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Transportation network redundancy: Complementary measures and computational methods

delete2018-08-01
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X
Xiangdong Xu
A
Anthony Chen *
S
Sarawut Jansuwan
杨超 cover
杨超 (Chao Yang)
S
Seungkyu Ryu
DOI:10.1016/j.trb.2018.05.014delete
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Abstract

Abstract

En 中文
Redundancy is vital for transportation networks to provide utility to users during disastrous events. In this paper, we develop two network-based measures for systematically characterizing the redundancy of transportation networks: travel alternative diversity and network spare capacity. Specifically, the travel alternative diversity dimension is to evaluate the existence of multiple modes and effective routes available for travelers or the number of effective connections between a specific origin-destination pair. The network spare capacity dimension is to quantify the network-wide residual capacity with an explicit consideration of travelers' mode and route choice behaviors as well as congestion effect. They can address two fundamental questions in the pre-disaster transportation system evaluation and planning, i.e., how many effective redundant alternatives are there for travelers in the normal or disruptive event? and how much redundant capacity does the network have? To implement the two measures in practice, computational methods are provided to evaluate the network redundancy. Numerical examples are also presented to demonstrate the features of the two redundancy measures as well as the applicability of the computational methods. The analysis results reveal that the two measures have different characterizations on network redundancy from different perspectives, and they can complement each other by providing meaningful information to both travelers and planners. (C) 2018 Elsevier Ltd. All rights reserved.
Keywords:
Redundancy
Travel alternative diversity
Network spare capacity
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Journal

Transportation Research Part B-Methodological cover
Transportation Research Part B-Methodological
IF:
6.3
Papers:
3.5K
Citations:
1.9W

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national institutes of health (nih) - usa
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nih national institute on drug abuse (nida)
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tongji university
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