Fuzzy Interpretation of Operational Design Domains in Autonomous Driving

Aniket Salvi, Gereon Weiss, Mario Trapp, Fabian Oboril, Cornelius Buerkle

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

4 Scopus citations


The evolution towards autonomous driving involves operating safely in open-world environments. For this, autonomous vehicles and their Autonomous Driving System (ADS) are designed and tested for specific, so-called Operational Design Domains (ODDs). When moving from prototypes to real-world mobility solutions, autonomous vehicles, however, will face changing scenarios and operational conditions that they must handle safely. Within this work, we propose a fuzzy-based approach to consider changing operational conditions of autonomous driving based on smaller ODD fragments, called mu ODDs. By this, an ADS is enabled to smoothly adapt its driving behavior for meeting safety during shifting operational conditions. We evaluate our solution in simulated vehicle following scenarios passing through different mu ODDs, modeled by weather changes. The results show that our approach is capable of considering operational domain changes without endangering safety and allowing improved utility optimization.

Original languageEnglish
Title of host publication2022 IEEE Intelligent Vehicles Symposium, IV 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages7
ISBN (Electronic)9781665488211
StatePublished - 2022
Externally publishedYes
Event2022 IEEE Intelligent Vehicles Symposium, IV 2022 - Aachen, Germany
Duration: 5 Jun 20229 Jun 2022

Publication series

NameIEEE Intelligent Vehicles Symposium, Proceedings


Conference2022 IEEE Intelligent Vehicles Symposium, IV 2022


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