateral acceleration and velocity limits. This is essential for ensuring that the vehicle’s movements remain safe and manageable.

The ShiftLine struct (as seen here) is utilized to represent points along the path where the lateral shift starts and ends. It includes details like the start and end points in absolute coordinates, the relative shift lengths at these points compared to the reference path, and the associated indexes on the reference path. This struct is integral to managing the path shifts, as it allows the path planner to dynamically adjust the trajectory based on the vehicle’s current position and planned maneuver.

Furthermore, the design and its implementation incorporate various equations and mathematical models to calculate essential parameters for the path shift. These include the total distance of the lateral shift, the maximum allowable lateral acceleration and jerk, and the total time required for the shift. Practical considerations are also noted, such as simplifying assumptions in the absence of a specific time interval for most lane change and avoidance cases.

The shifted path generation logic enables the behavior path planner to dynamically generate safe and efficient paths, precisely controlling the vehicle’s lateral movements to ensure the smooth execution of lane changes and avoidance maneuvers. This careful planning and execution adhere to the vehicle’s dynamic capabilities and safety constraints, maximizing efficiency and safety in autonomous vehicle navigation.

!!! note

If you're a math lover, refer to [Path Generation Design](./docs/behavior_path_planner_path_generation_design.md) for the nitty-gritty.

Collision Assessment / Safety check

The purpose of the collision assessment function in the Behavior Path Planner is to evaluate the potential for collisions with target objects across all modules. It is utilized in two scenarios:

1. During candidate path generation, to ensure that the generated candidate path is collision-free.
2. When the path is approved by the manager, and the ego vehicle is executing the current module. If the current situation is deemed unsafe, depending on each module’s requirements, the planner will either cancel the execution or opt to execute another module.

The safety check process involves several steps. Initially, it obtains the pose of the target object at a specific time, typically through interpolation of the predicted path. It then checks for any overlap between the ego vehicle and the target object at this time. If an overlap is detected, the path is deemed unsafe. The function also identifies which vehicle is in front by using the arc length along the given path. The function operates under the assumption that accurate data on the position, velocity, and shape of both the ego vehicle (the autonomous vehicle) and any target objects are available. It also relies on the yaw angle of each point in the predicted paths of these objects, which is expected to point towards the next path point.

A critical part of the safety check is the calculation of the RSS (Responsibility-Sensitive Safety) distance-inspired algorithm. This algorithm considers factors such as reaction time, safety time margin, and the velocities and decelerations of both vehicles. Extended object polygons are created for both the ego and target vehicles. Notably, the rear object’s polygon is extended by the RSS distance longitudinally and by a lateral margin. The function finally checks for overlap between this extended rear object polygon and the front object polygon. Any overlap indicates a potential unsafe situation.

However, the module does have a limitation concerning the yaw angle of each point in the predicted paths of target objects, which may not always accurately point to the next point, leading to potential inaccuracies in some edge cases.

!!! note

For further reading on the collision assessment  method, please refer to [Safety check utils](./docs/behavior_path_planner_safety_check.md)

Generating Drivable Area

Static Drivable Area logic

The drivable area is used to determine the area in which the ego vehicle can travel. The primary goal of static drivable area expansion is to ensure safe travel by generating an area that encompasses only the necessary spaces for the vehicle’s current behavior, while excluding non-essential areas. For example, while avoidance module is running, the drivable area includes additional space needed for maneuvers around obstacles, and it limits the behavior by not extending the avoidance path outside of lanelet areas.

Static drivable area expansion operates under assumptions about the correct arrangement of lanes and the coverage of both the front and rear of the vehicle within the left and right boundaries. Key parameters for drivable area generation include extra footprint offsets for the ego vehicle, the handling of dynamic objects, maximum expansion distance, and specific methods for expansion. Additionally, since each module generates its own drivable area, before passing it as the input to generate the next running module’s drivable area, or before generating a unified drivable area, the system sorts drivable lanes based on the vehicle’s passage order. This ensures the correct definition of the lanes used in drivable area generation.

!!! note

Further details can is provided in [Drivable Area Design](./docs/behavior_path_planner_drivable_area_design.md).

