Rule-Compliant Trajectory Repairing using Satisfiability Modulo Theories

Yuanfei Lin, Matthias Althoff

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

13 Scopus citations

Abstract

Autonomous vehicles must comply with traffic rules. However, most motion planners do not explicitly consider all relevant traffic rules. Once traffic rule violations of an initially-planned trajectory are detected, there is often not enough time to replan the entire trajectory. To solve this problem, we propose to repair the initial trajectory by investigating the satisfiability modulo theories paradigm. This framework makes it efficient to reason whether and how the trajectory can be repaired and, at the same time, determine the part along the trajectory that can remain unchanged. Moreover, the robustness of traffic rule satisfaction is used to formulate a convex optimization problem for generating rule-compliant trajectories. We compare our approach with trajectory replanning and demonstrate its usefulness with traffic scenarios from the CommonRoad benchmark suite and recorded data. The evaluation result shows that rule-compliant trajectory repairing is computationally efficient and widely applicable.

Original languageEnglish
Title of host publication2022 IEEE Intelligent Vehicles Symposium, IV 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages449-456
Number of pages8
ISBN (Electronic)9781665488211
DOIs
StatePublished - 2022
Event2022 IEEE Intelligent Vehicles Symposium, IV 2022 - Aachen, Germany
Duration: 5 Jun 20229 Jun 2022

Publication series

NameIEEE Intelligent Vehicles Symposium, Proceedings
Volume2022-June

Conference

Conference2022 IEEE Intelligent Vehicles Symposium, IV 2022
Country/TerritoryGermany
CityAachen
Period5/06/229/06/22

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