Multi-Level Crash Prediction Models Considering Influence of Adjacent Zonal Attributes

This study investigates factors affecting accidents across transport facilities and modes, using micro and macro levels variables simultaneously while accounting for the influence of adjacent zones on the accidents occurrence in a zone. To this end, 15968 accidents in 96 traffic analysis zones of Tehran were analyzed. Adverting to the multi-level structure of accidents data, the present study adopts a multilevel model for its modeling processes. The effects of the adjacent zones on the accidents which have occurred in one zone were assessed using the independent variables obtained from the zones adjacent to that specific zone. A Negative Binomial (NB) model was also developed, and results show that the multilevel model that considers the effect of adjacent zones shows a better performance compared to the multilevel model that does not consider the adjacent zones’ effect and NB model. Moreover, the final models show that at intersections and road segments, the significant independent variables are different for each mode of transport. Adopting a comprehensive approach to incorporate a multi-level, multi-resolution (micro/macro) model accounting for adjacent zones’ influence on multi-mode, multi-segment accidents is the contribution of this paper to accident studies.

Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden.