Macro-Level Pedestrian And Bicycle Crash Analysis: Incorporating Spatial Spillover Effects In Dual State Count Models

Keywords

Dual-state models; Hurdle negative binomial models; Macro-level crash analysis; Pedestrian and bicycle crashes; Spatial independent variables; Zero-inflated negative binomial

Abstract

This study attempts to explore the viability of dual-state models (i.e., zero-inflated and hurdle models) for traffic analysis zones (TAZs) based pedestrian and bicycle crash frequency analysis. Additionally, spatial spillover effects are explored in the models by employing exogenous variables from neighboring zones. The dual-state models such as zero-inflated negative binomial and hurdle negative binomial models (with and without spatial effects) are compared with the conventional single-state model (i.e., negative binomial). The model comparison for pedestrian and bicycle crashes revealed that the models that considered observed spatial effects perform better than the models that did not consider the observed spatial effects. Across the models with spatial spillover effects, the dual-state models especially zero-inflated negative binomial model offered better performance compared to single-state models. Moreover, the model results clearly highlighted the importance of various traffic, roadway, and sociodemographic characteristics of the TAZ as well as neighboring TAZs on pedestrian and bicycle crash frequency.

Publication Date

8-1-2016

Publication Title

Accident Analysis and Prevention

Volume

93

Number of Pages

14-22

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/j.aap.2016.04.018

Socpus ID

84968879607 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84968879607

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