Crash risk analysis for Shanghai urban expressways: A Bayesian semi-parametric modeling approach

Accident Analysis and Prevention

Volumn 95, Issue , 2016, Pages 495-502

  Yu, Rongjie ^a,b,c   Wang, Xuesong ^a,b,c   Yang, Kui ^a,b,c   Abdel Aty, Mohamed ^b  

^a BEIJING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS   (China)

^b University of Central Florida   (United States)

^c TONGJI UNIVERSITY   (China)

Author keywords

Bayesian inference; Crash risk analysis; Random effects logistic regression model; Semi parametric model

Indexed keywords

ACCIDENT PREVENTION; ADVANCED TRAFFIC MANAGEMENT SYSTEMS; AIR TRAFFIC CONTROL; BAYESIAN NETWORKS; HIGHWAY TRAFFIC CONTROL; INFERENCE ENGINES; NORMAL DISTRIBUTION; RANDOM PROCESSES; REGRESSION ANALYSIS; RISK ASSESSMENT; SAFETY ENGINEERING; TRAFFIC CONGESTION; TRAFFIC CONTROL;

ACTIVE TRAFFIC MANAGEMENTS; BAYESIAN INFERENCE; INFERENCE TECHNIQUES; LOGISTIC REGRESSION MODELING; LOGISTIC REGRESSION MODELS; SEMI-PARAMETRIC MODELING; SEMIPARAMETRIC MODELS; UNOBSERVED HETEROGENEITY;

RISK ANALYSIS;

BAYES THEOREM; CAR DRIVING; CHINA; CITY; ENVIRONMENTAL PLANNING; HUMAN; PROCEDURES; RISK ASSESSMENT; SAFETY; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA; TRAFFIC ACCIDENT; URBAN POPULATION;

ACCIDENTS, TRAFFIC; AUTOMOBILE DRIVING; BAYES THEOREM; CHINA; CITIES; ENVIRONMENT DESIGN; HUMANS; LOGISTIC MODELS; MODELS, STATISTICAL; RISK ASSESSMENT; SAFETY; URBAN POPULATION;

EID: 84956646625     PISSN: 00014575     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.aap.2015.11.029     Document Type: Article

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