Associating Incident Clearance Duration with Freeway Segment Types Using Hierarchical Bayesian Survival Model
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 149, Issue 1
Abstract
Traffic incidents represent nonrecurring events that have long been found to deteriorate traffic operations and safety. Studies agree that quick incident clearance would translate into substantial savings for the motoring public. However, many factors influence how quickly an incident can be cleared. This paper investigated the influence of the incident location on incident clearance duration using a hierarchical Bayesian survival model. The study presented a statistical approach to examine disparities in incident clearance duration on different freeway segments (i.e., basic, merge, diverge, weaving, on-ramp, and off-ramp sections). In the analysis, data from 58,167 incidents that occurred on freeways in Jacksonville, Florida, for the years 2014–2017 were analyzed. The Bayesian hypothesis testing revealed credible differences in incident clearance durations among most freeway segment pairs. The model results indicated that basic freeway segments had the longest incident clearance durations, followed by diverge segments and off-ramps. Incidents that were crashes, were severe, resulted in shoulder blockage, occurred on weekends, and occurred on segments with high traffic volumes took significantly longer time to be cleared. The study findings could help practitioners strategically position and allocate appropriate incident response resources along the freeway corridors. Practitioners could consider depots along longer basic freeway segments and diverge segments to enable the quick arrival of incident response teams.
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Data Availability Statement
All data used during the study were provided by the Florida Department of Transportation. Direct requests for these materials may be made to the provider.
Acknowledgments
The authors thank the Florida Department of Transportation for providing access to the SunGuide incident data. The opinions, findings, and conclusions expressed in this publication are those of the author(s) and not necessarily those of the Florida Department of Transportation.
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Journal of Transportation Engineering, Part A: Systems
Volume 149 • Issue 1 • January 2023
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© 2022 American Society of Civil Engineers.
History
Received: Jan 4, 2022
Accepted: Aug 11, 2022
Published online: Oct 21, 2022
Published in print: Jan 1, 2023
Discussion open until: Mar 21, 2023
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