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

Multi-Level Model Adjacent Zone Crash Frequency Micro/Macro Variable.

Authors

  • Nemat Soltani
    Soltani.nemat@gmail.com
    Ph.D. Candidate, Tarahan Parseh Transportation Research Institute, Tehran, Iran.
  • Mahmoud Saffarzadeh Professor, Department of Civil & Environmental Engineering, Tarbiat Modares University, Tehran, Iran.
  • Ali Naderan Assistant Professor, Department of Civil Engineering, Islamic Azad University, Tehran Science and Research Branch, Tehran, Iran

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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.