Examining driver injury severity in intersection-related crashes using cluster analysis and hierarchical Bayesian models

Accident Analysis and Prevention

Volumn 120, Issue , 2018, Pages 139-151

  Li, Zhenning ^a   Chen, Cong ^b   Ci, Yusheng ^c   Zhang, Guohui ^a   Wu, Qiong ^a   Liu, Cathy ^d  

^a University of Hawaii at Manoa   (United States)

^b University of South Florida   (United States)

^c HARBIN INSTITUTE OF TECHNOLOGY   (China)

^d University of Utah   (United States)

^e Sean)   (United States)

Author keywords

Cross level interaction; Driver injury severity; Hierarchical Bayesian model; Intersection related crash; K means cluster analysis

Indexed keywords

BAYESIAN NETWORKS; CLUSTER ANALYSIS; RISK ASSESSMENT; TRAFFIC CONTROL; VEHICLES;

CROSS LEVELS; DRIVER INJURY SEVERITIES; ENVIRONMENTAL CONDITIONS; EXTERNAL ENVIRONMENTS; HIERARCHICAL BAYESIAN; HIERARCHICAL BAYESIAN MODELING; HIERARCHICAL BAYESIAN MODELS; K-MEANS CLUSTER ANALYSIS;

ACCIDENTS;

AGE; BAYES THEOREM; CLASSIFICATION; CLUSTER ANALYSIS; DRUNKEN DRIVING; FEMALE; HUMAN; INJURY; INJURY SCALE; MALE; NEW MEXICO; SEATBELT; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA; TRAFFIC ACCIDENT; UTILIZATION; WEATHER;

ACCIDENTS, TRAFFIC; AGE FACTORS; BAYES THEOREM; CLUSTER ANALYSIS; DRIVING UNDER THE INFLUENCE; FEMALE; HUMANS; INJURY SEVERITY SCORE; LOGISTIC MODELS; MALE; NEW MEXICO; SEAT BELTS; WEATHER; WOUNDS AND INJURIES;

EID: 85051555925     PISSN: 00014575     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.aap.2018.08.009     Document Type: Article

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