A simulation study of platooning AV fleet service in shared urban environments with uncertainties

Ran Dong; Roger Woodman; Paul A. Jennings; Simon Brewerton; Stewart A. Birrell; Matthew D. Higgins

doi:10.1016/j.treng.2021.100062

A simulation study of platooning AV fleet service in shared urban environments with uncertainties

Ran Dong, Roger Woodman, Paul A. Jennings, Simon Brewerton, Stewart A. Birrell, Matthew D. Higgins

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Abstract

This paper conducts a simulation study of low-speed Autonomous Vehicles (AVs), referred to as “pods”, platooning in shared urban environments. The proposed on-demand transport service can help solve the “last mile” challenge and improve mobility for non-drivers, elderly, and disabled people. To help the industry understands the dynamic system for deployment, this paper provides a practical prospect for pod platooning without prior planning. We designed a simulation system for the new transport. Non-homogenous Poisson processes were adopted to simulate arrivals of user requests. A three-density-zone map was designed from real-world city layouts. Practical time and location patterns of user demand were used. The supervision cost reduction as a benefit of platooning was estimated. System performance and user experience were evaluated. We identified how deployment can influence platooning. We found that platooning can reduce supervision cost by approximately 20% and 14%, during peak times on weekdays and midday on weekends respectively.

Original language	English
Article number	100062
Number of pages	13
Journal	Transportation Engineering
Volume	4
Early online date	2 Mar 2021
DOIs	https://doi.org/10.1016/j.treng.2021.100062
Publication status	E-pub ahead of print - 2 Mar 2021
Externally published	Yes

Bibliographical note

This is an open access article under the CC BY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/)

Keywords

Electric Autonomous Vehicle
Platooning
Urban transport
Uncertainty
Monte Carlo Simulation

Access to Document

10.1016/j.treng.2021.100062Licence: CC BY-NC-ND

PublishedFinal published version, 2.63 MBLicence: CC BY-NC-ND

https://www.sciencedirect.com/science/article/pii/S2666691X2100018XLicence: CC BY-NC-ND

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Cite this

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title = "A simulation study of platooning AV fleet service in shared urban environments with uncertainties",

abstract = "This paper conducts a simulation study of low-speed Autonomous Vehicles (AVs), referred to as “pods”, platooning in shared urban environments. The proposed on-demand transport service can help solve the “last mile” challenge and improve mobility for non-drivers, elderly, and disabled people. To help the industry understands the dynamic system for deployment, this paper provides a practical prospect for pod platooning without prior planning. We designed a simulation system for the new transport. Non-homogenous Poisson processes were adopted to simulate arrivals of user requests. A three-density-zone map was designed from real-world city layouts. Practical time and location patterns of user demand were used. The supervision cost reduction as a benefit of platooning was estimated. System performance and user experience were evaluated. We identified how deployment can influence platooning. We found that platooning can reduce supervision cost by approximately 20% and 14%, during peak times on weekdays and midday on weekends respectively.",

keywords = "Electric Autonomous Vehicle, Platooning, Urban transport, Uncertainty, Monte Carlo Simulation",

author = "Ran Dong and Roger Woodman and Jennings, {Paul A.} and Simon Brewerton and Birrell, {Stewart A.} and Higgins, {Matthew D.}",

note = "This is an open access article under the CC BY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/) ",

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T1 - A simulation study of platooning AV fleet service in shared urban environments with uncertainties

AU - Dong, Ran

AU - Woodman, Roger

AU - Jennings, Paul A.

AU - Brewerton, Simon

AU - Birrell, Stewart A.

AU - Higgins, Matthew D.

N1 - This is an open access article under the CC BY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/)

PY - 2021/3/2

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N2 - This paper conducts a simulation study of low-speed Autonomous Vehicles (AVs), referred to as “pods”, platooning in shared urban environments. The proposed on-demand transport service can help solve the “last mile” challenge and improve mobility for non-drivers, elderly, and disabled people. To help the industry understands the dynamic system for deployment, this paper provides a practical prospect for pod platooning without prior planning. We designed a simulation system for the new transport. Non-homogenous Poisson processes were adopted to simulate arrivals of user requests. A three-density-zone map was designed from real-world city layouts. Practical time and location patterns of user demand were used. The supervision cost reduction as a benefit of platooning was estimated. System performance and user experience were evaluated. We identified how deployment can influence platooning. We found that platooning can reduce supervision cost by approximately 20% and 14%, during peak times on weekdays and midday on weekends respectively.

AB - This paper conducts a simulation study of low-speed Autonomous Vehicles (AVs), referred to as “pods”, platooning in shared urban environments. The proposed on-demand transport service can help solve the “last mile” challenge and improve mobility for non-drivers, elderly, and disabled people. To help the industry understands the dynamic system for deployment, this paper provides a practical prospect for pod platooning without prior planning. We designed a simulation system for the new transport. Non-homogenous Poisson processes were adopted to simulate arrivals of user requests. A three-density-zone map was designed from real-world city layouts. Practical time and location patterns of user demand were used. The supervision cost reduction as a benefit of platooning was estimated. System performance and user experience were evaluated. We identified how deployment can influence platooning. We found that platooning can reduce supervision cost by approximately 20% and 14%, during peak times on weekdays and midday on weekends respectively.

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KW - Monte Carlo Simulation

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