Journal
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
Volume 38, Issue -, Pages 167-176Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.trc.2013.11.020
Keywords
Real-time crash risk assessment; Spatial and temporal transferability; Bayesian updating; Freeway; Safety
Categories
Funding
- China's National Key Basic Research Program [2012CB725400]
- National Natural Science Foundation of China [51322810, 50908050]
- Scientific Research Foundation of Graduate School of Southeast University
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This study aimed to improve the spatial and temporal transferability of the real-time crash risk prediction models by using the Bayesian updating approach. Data from California's I-880N freeway in 2002 and 2009 and the I-5N freeway in 2009 were used. The crash risk models for these three datasets are quite different from each other. The model parameters do not remain stable over time or space. The transferability evaluation results show that the crash risk models cannot be directly transferred across time and space. The updating results indicate that the Bayesian updating approach is effective in improving both spatial and temporal transferability even when new data are limited. The predictive performance of the updated model increases with an increase in the sample size of the new data. In addition, when limited new data are available, updating an existing model is better than developing a model using the limited new data. (C) 2013 Elsevier Ltd. All rights reserved.
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