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Towards a Complete Safety Framework for Longitudinal Driving
Halmstad University, School of Information Technology.ORCID iD: 0000-0001-8587-2251
Lund University, Lund, Sweden.
Lund University, Lund, Sweden.ORCID iD: 0000-0002-9738-4148
Karlsruhe Institute Of Technology, Karlsruhe, Germany.ORCID iD: 0000-0003-4894-4134
2024 (English)In: IEEE Intelligent Vehicles Symposium, Proceedings, Piscataway: Institute of Electrical and Electronics Engineers (IEEE), 2024, p. 3159-3159Conference paper, Published paper (Refereed)
Abstract [en]

Formal models for the safety validation of autonomous vehicles have become increasingly important. To this end, we present a safety framework for longitudinal automated driving. This framework enables the calculation of minimum safe inter-vehicular distances for arbitrary ego vehicle control policies in a computationally efficient manner. We use this framework to enhance and generalize the Responsibility-Sensitive Safety (RSS) [1] model and models based on it, which fail to cover situations where the ego vehicle has a higher decelerating capacity than its preceding vehicle. © 2024 IEEE.

Place, publisher, year, edition, pages
Piscataway: Institute of Electrical and Electronics Engineers (IEEE), 2024. p. 3159-3159
Series
IEEE Intelligent Vehicles Symposium, ISSN 1931-0587, E-ISSN 2642-7214
Keywords [en]
Computational modeling, Safety, Computational efficiency, Autonomous vehicles
National Category
Vehicle and Aerospace Engineering
Identifiers
URN: urn:nbn:se:hh:diva-55032DOI: 10.1109/IV55156.2024.10588489ISI: 001275100903052ISBN: 979-8-3503-4881-1 (electronic)ISBN: 979-8-3503-4882-8 (print)OAI: oai:DiVA.org:hh-55032DiVA, id: diva2:1921218
Conference
35th IEEE Intelligent Vehicles Symposium, IV 2024, Jeju Island, South Korea, 2-5 June, 2024
Available from: 2024-12-13 Created: 2024-12-13 Last updated: 2025-10-01Bibliographically approved

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Sidorenko, GalinaThunberg, JohanVinel, Alexey

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • de-DE
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Output format
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