Skip to main navigation Skip to search Skip to main content

How Random Incidents Affect Travel-Time Distributions

  • Melike Baykal-Gursoy
  • , Andrew Reed Benton
  • , Pedro Gerum
  • , Marcelo Figueroa Candia
  • Rutgers University
  • Boston Consulting Group Inc.

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

We present a novel analytical model to approximate the travel-time distribution of vehicles traversing a freeway corridor that experiences random quality of service degradations due to non-recurrent incidents. The proposed model derives the generating function of travel times in closed-form using clearance time, incident frequency and severity, and other ordinary traffic characteristics. We validate the model using data from a freeway corridor where weather events and traffic accidents serve as the principal causes of service degradation. The resulting model is equivalent in performance to widely used methodologies while uniquely providing a clear connection on how incidents affect travel time distribution. With this connection, the model readily yields travel time reliability measures for alternative roadway behaviors, providing crucial information for long-term planning.
Original languageEnglish
Pages (from-to)13000-13010
Number of pages11
JournalIEEE Transactions on Intelligent Transportation Systems
Volume23
Issue number8
DOIs
StatePublished - Aug 1 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Markov modulated service
  • Random incidents
  • Stochastic models
  • Travel time reliability

Cite this