Future Crash Configurations: Analysis of the Impact of Future Vehicles in Mixed Traffic

Within the EU-funded SALIENT project (https://www.salient-project.eu), an analysis of crash configurations of new and future vehicle fleets (including heavier SUV-type vehicles and autonomous vehicles) has been developed.The future crash scenarios identified will be translated into relevant scenarios for further simulations and crash tests. The work laid out in this paper contains the results of a detailed literature and state-of-the-art review and data analysis of relevant international datasets, to then propose considerations for future crash configurations and scenarios. These considerations are explored in detail real-world data of crashes involving CCAM and automated vehicles. The results of this research aim to serve as a basis for a safe transition from today’s user-driven vehicles to SAVs (semi-autonomous vehicles) and AVs (autonomous vehicles) in mixed traffic, to maximise compatibility between vehicles.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-08-12
DOI
https://doi.org/10.5281/zenodo.13305842
Primary Topic
Autonomous Vehicle Technology and Safety
Type
article
Field-Weighted Citation Impact
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article

Future Crash Configurations: Analysis of the Impact of Future Vehicles in Mixed Traffic

Zenodo (CERN European Organization for Nuclear Research)
Autonomous Vehicle Technology and Safety
article

Future Crash Configurations: Analysis of the Impact of Future Vehicles in Mixed Traffic

article en

Abstract

Within the EU-funded SALIENT project (https://www.salient-project.eu), an analysis of crash configurations of new and future vehicle fleets (including heavier SUV-type vehicles and autonomous vehicles) has been developed.The future crash scenarios identified will be translated into relevant scenarios for further simulations and crash tests. The work laid out in this paper contains the results of a detailed literature and state-of-the-art review and data analysis of relevant international datasets, to then propose considerations for future crash configurations and scenarios. These considerations are explored in detail real-world data of crashes involving CCAM and automated vehicles. The results of this research aim to serve as a basis for a safe transition from today’s user-driven vehicles to SAVs (semi-autonomous vehicles) and AVs (autonomous vehicles) in mixed traffic, to maximise compatibility between vehicles.

Zenodo (CERN European Organization for Nuclear Research)
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Autonomous Vehicle Technology and Safety
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