Quantifying the Impact of Automated Vehicles on Traffic

Conference paper (2023)

Authors

Martin Sigl BMW Group
Binnert Prins BMW Group
Christoph Schutz BMW Group
Sebastian Wagner BMW Group
F. Schulte Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering
Daniel Watzenig Graz University of Technology, Virtual Vehicle Research GmbH
Research Group
Transport Engineering and Logistics (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2023 Martin Sigl, Binnert Prins, Christoph Schutz, Sebastian Wagner, F. Schulte, Daniel Watzenig
DOI: https://doi.org/10.1109/IAVVC57316.2023.10328115
Autonomous Vehicles Automated Driving Impact Analysis
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Published Date

2023

Language

English

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Marine and Transport Technology

Research Group

Transport Engineering and Logistics

Abstract

One of the major challenges in the development of Automated Driving is its assessment. It is expected that Automated Vehicles behave differently than human drivers. Therefore, mixed human-robot traffic will yield different and new driving situations as human-only traffic. It is important to know how this mixed traffic will change the composition of traffic situations to be able to quantify the impact Automated Vehicles will have on everyday traffic. This paper presents a methodology on how to find metrics that quantify traffic in order to detect changes in the traffic space that will come with the introduction of Automated Vehicles. Additionally, this methodology provides tools to help with the validation of virtual testing platforms such as simulation.