A dynamic Bayesian network model for real-time crash prediction using traffic speed conditions data
- 1 May 2015
- journal article
- Published by Elsevier BV in Transportation Research Part C: Emerging Technologies
- Vol. 54, 176-186
- https://doi.org/10.1016/j.trc.2015.03.006
Abstract
No abstract availableFunding Information
- Natural Science Foundation of China (51278362, 51422812)
- New Century Excellent Talents in University (NCET13-0425)
This publication has 32 references indexed in Scilit:
- Impact of traffic states on freeway crash involvement ratesAccident Analysis & Prevention, 2013
- Bayesian Updating Approach for Real-Time Safety Evaluation with Automatic Vehicle Identification DataTransportation Research Record: Journal of the Transportation Research Board, 2012
- Impact of traffic oscillations on freeway crash occurrencesAccident Analysis & Prevention, 2010
- Comprehensive Analysis of the Relationship Between Real-Time Traffic Surveillance Data and Rear-End Crashes on FreewaysTransportation Research Record: Journal of the Transportation Research Board, 2006
- Identifying crash propensity using specific traffic speed conditionsJournal of Safety Research, 2005
- Spatiotemporal Variation of Risk Preceding Crashes on FreewaysTransportation Research Record: Journal of the Transportation Research Board, 2005
- Split Models for Predicting Multivehicle Crashes During High-Speed and Low-Speed Operating Conditions on FreewaysTransportation Research Record: Journal of the Transportation Research Board, 2005
- Assessing Safety Benefits of Variable Speed LimitsTransportation Research Record: Journal of the Transportation Research Board, 2004
- Predicting Freeway Crashes from Loop Detector Data by Matched Case-Control Logistic RegressionTransportation Research Record: Journal of the Transportation Research Board, 2004
- Real-Time Crash Prediction Model for Application to Crash Prevention in Freeway TrafficTransportation Research Record: Journal of the Transportation Research Board, 2003