A hierarchical Bayesian spatiotemporal random parameters approach for alcohol/drug impaired-driving crash frequency analysis

Analytic Methods in Accident Research

Volumn 21, Issue , 2019, Pages 44-61

  Li, Zhenning ^a   Chen, Xiaofeng ^b   Ci, Yusheng ^c   Chen, Cong ^d   Zhang, Guohui ^a  

^a University of Hawaii at Manoa   (United States)

^b NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

^c HARBIN INSTITUTE OF TECHNOLOGY   (China)

^d University of South Florida   (United States)

Author keywords

Crash frequency; Hierarchical Bayesian model; Spatiotemporal instability; Unobserved heterogeneity

Indexed keywords

BAYESIAN NETWORKS; NORMAL DISTRIBUTION;

CRASH FREQUENCY; HIERARCHICAL BAYESIAN; HIERARCHICAL BAYESIAN MODELING; SPATIO-TEMPORAL INSTABILITY; SPATIOTEMPORAL INTERACTIONS; TEMPORAL AND SPATIAL; UNOBSERVED HETEROGENEITY; VEHICLE-MILES TRAVELED;

ACCIDENTS;

EID: 85061123126     PISSN: 22136657     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.amar.2019.01.002     Document Type: Article

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