Predicting expressway crash frequency using a random effect negative binomial model: A case study in China

Accident Analysis and Prevention

Volumn 98, Issue , 2017, Pages 214-222

  Ma, Zhuanglin ^a   Zhang, Honglu ^b   Chien, Steven I Jy ^a,c   Wang, Jin ^d   Dong, Chunjiao ^e  

^a CHANG'AN UNIVERSITY   (China)

^b Deppon Logistics Co Ltd   (China)

^c NEW JERSEY INSTITUTE OF TECHNOLOGY   (United States)

^d Transportation Science and Research Institute of Yunnan   (China)

^e University of Tennessee   (United States)

Author keywords

Crash frequency; Goodness of fit; Negative binomial model; Prediction; Random effects negative binomial model

Indexed keywords

FORECASTING; MAXIMUM LIKELIHOOD;

CRASH FREQUENCY; EXPLANATORY VARIABLES; GOODNESS OF FIT; MAXIMUM LIKELIHOOD METHODS; MODEL PERFORMANCE; NEGATIVE BINOMIAL MODELS; PREDICTION ERRORS; STEPWISE PROCEDURE;

RANDOM PROCESSES;

CHINA; ENVIRONMENTAL PLANNING; HUMAN; MOTOR VEHICLE; PROBABILITY; SAFETY; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA; THEORETICAL MODEL; TRAFFIC ACCIDENT;

ACCIDENTS, TRAFFIC; CHINA; ENVIRONMENT DESIGN; HUMANS; MODELS, STATISTICAL; MODELS, THEORETICAL; MOTOR VEHICLES; PROBABILITY; SAFETY;

EID: 84994051939     PISSN: 00014575     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.aap.2016.10.012     Document Type: Article

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