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A Novel Risk Indicator for Cut-In Situations
The Swedish National Road and Transport Research Institute (VTI), Linköping, Sweden.ORCID iD: 0000-0003-4951-5315
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research. RISE Viktoria, Gothenburg, Sweden.ORCID iD: 0000-0002-1043-8773
The Swedish National Road and Transport Research Institute (VTI), Linköping, Sweden.
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2020 (English)In: 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC), Piscataway, NJ: IEEE, 2020, article id 9294315Conference paper, Published paper (Refereed)
Abstract [en]

Cut-in situations occurs when a vehicle intention- ally changes lane and ends up in front of another vehicle or in-between two vehicles. In such situations, having a method to indicate the collision risk prior to making the cut-in maneuver could potentially reduce the number of sideswipe and rear end collisions caused by the cut-in maneuvers. This paper propose a new risk indicator, namely cut-in risk indicator (CRI), as a way to indicate and potentially foresee collision risks in cut-in situations. As an example use case, we applied CRI on data from a driving simulation experiment involving a manually driven vehicle and an automated platoon in a highway merging situation. We then compared the results with time-to-collision (TTC), and suggest that CRI could correctly indicate collision risks in a more effective way. CRI can be computed on all vehicles involved in the cut-in situations, not only for the vehicle that is cutting in. Making it possible for other vehicles to estimate the collision risk, for example if a cut-in from another vehicle occurs, the surrounding vehicles could be warned and have the possibility to react in order to potentially avoid or mitigate accidents. © 2020 IEEE.

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE, 2020. article id 9294315
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:hh:diva-43770DOI: 10.1109/ITSC45102.2020.9294315ISI: 000682770700139Scopus ID: 2-s2.0-85099646310ISBN: 978-1-7281-4149-7 (electronic)ISBN: 978-1-7281-4150-3 (print)OAI: oai:DiVA.org:hh-43770DiVA, id: diva2:1515907
Conference
The 23rd IEEE International Conference on Intelligent Transportation Systems, Virtual Conference, September 20 – 23, 2020
Funder
Vinnova, 2015-04881
Note

Funding: Swedish Government Agency for Innovation Systems VINNOVA through the NGEA step 2; Vehicle and Traffic Safety Centre at Chalmers (SAFER)

Available from: 2021-01-11 Created: 2021-01-11 Last updated: 2023-10-05Bibliographically approved

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Aramrattana, MaytheewatLarsson, TonyEnglund, Cristofer

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