Resilience of urban street network configurations under low demands

Urban street networks are subject to a variety of random disruptions. The impact of movement restrictions (e.g., one-way or left-turn restrictions) on the ability of a network to overcome these disruptions—that is, its resilience—has not been thoroughly studied. To address this gap, this paper investigates the resilience of one-way and two-way square grid street networks with and without left turns under light traffic conditions. Networks are studied using a simplified routing algorithm that can be examined analytically and a microsimulation that describes detailed vehicle dynamics. In the simplified method, routing choices are enumerated for all possible origin-destination (OD) combinations to identify how the removal of a link affects operations, both when knowledge of the disruption is and is not available at the vehicle's origin. Disruptions on two-way networks that allow left turns tend to have little impact on travel distances because of the availability of multiple shortest paths between OD pairs and the flexibility in route modification. Two-way networks that restrict left turns at intersections only have a single shortest-distance path between any OD pair and thus experience larger increases in travel distance, even when the disruption is known ahead of time. One-way networks sometimes have multiple shortest-distance routes and thus travel distances increase less than two-way network without left turns when links are disrupted. These results reveal a clear tradeoff between improved efficiency and reduced resilience for networks that have movement restrictions, and can be used as a basis to study network resilience under more congested scenarios and in more realistic network structures.

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Work Title Resilience of urban street network configurations under low demands
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Open Access
Creators
  1. Zhengyao Yu
  2. Vikash V. Gayah
License In Copyright (Rights Reserved)
Work Type Article
Publisher
  1. Transportation Research Record
Publication Date July 3, 2020
Publisher Identifier (DOI)
  1. https://doi.org/10.1177/0361198120933269
Deposited November 18, 2021

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  • Added Creator Vikash V. Gayah
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