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Efficiently Bounding the Probabilities of Vehicle Collision at Intelligent Intersections
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).ORCID iD: 0000-0002-9738-4148
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).ORCID iD: 0000-0001-8587-2251
Scania CV AB, Södertälje, Sweden.
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS). Western Norway University of Applied Sciences, Bergen, Norway.ORCID iD: 0000-0003-4894-4134
2021 (English)In: IEEE Open Journal of Intelligent Transportation Systems, E-ISSN 2687-7813, Vol. 2, p. 47-59Article in journal (Refereed) Published
Abstract [en]

Intelligent intersections have the potential to serve as an integral part of tomorrow’s traffic infrastructure. Wireless communication is key to enabling such technology. We consider a scenario where two flows of vehicles are to traverse an intelligent intersection. We investigate safety in emergency braking scenarios, where one of the vehicles in a flow suddenly decides to emergency brake and emergency braking messages are broadcast to affected vehicles. We provide a framework for computing lower bounds on probabilities for safe braking – collisions between vehicles are to be avoided. If we require that a crash or collision, for example, occurs at most once in a million scenarios, our approach allows for computation of lower bounds on the time-varying (or distance-varying) packet loss probabilities to ensure this. One of the benefits of the proposed framework is that the computational time is reduced; eliminating, for example, the need for time-consuming Monte Carlo simulations.

Place, publisher, year, edition, pages
New York, NY: IEEE, 2021. Vol. 2, p. 47-59
Keywords [en]
V2X, vehicular communications, collision, crash, safety, C-ITS, intelligent intersection, autonomous vehicles, ISO 21448
National Category
Communication Systems Telecommunications
Identifiers
URN: urn:nbn:se:hh:diva-43848DOI: 10.1109/OJITS.2021.3058449ISI: 000710543200004Scopus ID: 2-s2.0-85111610452OAI: oai:DiVA.org:hh-43848DiVA, id: diva2:1527765
Funder
Knowledge FoundationSwedish Foundation for Strategic ResearchEU, Horizon 2020The Research Council of NorwayVinnovaELLIIT - The Linköping‐Lund Initiative on IT and Mobile Communications
Note

Funding: This work was supported in part by the Knowledge Foundation (KKS) in the framework of “Safety of Connected Intelligent Vehicles in Smart Cities—SafeSmart” Project (2019–2023); in part by the Swedish Foundation for Strategic Research (SSF) in the framework of Strategic Mobility Program (2019-2020); in part by the EU Horizon 2020 Program under in the framework of “ENabling SafE Multi-Brand pLatooning for Europe—ENSEMBLE” Project (2018-2021); in part by the Research Council of Norway (RCN) in the framework of “Finding a Critical Speed Function Ahead of a Road Section for Vehicles in Motion—CriSp” Project (2020-2022); in part by the Swedish Innovation Agency (VINNOVA) in the framework of “Emergency Vehicle Traffic Light Pre-Emption in Cities – EPIC” Project (2020–2022); and in part by ELLIIT Strategic Research Network.

Available from: 2021-02-11 Created: 2021-02-11 Last updated: 2023-06-08Bibliographically approved

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Thunberg, JohanSidorenko, GalinaVinel, Alexey

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