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This content will become publicly available on February 22, 2023

Title: Adaptive transit scheduling to reduce rider vulnerability during heatwaves
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.
Authors:
; ; ; ;
Award ID(s):
1934933 1635490 1931324 1444755
Publication Date:
NSF-PAR ID:
10317788
Journal Name:
Sustainable and Resilient Infrastructure
ISSN:
2378-9689
Sponsoring Org:
National Science Foundation
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