In this paper, we address the application of stochastic model predictive control with chance constraints to autonomous driving. We use a condensed formulation of a linearized vehicle model to setup a quadratic program with nonlinear chance constraints, which can be solved with off-the-shelf optimization algorithms. We further show how obstacle information in the path planning stage can be converted into a set of linear state constraints that can be directly used in the control algorithm. The resulting controller is potentially real-time capable and achieves a tradeoff between safety and comfort in its control behavior.
Stochastic model predictive controller with chance constraints for comfortable and safe driving behavior of autonomous vehicles
2015-06-01
695269 byte
Conference paper
Electronic Resource
English
Model Predictive Control for Safe Autonomous Driving Applications
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