Dynamic Drivable Area Logic

Large vehicles require much more space, which sometimes causes them to veer out of their current lane. A typical example being a bus making a turn at a corner. In such cases, relying on a static drivable area is insufficient, since the static method depends on lane information provided by high-definition maps. To overcome the limitations of the static approach, the dynamic drivable area expansion algorithm adjusts the navigable space for an autonomous vehicle in real-time. It conserves computational power by reusing previously calculated path data, updating only when there is a significant change in the vehicle’s position. The system evaluates the minimum lane width necessary to accommodate the vehicle’s turning radius and other dynamic factors. It then calculates the optimal expansion of the drivable area’s boundaries to ensure there is adequate space for safe maneuvering, taking into account the vehicle’s path curvature. The rate at which these boundaries can expand or contract is moderated to maintain stability in the vehicle’s navigation. The algorithm aims to maximize the drivable space while avoiding fixed obstacles and adhering to legal driving limits. Finally, it applies these boundary adjustments and smooths out the path curvature calculations to ensure a safe and legally compliant navigable path is maintained throughout the vehicle’s operation.

!!! note

The feature can be enabled in the [drivable_area_expansion.param.yaml](https://github.com/autowarefoundation/autoware_launch/blob/0cd5d891a36ac34a32a417205905c109f2bafe7b/autoware_launch/config/planning/scenario_planning/lane_driving/behavior_planning/behavior_path_planner/drivable_area_expansion.param.yaml#L10).

Generating Turn Signal

The Behavior Path Planner module uses the autoware_auto_vehicle_msgs::msg::TurnIndicatorsCommand to output turn signal commands (see TurnIndicatorsCommand.idl). The system evaluates the driving context and determines when to activate turn signals based on its maneuver planning—like turning, lane changing, or obstacle avoidance.

Within this framework, the system differentiates between desired and required blinker activations. Desired activations are those recommended by traffic laws for typical driving scenarios, such as signaling before a lane change or turn. Required activations are those that are deemed mandatory for safety reasons, like signaling an abrupt lane change to avoid an obstacle.

The TurnIndicatorsCommand message structure has a command field that can take one of several constants: NO_COMMAND indicates no signal is necessary, DISABLE to deactivate signals, ENABLE_LEFT to signal a left turn, and ENABLE_RIGHT to signal a right turn. The Behavior Path Planner sends these commands at the appropriate times, based on its rules-based system that considers both the desired and required scenarios for blinker activation.

!!! note

For more in-depth information, refer to [Turn Signal Design](./docs/behavior_path_planner_turn_signal_design.md) document.

Rerouting

!!! warning

Rerouting is a feature that was still under progress. Further information will be included on a later date.

Parameters and Configuration

The configuration files are organized in a hierarchical directory structure for ease of navigation and management. Each subdirectory contains specific configuration files relevant to its module. The root directory holds general configuration files that apply to the overall behavior of the planner. The following is an overview of the directory structure with the respective configuration files.

behavior_path_planner
├── behavior_path_planner.param.yaml
├── drivable_area_expansion.param.yaml
├── scene_module_manager.param.yaml
├── avoidance
│   └── avoidance.param.yaml
├── avoidance_by_lc
│   └── avoidance_by_lc.param.yaml
├── dynamic_avoidance
│   └── dynamic_avoidance.param.yaml
├── goal_planner
│   └── goal_planner.param.yaml
├── lane_change
│   └── lane_change.param.yaml
├── side_shift
│   └── side_shift.param.yaml
└── start_planner
    └── start_planner.param.yaml

Similarly, the common directory contains configuration files that are used across various modules, providing shared parameters and settings essential for the functioning of the Behavior Path Planner:

common
├── common.param.yaml
├── costmap_generator.param.yaml
└── nearest_search.param.yaml

The preset directory contains the configurations for managing the operational state of various modules. It includes the default_preset.yaml file, which specifically caters to enabling and disabling modules within the system.

preset
└── default_preset.yaml

Limitations & Future Work

1. Goal Planner module cannot be simultaneously executed together with other modules.
2. Module is not designed as plugin. Integrating custom module is not straightforward and user have to modify some part of the behavior path planner main code.