Stochastic model predictive controller with chance constraints for comfortable and safe driving behavior of autonomous vehicles

David Lenz, Tobias Kessler, Alois Knoll

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

25 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publicationIV 2015 - 2015 IEEE Intelligent Vehicles Symposium
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages292-297
Number of pages6
ISBN (Electronic)9781467372664
DOIs
StatePublished - 26 Aug 2015
EventIEEE Intelligent Vehicles Symposium, IV 2015 - Seoul, Korea, Republic of
Duration: 28 Jun 20151 Jul 2015

Publication series

NameIEEE Intelligent Vehicles Symposium, Proceedings
Volume2015-August

Conference

ConferenceIEEE Intelligent Vehicles Symposium, IV 2015
Country/TerritoryKorea, Republic of
CitySeoul
Period28/06/151/07/15

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