Agent-Based Framework for Self-Organization of Collective and Autonomous Shuttle Fleets

Abstract

The mobility of people is at the center of transportation planning and decision-making of the cities of the future. In order to accelerate the transition to zero-emissions and to maximize air quality benefits, smart cities are prioritizing walking, cycling, shared mobility services and public transport over the use of private cars. Extensive progress has been made in autonomous and electric cars. Autonomous Vehicles (AV) are increasingly capable of moving without full control of humans, automating some aspects of driving, such as steering or braking. For these reasons, cities are investing in the infrastructure and technology needed to support connected, multi-modal transit networks that include shared electric Autonomous Vehicles (AV). The relationship between traditional public transport and new mobility services is in the spotlight and need to be rethought. This article proposes an agent-based simulation framework that allows for the creation and simulation of mobility scenarios to investigate the impact of new mobility modes on a city daily life. It lets traffic planners explore the cooperative integration of AV using a decentralized control approach. A prototype has been implemented and validated with data of the city of Trento.

Publication DOI: https://doi.org/10.1109/TITS.2020.3021592
Divisions: ?? 50811700Jl ??
College of Engineering & Physical Sciences
College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
Funding Information: Manuscript received May 31, 2020; revised August 1, 2020; accepted August 13, 2020. Date of publication September 16, 2020; date of current version June 2, 2021. This work was supported in part by the Leverhulme Trust under Grant RF-2019-548/9 and in part
Additional Information: © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Funding: This work was supported in part by the Leverhulme Trust under Grant RF-2019-548/9 and in part by EPSRC under Grant EP/T017627/1.
Uncontrolled Keywords: agent-based simulation,autonomous shuttles,self-organization,Transportation planning,Automotive Engineering,Mechanical Engineering,Computer Science Applications
Publication ISSN: 1558-0016
Last Modified: 14 May 2024 07:25
Date Deposited: 15 Jul 2022 12:23
Full Text Link: https://arxiv.o ... /2104.07494.pdf
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
https://ieeexpl ... ocument/9199130 (Publisher URL)
PURE Output Type: Article
Published Date: 2021-06-01
Published Online Date: 2020-09-16
Accepted Date: 2020-08-13
Authors: Bucchiarone, Antonio
De Sanctis, Martina
Bencomo, Nelly (ORCID Profile 0000-0001-6895-1636)

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