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Modelling the impact of context in real-world highway pull-out dynamics to inform acceptable path planning of automated vehicles

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posted on 2024-01-05, 16:52 authored by Anna-Maria Sourelli, Ruth Welsh, Pete Thomas
Growing research attention is focusing on Automated Vehicle (AV) technologies, promising significant safety benefits. An in-depth understanding of human driving will play an important role in determining the most acceptable AV behaviour, supporting passenger comfort and thus the adoption of the technology, but also the optimal prediction of the behaviour of the surrounding traffic. The current study examined 1740 real-world motorway pull-out manoeuvres (pull-out distance, speed differential with the leading vehicle, manoeuvre duration, pull-out comfort zone) under different conditions. The results highlighted the significant impact of the surrounding traffic and the driving characteristics on or before the manoeuvre initiation point, which reflected the overtaking strategy selected. The findings can inform the design of automated overtaking systems that resemble human driving and thus encourage their uptake; in addition, they can assist the intention prediction for lane keeping assistance systems in order to optimise the system’s response to cutting in and pull-out manoeuvres.<p></p>

Funding

Loughborough University

History

School

  • Design and Creative Arts

Department

  • Design

Published in

Transportmetrica A: Transport Science

Volume

20

Issue

1

Pages

1 - 21

Publisher

Taylor & Francis

Version

  • VoR (Version of Record)

Rights holder

© The Authors

Publisher statement

This is an Open Access Article. It is published by Taylor & Francis under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence (CC BY-NC-ND 4.0). Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

2022-02-14

Publication date

2022-03-07

Copyright date

2022

ISSN

2324-9935

eISSN

2324-9943

Language

  • en

Depositor

Anna-Maria Sourelli. Deposit date: 8 March 2022

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