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Title:

Intersection Auctions and Reservation-Based Control in Dynamic Traffic Assignment

Accession Number:

01556576

Record Type:

Component

Availability:

Transportation Research Board Business Office

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Washington, DC 20001 United States

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Order URL: http://worldcat.org/isbn/9780309369473

Abstract:

Autonomous vehicle (AV) technology is maturing, and AVs are being test-driven on public roads. A promising intersection control policy, tile-based reservation (TBR), proposed by Dresner and Stone in 2004, could improve intersection capacity beyond the capabilities of optimized traffic signals. Although TBR has been studied in several microsimulation models, it has yet to be analyzed under user equilibrium behavior. In this study, TBR was modeled in the dynamic traffic assignment to draw on the extensive literature on vehicle routing behaviors. With the proposed model, TBR can be computationally simulated on large city networks, with the goal of solving the traffic assignment problem. TBR also arbitrarily prioritizes vehicle movement, and high-value-of-time travelers may be able to gain priority through intersection auctions, as suggested by the literature. An in-depth study of simple intersection auctions found that much of the benefit (over first-come, first-served prioritization) resulted from the randomizing effect of auctions giving larger queues of vehicles greater shares of the intersection capacity.

Monograph Title:

Network Modeling, Volume 1

Monograph Accession #:

01593848

Report/Paper Numbers:

15-2149

Language:

English

Authors:

Levin, Michael W
Boyles, Stephen D

Pagination:

pp 35–44

Publication Date:

2015

Serial:

Transportation Research Record: Journal of the Transportation Research Board

Issue Number: 2497
Publisher: Transportation Research Board
ISSN: 0361-1981

ISBN:

9780309369473

Media Type:

Print

Features:

Figures (8) ; References (24)

Subject Areas:

Highways; Operations and Traffic Management; Planning and Forecasting; I73: Traffic Control

Files:

TRIS, TRB, ATRI

Created Date:

Dec 30 2014 12:46PM

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