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Abstract for presentation (Poster or Podium) with a Paper in the Conference Proceedings

Public Transport

Assessing the Impacts of Transit Signal Priority on Crash Severity

Sunday, June 16, 2024
3:00 PM - 4:15 PM ET
Room: Galleria

    Primary Author(s)

  • MA

    MD Sultan Ali, PhD

    Traffic & ITS Engineer
    CHA Consulting, Inc.
    Doral, FL, United States

    • Presenter(s)

  • MA

    MD Sultan Ali, PhD

    Traffic & ITS Engineer
    CHA Consulting, Inc.
    Doral, FL, United States

    • Co-Author(s)

  • JK

    John Kodi, Ph.D.

    Traffic & ITS Engineer
    HNTB
    Tallahassee, Florida, United States

    • Presenter(s)

  • JK

    John Kodi, Ph.D.

    Traffic & ITS Engineer
    HNTB
    Tallahassee, Florida, United States

    • Co-Author(s)

  • EM

    Enock Mwambeleko, n/a

    Graduate Research Assistant
    Florida International University
    Miami, Florida, United States

  • PA

    Priyanka Alluri, Ph.D.

    Associate Professor
    Florida International University
    Miami, Florida, United States

  • TS

    Thobias Sando, Ph.D.

    Professor
    University of North Florida
    Jacksonville, Florida, United States

    • Submitter(s)

  • MA

    MD Sultan Ali

    CHA Consulting, Inc.
    Doral, Florida, United States

Abstract:

Transit Signal Priority (TSP) is a traffic management strategy implemented in emerging smart cities to enhance the quality of service for public transit users. While its primary goal is to improve the mobility performance of transit vehicles, TSP also brings about significant safety benefits. This study used a binary Bayesian logit model with random effects, which accounts for unobserved heterogeneity, to explore the impacts of TSP on the severity of corridor-related crashes in Florida. The analysis revealed that the deployment of TSP was associated with lower crash severity. Overall, TSP reduced the likelihood of a fatal plus injury (FI) crash by 7.96%. This reduction was significant at a 95% Bayesian credible interval (BCI). The study also investigated other factors contributing to crash severity, including crash characteristics, driver characteristics, roadway geometry, and environmental factors. Specifically, distracted driving, vulnerable road users, and higher speed limit were associated with a higher risk of being involved in a FI crash. In contrast, higher Average Annual Daily Traffic (AADT) was linked to a lower risk of a FI crash. Additionally, certain crash types like rear-end crashes and sideswipe crashes were associated with a lower risk of a FI crash. These findings hold crucial implications for transportation agencies and practitioners when planning future TSP deployments. By understanding the safety benefits of TSP and considering the factors contributing to crash severity, policymakers can make informed decisions to optimize the deployment of TSP and enhance overall road safety in their regions.

Learning Objectives:

Attendees can expect to learn the following from this session:
  • Upon completion, participant will be able to have a deeper understanding on the influence of transit signal priority on crash severity
  • Upon completion, participant will be able to understand how safety analysis is conducted for transit signal priority using empirical assessment using Bayesian logit model with unobserved heterogeneity
  • Upon completion, participant will be able to understand the safety benefits of transit signal priority and the factors contributing to crash severity