CommonRoad-CriMe: A Toolbox for Criticality Measures of Autonomous Vehicles

Yuanfei Lin, Matthias Althoff

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

19 Scopus citations

Abstract

Criticality measures are essential for autonomous vehicles to capture the complexity of the surrounding environment, trigger emergency maneuvers, and verify safety. However, there is currently no publicly available toolbox that allows researchers to use or evaluate a large number of criticality measures on arbitrary traffic scenarios. To address this issue, we present CommonRoad-CriMe, an open-source toolbox for measuring the criticality of autonomous vehicles in a unified framework. Our toolbox covers a wide range of state-of-the-art criticality measures and provides visualized information to facilitate debugging and showcasing. Numerical experiments demonstrate how our toolbox facilitates the comparison of different criticality measures and the analysis of traffic conflicts. Our toolbox is available at commonroad.in.tum.de.

Original languageEnglish
Title of host publicationIV 2023 - IEEE Intelligent Vehicles Symposium, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350346916
DOIs
StatePublished - 2023
Event34th IEEE Intelligent Vehicles Symposium, IV 2023 - Anchorage, United States
Duration: 4 Jun 20237 Jun 2023

Publication series

NameIEEE Intelligent Vehicles Symposium, Proceedings
Volume2023-June

Conference

Conference34th IEEE Intelligent Vehicles Symposium, IV 2023
Country/TerritoryUnited States
CityAnchorage
Period4/06/237/06/23

Fingerprint

Dive into the research topics of 'CommonRoad-CriMe: A Toolbox for Criticality Measures of Autonomous Vehicles'. Together they form a unique fingerprint.

Cite this