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Research Papers: Design Automation

Autonomous Electric Vehicle Sharing System Design

[+] Author and Article Information
Namwoo Kang

Assistant Professor
Mem. ASME
K-School,
Korea Advanced Institute of Science and
Technology (KAIST),
Daejeon 34141, South Korea
e-mail: nwkang@kaist.ac.kr

Fred M. Feinberg

Professor
Ross School of Business,
Department of Statistics,
University of Michigan,
Ann Arbor, MI 48109
e-mail: feinf@umich.edu

Panos Y. Papalambros

Professor
Fellow ASME
Optimal Design Laboratory,
Department of Mechanical Engineering,
University of Michigan,
Ann Arbor, MI 48109
e-mail: pyp@umich.edu

1Corresponding author. Most of the work was done when the author was in the University of Michigan as a research fellow.

Contributed by the Design Automation Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received March 26, 2016; final manuscript received August 11, 2016; published online October 11, 2016. Assoc. Editor: Christopher Mattson.

J. Mech. Des 139(1), 011402 (Oct 11, 2016) (10 pages) Paper No: MD-16-1244; doi: 10.1115/1.4034471 History: Received March 26, 2016; Revised August 11, 2016

Car sharing services promise “green” transportation systems. Two vehicle technologies offer marketable, sustainable sharing: autonomous vehicles (AVs) eliminate customer requirements for car pick-up and return, and battery electric vehicles entail zero emissions. Designing an autonomous electric vehicle (AEV) fleet must account for the relationships among fleet operations, charging station (CS) operations, electric powertrain performance, and consumer demand. This paper presents a system design optimization framework integrating four subsystem problems: fleet size and assignment schedule; number and locations of charging stations; vehicle powertrain requirements; and service fees. We also compare an AEV service and autonomous vehicle (AV) service with gasoline engines. A case study for an autonomous fleet operating in Ann Arbor, MI, is used to examine AEV and AV sharing systems profitability and feasibility for a variety of market scenarios. The results provide practical insights for service system decision makers.

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Figures

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Fig. 1

AEV-sharing system operation

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Fig. 2

System design framework

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Fig. 3

AEV fleet assignment simulation model

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Fig. 4

Wait time simulation results

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Fig. 5

Candidates for charging station locations [21]

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Fig. 6

Engineering simulation model [15]

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Fig. 7

FTP-75 driving cycle [28]

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Fig. 8

Cost comparison between AEV and AV services

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Fig. 9

Parametric study for fuel cost

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