Multi-Level Hot Zone Identification For Pedestrian Safety

Keywords

Bayesian approach; CAR; Gaussian conditional autoregressive; Macroscopic analysis; Pedestrian safety; Poisson lognormal model; Screening; Simultaneous equations modeling; Spatial error modeling

Abstract

According to the National Highway Traffic Safety Administration (NHTSA), while fatalities from traffic crashes have decreased, the proportion of pedestrian fatalities has steadily increased from 11% to 14% over the past decade. This study aims at identifying two zonal levels factors. The first is to identify hot zones at which pedestrian crashes occurs, while the second are zones where crash-involved pedestrians came from. Bayesian Poisson lognormal simultaneous equation spatial error model (BPLSESEM) was estimated and revealed significant factors for the two target variables. Then, PSIs (potential for safety improvements) were computed using the model. Subsequently, a novel hot zone identification method was suggested to combine both hot zones from where vulnerable pedestrians originated with hot zones where many pedestrian crashes occur. For the former zones, targeted safety education and awareness campaigns can be provided as countermeasures whereas area-wide engineering treatments and enforcement may be effective safety treatments for the latter ones. Thus, it is expected that practitioners are able to suggest appropriate safety treatments for pedestrian crashes using the method and results from this study.

Publication Date

1-1-2015

Publication Title

Accident Analysis and Prevention

Volume

76

Number of Pages

64-73

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/j.aap.2015.01.006

Socpus ID

84921407732 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84921407732

This document is currently not available here.

Share

COinS