TY  - JOUR
PY  - 2019//
TI  - Integrating macro- and micro-level safety analyses: a Bayesian approach incorporating spatial interaction
JO  - Transportmetrica A: transport science
A1  - Cai, Qing
A1  - Abdel-Aty, Mohamed
A1  - Lee, Jaeyoung
A1  - Huang, Helai
SP  - 285
EP  - 306
VL  - 15
IS  - 2
N2  - 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.<p />  <p>Language: en</p>
LA  - en
SN  - 2324-9935
UR  - http://dx.doi.org/10.1080/23249935.2018.1471752
ID  - ref1
ER  -