Multiyear Pattern Discovery and Policy Implications of Transit Bus Involved Fatal Crashes

Abstract Fatal transit bus crashes remain a significant safety concern in urban transportation systems, with buses operating in complex, high-risk environments where interactions with pedestrians, cyclists, and other vehicles are frequent. This study seeks to identify the key factors contributing to these fatal incidents using Cluster Correspondence Analysis (CCA), applied to data from the Fatality Analysis Reporting System (FARS). By analyzing crash patterns over multiple years, the study uncovered distinct crash characteristics related to intersection-related conflicts, high-speed roadways, non-motorist involvement, and inadequate traffic control. The findings highlighted the crucial role of roadway design, including the presence of unprotected medians and the lack of traffic control devices, in increasing crash severity. In response to these patterns, the study proposes a series of policy recommendations aimed at improving road infrastructure, enhancing traffic management systems, and promoting safer driving behaviors. These policy measures are designed to reduce the risk of fatal crashes involving transit buses and to ensure safer streets for all road users. The insights provided in this study offered a comprehensive foundation for future transit safety strategies and policy development.

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Publication Details

Journal
Data Science for Transportation
Published
2026-10-15
DOI
https://doi.org/10.1007/s42421-026-00180-6
Primary Topic
Traffic and Road Safety
Type
article
Field-Weighted Citation Impact
0.00
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article

Multiyear Pattern Discovery and Policy Implications of Transit Bus Involved Fatal Crashes

Subasish Das, Sharif Ahmed Rafat, Tausif Islam Chowdhury
Data Science for Transportation
Traffic and Road Safety
article

Multiyear Pattern Discovery and Policy Implications of Transit Bus Involved Fatal Crashes

Subasish Das, Sharif Ahmed Rafat, Tausif Islam Chowdhury
article en

Abstract

Abstract Fatal transit bus crashes remain a significant safety concern in urban transportation systems, with buses operating in complex, high-risk environments where interactions with pedestrians, cyclists, and other vehicles are frequent. This study seeks to identify the key factors contributing to these fatal incidents using Cluster Correspondence Analysis (CCA), applied to data from the Fatality Analysis Reporting System (FARS). By analyzing crash patterns over multiple years, the study uncovered distinct crash characteristics related to intersection-related conflicts, high-speed roadways, non-motorist involvement, and inadequate traffic control. The findings highlighted the crucial role of roadway design, including the presence of unprotected medians and the lack of traffic control devices, in increasing crash severity. In response to these patterns, the study proposes a series of policy recommendations aimed at improving road infrastructure, enhancing traffic management systems, and promoting safer driving behaviors. These policy measures are designed to reduce the risk of fatal crashes involving transit buses and to ensure safer streets for all road users. The insights provided in this study offered a comprehensive foundation for future transit safety strategies and policy development.

Data Science for TransportationVol. 8(3)
Texas State University (US)
Sustainable cities and communities, Industry, innovation and infrastructure, Good health and well-being
Openalex Percentile: Top 13%
Traffic and Road Safety
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