A collision between a truck and an overpass bridge on an interstate highway is rare but can be catastrophic, especially if the bridge involved was designed and built in the early interstate highway era. Such collisions highlight the importance of developing a systematic and scientific method for evaluating at-risk bridges. The findings of this research offer a method for screening the safety risk of highway bridges and identifying bridges that require further review. A risk-based approach has been developed for this study from statistical models, probabilistic theories, and a comprehensive data set. Data include a five-year history of run-off-road (ROR) truck crashes, highway geometric characteristics, and traffic and weather information. The random coefficient Poisson model was used to model truck crashes so that data heterogeneity among highway segments could be captured. Monte Carlo simulation was employed to estimate the collision hazard envelope, given the uncertainties of truck size, encroachment, and vehicle orientation angle. Finally, collision risk was calculated for each bridge bent, and the maximum value was considered as the bridge collision risk. A risk analysis can effectively model rare events when there are uncertainties. Moreover, the bent-specific predictive method improves collision estimate accuracy because the impact is usually between the truck and the bridge bent.
Predicting Collision Risk between Trucks and Interstate Overpasses
Journal of Transportation Engineering ; 142 , 8
2016-03-21
Article (Journal)
Electronic Resource
Unknown
Predicting Collision Risk between Trucks and Interstate Overpasses
British Library Online Contents | 2016
|Predicting Collision Risk between Trucks and Interstate Overpasses
Online Contents | 2016
|Predicting Collision Risk between Trucks and Interstate Overpasses
Online Contents | 2016
|Predicting Collision Risk between Trucks and Interstate Overpasses
Online Contents | 2016
|Evaluation of Truck Impact Hazards for Interstate Overpasses
Transportation Research Record | 2014
|