Safety Evaluation of High-Occupancy Toll Facilities Using Bayesian Networks
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 147, Issue 5
Abstract
High-occupancy toll (HOT) lanes have increasingly been adopted as a strategy to reduce congestion. While numerous studies have focused on the operations of HOT facilities, little is known about their safety performance. This study used a Bayesian network model to evaluate the safety performance of HOT facilities by identifying factors contributing to single-vehicle (SV) and multiple-vehicle (MV) crashes at these facilities. The study utilized 3 years (2012–2014) of data from four HOT facilities in California. Concrete barrier separation, wet road surface condition, nighttime condition, and weekend are major contributing factors for SV crashes. MV crashes are associated with pylon separation, weekdays, and daytime conditions. The maximum possible probability (79%) of a SV crash is expected to occur over the weekend, during nighttime, and on a wet road surface located in a rolling/mountainous terrain having double solid white line separation. Meanwhile, the maximum probability (93%) of a MV crash is expected to occur over the weekend, during the daytime, and on a dry road surface located in rolling/mountainous terrain having pylon separation. The study results can assist transportation officials in implementing policies that will improve the safety performance of HOT facilities.
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Data Availability Statement
Some or all data, models, or code used during the study were provided by a third party. Direct requests for these materials may be made to the provider as indicated in the acknowledgments.
Acknowledgments
The authors would like to acknowledge the financial support of a Florida International University Dissertation Year Fellowship. The authors would also like to thank HSIS for providing the data used to conduct this study.
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© 2021 American Society of Civil Engineers.
History
Received: Apr 2, 2020
Accepted: Jan 6, 2021
Published online: Feb 26, 2021
Published in print: May 1, 2021
Discussion open until: Jul 26, 2021
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