Investigating the Long-Term Impact of Disruptions on Passenger Travel Behavior Using AFC Data

A Case Study of Washington D.C. Metro Network

Master Thesis (2024)
Author(s)

F. Tavakoli (TU Delft - Civil Engineering & Geosciences)

Contributor(s)

O. Cats – Graduation committee member (TU Delft - Transport, Mobility and Logistics)

Y. Zhu – Graduation committee member (TU Delft - Transport, Mobility and Logistics)

M. Kroesen – Graduation committee member (TU Delft - Transport and Logistics)

Jie Gao – Graduation committee member (TU Delft - Transport, Mobility and Logistics)

Faculty
Civil Engineering & Geosciences
More Info
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Publication Year
2024
Language
English
Graduation Date
19-08-2024
Awarding Institution
Delft University of Technology
Programme
['Transport, Infrastructure and Logistics']
Faculty
Civil Engineering & Geosciences
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Abstract

Disruptions in urban public transport networks significantly impact urban mobility, causing inconveniences for passengers, economic losses, and vulnerabilities in transit systems. Major disruptions may lead some passengers to permanently switch to alternative modes like cars, even after the disruptions resolve, potentially worsening congestion and environmental issues. While the immediate impact of disruptions on behavior has been extensively studied, there is limited research on the long-term effects, often restricted to qualitative methods. This study aims to address this gap by proposing a framework to investigate the prolonged effects of public transport disruptions on passenger travel behavior using smart card data. A mixture latent Markov model is used to track passenger behavior from the pre-disruption to the post-disruption period. This framework identifies travel patterns and tracks how passengers transition between these patterns over time, thus inferring the impact of disruptions on behavior. Each passenger is assigned a mobility style that reflects their general travel attitude, such as those who do not change their behavior. The results from our case study reveal that the impact of the disruption was not as substantial as anticipated, with a high proportion of passengers maintaining their behavior.

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