Simulation analysis of urban network performance under link disruptions: Impacts of information provisions in different street configurations

Zhengyao Yu, Vikash V. Gayah

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

This study uses aggregated network-level operation metrics to examine the performance of three street network configurations, namely two-way (TW), two-way without left turns (TWL), and one-way networks (OW), under disruptive events in the network. Overall, a TWL network is found to be the most efficient both with and without disruptions. When there is no disruption, a TWL network shows a comparable trip completion rate as a TW network with turn pockets at intersection. Although the mean travel distance in the TWL network is about 30% higher than the TW network, its mean trip time is only 16% higher due to lower intersection delays. When disruptions take place, only TWL network is found to accommodate the most challenging ones in the central area due to its higher intersection efficiency and more evenly distributed traffic inside. The study also examined the impacts of various ITS-related strategies to provide drivers with advanced information on the disruption to mitigate its negative effects. The results revealed that providing information on disruptions that occur outside the most congested areas when vehicles start their trip might actually reduce overall network performance, since doing so may cause vehicles to reroute through heavily congested areas. For disruptions in the central region of the network, alerting drivers just one or two blocks upstream of the disruption can achieve similar delay reductions to broadcasting the disruption to 75% of road users.

Original languageEnglish (US)
Pages (from-to)471-487
Number of pages17
JournalJournal of Intelligent Transportation Systems: Technology, Planning, and Operations
Volume27
Issue number4
DOIs
StatePublished - 2023

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Information Systems
  • Automotive Engineering
  • Aerospace Engineering
  • Computer Science Applications
  • Applied Mathematics

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