Imperial College London
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Dr Marc Stettler

Faculty of Engineering, Department of Civil and Environmental Engineering

Reader in Transport and the Environment
 
 
 
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Contact

 

+44 (0)20 7594 2094m.stettler Website

 
 
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Location

 

614Skempton BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Ye:2020:10.1109/ITSC45102.2020.9294527,
author = {Ye, Q and Stebbins, SM and Feng, Y and Candela, E and Stettler, M and Angeloudis, P},
doi = {10.1109/ITSC45102.2020.9294527},
pages = {1--7},
publisher = {IEEE},
title = {Intelligent management of on-street parking provision for the autonomous vehicles era},
url = {http://dx.doi.org/10.1109/ITSC45102.2020.9294527},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - The increasing degree of connectivity between vehicles and infrastructure, and the impending deployment of autonomous vehicles (AV) in urban streets, presents unique opportunities and challenges regarding the on-street parking provision for AVs. This study develops a novel simulation-optimisation approach for intelligent curbside management, based on a metaheuristic technique. The hybrid method balances curb lanes for driving or parking, aiming to minimise the average traffic delay. The model is tested using an idealised grid layout with a range of flow rates and parking policies. Results demonstrate delay decreased by 9%-27% from the benchmark case. Additionally, the traffic delay distribution shows the trade-offs between expanding road capacity and minimising traffic demand through curb management, indicating the interplay between curb parking and traffic management in the AV era.
AU  - Ye,Q
AU  - Stebbins,SM
AU  - Feng,Y
AU  - Candela,E
AU  - Stettler,M
AU  - Angeloudis,P
DO  - 10.1109/ITSC45102.2020.9294527
EP  - 7
PB  - IEEE
PY  - 2020///
SN  - 2153-0009
SP  - 1
TI  - Intelligent management of on-street parking provision for the autonomous vehicles era
UR  - http://dx.doi.org/10.1109/ITSC45102.2020.9294527
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000682770702031&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://ieeexplore.ieee.org/document/9294527
UR  - http://hdl.handle.net/10044/1/94213
ER  -
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