Multi-level hot zone identification for pedestrian safety

    Authors

    J. Lee; M. Abdel-Aty; K. Choi;H. L. Huang

    Comments

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    Abbreviated Journal Title

    Accid. Anal. Prev.

    Keywords

    Pedestrian safety; Bayesian approach; Spatial error modeling; Gaussian; conditional autoregressive; CAR; Screening; Macroscopic analysis; Poisson lognormal model; Simultaneous equations modeling; SPATIAL-ANALYSIS; STATISTICAL-ANALYSIS; INJURY COLLISIONS; CRASH-FREQUENCY; MODEL; Ergonomics; Public, Environmental & Occupational Health; Social; Sciences, Interdisciplinary; Transportation

    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. (C) 2015 Elsevier Ltd. All rights reserved.

    Journal Title

    Accident Analysis and Prevention

    Volume

    76

    Publication Date

    1-1-2015

    Document Type

    Article

    Language

    English

    First Page

    64

    Last Page

    73

    WOS Identifier

    WOS:000351961500009

    ISSN

    0001-4575

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