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Title:

Routing Policy Choice Set Generation in Stochastic Time-Dependent Networks: Case Studies for Stockholm, Sweden, and Singapore

Accession Number:

01514937

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/9780309295581

Abstract:

Transportation systems are inherently uncertain because of random disruptions; nevertheless, real-time information can help travelers make better route choices under such disruptions. The first revealed-preference study of routing policy choice is presented. A "routing policy" is defined as a decision rule applied at each link that maps possible realized traffic conditions to decisions to be made on the link next. The policy represents a traveler’s ability to incorporate real-time information not yet available at the time of decision. Two case studies are conducted in Stockholm, Sweden, and in Singapore. Data for the underlying stochastic time-dependent network are generated from taxi GPS traces through map-matching and nonparametric link travel time estimation. An efficient algorithm to find the optimal routing policy in large-scale networks is first presented, which is a building block of any routing policy choice set generation method. The routing policy choice sets are then generated by link elimination and simulation. The generated choice sets are first evaluated on the basis of whether they include the observed traces on a specific day, or coverage. The sets are then evaluated on the basis of "adaptiveness," defined as the capability of a routing policy to be realized as different paths over different days. A combination of link elimination and simulation methods yields satisfactory coverage. The comparison with a path choice set benchmark also suggests that a routing policy choice set could potentially provide better coverage and capture the adaptive nature of route choice.

Monograph Accession #:

01557688

Report/Paper Numbers:

14-1732

Language:

English

Authors:

Ding, Jing
Gao, Song
Jenelius, Erik
Rahmani, Mahmood
Huang, He
Ma, Long
Pereira, Francisco C
Ben-Akiva, Moshe

Pagination:

pp 76–86

Publication Date:

2014

Serial:

Transportation Research Record: Journal of the Transportation Research Board

Issue Number: 2466
Publisher: Transportation Research Board
ISSN: 0361-1981

ISBN:

9780309295581

Media Type:

Print

Features:

Figures (4) ; Maps; References (41) ; Tables (2)

Geographic Terms:

Subject Areas:

Highways; Planning and Forecasting; I72: Traffic and Transport Planning

Files:

TRIS, TRB, ATRI

Created Date:

Jan 27 2014 2:37PM

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