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

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

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

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.

Original languageEnglish
Article number110095
JournalReliability Engineering and System Safety
Volume247
DOIs
StatePublished - Jul 2024

Keywords

  • Infrastructure disruption
  • Macroscopic fundamental diagram
  • Network topology
  • Traffic resilience
  • Traffic simulation

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