Automated Driving Applications
You can use model predictive control (MPC) in automated driving applications to improve vehicle responsiveness while maintaining passenger comfort and safety. MPC has several features that are useful for automated driving, such as predicting vehicle behavior in the near future and explicitly handling constraints during optimization. For more information, see Automated Driving Using Model Predictive Control.
|Adaptive Cruise Control System||Simulate adaptive cruise control using model predictive controller|
|Lane Keeping Assist System||Simulate lane-keeping assistance using adaptive model predictive controller|
|Path Following Control System||Simulate path-following control using adaptive model predictive controller|
|Nonlinear MPC Controller||Simulate nonlinear model predictive controllers|
MPC Driving Basics
You can design and simulate automated driving systems using MPC controllers.
Adaptive Cruise Control
Design an MPC controller that tracks a set velocity and maintains a safe distance from a lead vehicle by adjusting the longitudinal acceleration of an ego vehicle.
Design an adaptive cruise control system that detects a lead vehicle in its environment by combining data from vision and radar sensors.
Lane Keeping Assist
Design an MPC controller that keeps an ego vehicle traveling along the center of a straight or curved road by adjusting the front steering angle.
Design an MPC-based lane-keeping assist system that uses lane detection and road curvature previewing from the Automated Driving Toolbox™.
Design a lane-following controller using nonlinear MPC with road curvature previewing.
Design an MPC-based lane-following system that uses lane detection and road curvature previewing from the Automated Driving Toolbox.
Design an MPC-based lane-following system that detects lane and vehicles using a camera system simulated using the Unreal Engine®.
Automate testing of highway lane-following controller against multiple testing scenarios.
Simulate lane following applications that contain intelligent target vehicles that adapt their trajectories based on neighboring vehicles.
Design a lane-change controller using a nonlinear MPC controller.
Simulate a lane-changing controller in a highway driving scenario.
Design controller for parking garage valet using nonlinear model predictive control.
Design a parallel parking controller using nonlinear model predictive control.
Automatically parallel park a vehicle by generating a path using the RRT star planner and tracking the trajectory using nonlinear model predictive control.