Traditionally, crash frequency analyses have been undertaken at the macro- and micro-levels, independently. This study proposes a Bayesian integrated spatial crash frequency model, which links the crash counts of macro- and micro-levels based on the spatial interaction. In addition, the proposed model considers the spatial autocorrelation of the different types of road entities (i.e. segments and intersections) at the micro-level with a joint structure. The modelling results indicated that the integrated model can provide better model performance for estimating macro- and micro-level crash counts, which validates the concept of integrating the models for the two levels. Also, the integrated model could simultaneously identify both macro- and micro-level factors contributing to the crash occurrence. Subsequently, a novel hotspot identification method was suggested, which enables us to detect hotspots for both macro- and micro-levels with comprehensive information from the two levels.
Integrating macro- and micro-level safety analyses: a Bayesian approach incorporating spatial interaction
Transportmetrica A: Transport Science ; 15 , 2 ; 285-306
2019-11-29
22 pages
Article (Journal)
Electronic Resource
English
Integrating Micro and Macro Models: Mutual Benefits
British Library Conference Proceedings | 1995
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