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Traffic resilience quantification based on macroscopic fundamental diagrams and analysis using topological attributes

Qing-Long Lu, Wenzhe Sun, Jiannan Dai, Schmöcker, Jan-Dirk and Constantinos Antoniou

Reliability Engineering and System Safety, 2024, vol. 247, issue C

Abstract: Transportation system disruptions significantly impair transportation efficiency. This paper proposes new indicators derived from the Macroscopic Fundamental Diagram (MFD) dynamics before and after a disruption to evaluate its impact on traffic resilience. Considering that MFD is an intrinsic property of a homogeneously congested transportation network, the resilience losses due to congestion and network disruption are measured separately. The resilience loss is defined as the reduction in trip completion rate, comparing congested cases to uncongested cases or disrupted cases to undisrupted cases. The resilience loss hence also exists for an undisrupted network and is measurable by the proposed method. A Simulation of Urban MObility (SUMO) model is calibrated by real origin–destination patterns, to allow for experiments in scenarios of different demand variations and supply disruptions. Case studies are conducted in Munich, Germany and Kyoto, Japan to test the usefulness of the newly proposed indicators. We furthermore explore the relationship between resilience loss and network topological attributes such as centrality and connectivity from a variety of synthetic disruption experiments in Munich and Kyoto. We find that the resilience loss in a grid-like network as in Kyoto is less dependent on the degradation of network connectivity than in a ring-like network as in Munich.

Keywords: Traffic resilience; Macroscopic fundamental diagram; Infrastructure disruption; Traffic simulation; Network topology (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:247:y:2024:i:c:s0951832024001698

DOI: 10.1016/j.ress.2024.110095

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