Adaptive transit scheduling to reduce rider vulnerability during heatwaves

Noam Rosenthal, Mikhail Chester, Andrew Fraser, David M. Hondula, David P. Eisenman

Research output: Contribution to journalArticlepeer-review

Abstract

Extreme heat events induced by climate change present a growing risk to transit passenger comfort and health. To reduce exposure, agencies may consider changes to schedules that reduce headways on heavily trafficked bus routes serving vulnerable populations. This paper develops a schedule optimization model to minimize heat exposure and applies it to local bus services in Phoenix, Arizona, using agent-based simulation to inform travel demand and rider characteristics. Rerouting as little as 10% of a fleet is found to reduce network-wide exposure by as much as 35% when operating at maximum fleet capacity. Outcome improvements are notably characterized by diminishing returns, owing to skewed ridership and the inverse relationship between fleet size and passenger wait time. Access to spare vehicles can also ensure significant reductions in exposure, especially under the most extreme temperatures. Rerouting, therefore, presents a low-cost, adaptable resilience strategy to protect riders from extreme heat exposure.

Original languageEnglish (US)
JournalSustainable and Resilient Infrastructure
DOIs
StateAccepted/In press - 2022

Keywords

  • agent-based model
  • Heat
  • optimization
  • public health
  • public transit

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Geography, Planning and Development
  • Building and Construction
  • Safety, Risk, Reliability and Quality

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