Planning and Control
Automated Driving Toolbox™ provides several features that support path planning and vehicle control.
To plan driving paths, you can use a vehicle costmap and the optimal rapidly exploring random tree (RRT*) motion-planning algorithm. You can also check the validity of the path, smooth the path, and generate a velocity profile along the path.
To design vehicle control systems, you can use lateral and longitudinal controllers that enable autonomous vehicles to follow a planned trajectory.
|Costmap representing planning space around vehicle|
|Store vehicle dimensions|
|Check vehicle costmap for collision-free poses or points|
|Check vehicle costmap for occupied poses or points|
|Get cost value of cells in vehicle costmap|
|Set cost value of cells in vehicle costmap|
|Collision-checking configuration for costmap based on inflation|
|Configure RRT* path planner|
|Plan vehicle path using RRT* path planner|
|Check validity of planned vehicle path|
|Planned vehicle path|
|Interpolate poses along planned vehicle path|
|Smooth vehicle path using cubic spline interpolation (Since R2019a)|
|Path Smoother Spline||Smooth vehicle path using cubic spline interpolation (Since R2019a)|
|Velocity Profiler||Generate velocity profile of vehicle path given kinematic constraints (Since R2019b)|
|Lateral Controller Stanley||Control steering angle of vehicle for path following by using Stanley method|
|Longitudinal Controller Stanley||Control longitudinal velocity of vehicle by using Stanley method (Since R2019a)|
- Lateral Control Tutorial
Control the steering angle of a vehicle following a planned path and perform lane changing.
- Code Generation for Path Planning and Vehicle Control
Generate C++ code for a path planning and vehicle control algorithm, and verify the code using software-in-the-loop simulation.