A Bayesian network based framework for real-time crash prediction on the basic freeway segments of urban expressways

Accident Analysis and Prevention

Volumn 45, Issue , 2012, Pages 373-381

  Hossain, Moinul ^a   Muromachi, Yasunori ^a  

^a TOKYO INSTITUTE OF TECHNOLOGY   (Japan)

Author keywords

Basic freeway segments; Bayesian belief net; Random multinomial logit; Real time crash prediction model

Indexed keywords

BASIC FREEWAY SEGMENTS; BAYESIAN BELIEF NET; CRASH PREDICTION; CRASH RISK; FALSE ALARM RATE; HAZARDOUS TRAFFIC CONDITIONS; HIGH RESOLUTION DETECTOR; MODELING METHOD; MULTINOMIAL LOGIT; MULTINOMIAL LOGIT MODEL; NETWORK-BASED FRAMEWORK; PERFORMANCE EVALUATION; ROAD SECTION; TIME WINDOWS; TRAFFIC SENSORS; URBAN EXPRESSWAY;

BAYESIAN NETWORKS; FORECASTING; HIGHWAY ACCIDENTS; MATHEMATICAL MODELS;

REAL TIME SYSTEMS;

ARTICLE; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; COMPUTER PROGRAM; COMPUTER SIMULATION; ENVIRONMENTAL PLANNING; HUMAN; RISK ASSESSMENT; STATISTICAL MODEL; STATISTICS; TRAFFIC ACCIDENT; URBAN POPULATION;

ACCIDENTS, TRAFFIC; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; COMPUTER SIMULATION; ENVIRONMENT DESIGN; HUMANS; LOGISTIC MODELS; RISK ASSESSMENT; SOFTWARE; URBAN POPULATION;

EID: 84856100242     PISSN: 00014575     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.aap.2011.08.004     Document Type: Article

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