TY - GEN
T1 - Minimum-Violation Velocity Planning with Temporal Logic Constraints
AU - Halder, Patrick
AU - Althoff, Matthias
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Motion planning for autonomous agents requires compliance with a variety of constraints. However, in some situations, all constraints cannot be simultaneously satisfied, e.g., due to the misbehavior of other traffic participants. In such situations, one strategy for guaranteeing a feasible behavior of the system is deliberately ignoring less important constraints while maintaining the satisfaction of more important ones. We address this problem by presenting a novel velocity planner for an autonomous shuttle that violates temporal logic constraints as little as possible in the sense that important constraints are violated last. In particular, we provide an A-based velocity planner that minimally violates a hierarchically ordered set of constraints formalized in signal temporal logic. We apply our approach to challenging scenarios from the CommonRoad benchmark suite, showing that our proposed method yields easily interpretable and explainable decisions.
AB - Motion planning for autonomous agents requires compliance with a variety of constraints. However, in some situations, all constraints cannot be simultaneously satisfied, e.g., due to the misbehavior of other traffic participants. In such situations, one strategy for guaranteeing a feasible behavior of the system is deliberately ignoring less important constraints while maintaining the satisfaction of more important ones. We address this problem by presenting a novel velocity planner for an autonomous shuttle that violates temporal logic constraints as little as possible in the sense that important constraints are violated last. In particular, we provide an A-based velocity planner that minimally violates a hierarchically ordered set of constraints formalized in signal temporal logic. We apply our approach to challenging scenarios from the CommonRoad benchmark suite, showing that our proposed method yields easily interpretable and explainable decisions.
UR - http://www.scopus.com/inward/record.url?scp=85141836568&partnerID=8YFLogxK
U2 - 10.1109/ITSC55140.2022.9922114
DO - 10.1109/ITSC55140.2022.9922114
M3 - Conference contribution
AN - SCOPUS:85141836568
T3 - IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
SP - 2520
EP - 2527
BT - 2022 IEEE 25th International Conference on Intelligent Transportation Systems, ITSC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 25th IEEE International Conference on Intelligent Transportation Systems, ITSC 2022
Y2 - 8 October 2022 through 12 October 2022
ER -