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Modelling autonomous vehicle parking: An agent-based simulation approach

Lookup NU author(s): Professor Phil BlytheORCiD, Dr Shuo LiORCiD

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© 2024 The Authors. IET Intelligent Transport Systems published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.Autonomous vehicles (AVs) present a paradigm shift in addressing conventional parking challenges. Unlike human-driven vehicles, AVs can strategically park or cruise until summoned by users. Utilizing utility theory, the parking decision-making processes of AVs users are explored, taking into account constraints related to both cost and time. An agent-based simulation approach is adopted to construct an AV parking model, reflecting the complex dynamics of the parking decision process in the real world, where each user's choice has a ripple effect on traffic conditions, consequently affecting the feasible options for other users. The simulation experiments indicate that 11.50% of AVs gravitate towards parking lots near their destinations, while over 50% of AVs avoid public parking amenities altogether. This trend towards minimizing individual parking costs prompts AVs to undertake extended empty cruising, resulting in a significant increase of 48.18% in total vehicle mileage. Moreover, the pricing structure across various parking facilities and management dictates the parking preferences of AVs, establishing a nuanced trade-off between parking expenses and proximity for these vehicles.


Publication metadata

Author(s): Li W, Jia Y, Ji Y, Blythe P, Li S

Publication type: Article

Publication status: Published

Journal: IET Intelligent Transport Systems

Year: 2024

Pages: epub ahead of print

Online publication date: 12/03/2024

Acceptance date: 01/03/2024

Date deposited: 02/05/2024

ISSN (print): 1751-956X

ISSN (electronic): 1751-9578

Publisher: John Wiley and Sons Inc

URL: https://doi.org/10.1049/itr2.12506

DOI: 10.1049/itr2.12506

Data Access Statement: The data that support the findings of this study are available from the corresponding author upon reasonable request.


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Funding

Funder referenceFunder name
the Fundamental Research Funds for the Central Universities under Grant 2242020K40063
the Postgraduate Research and Practice Innovation Program of Jiangsu Province under Grant KYCX20_0137

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