How is driving volatility related to intersection safety? A Bayesian heterogeneity-based analysis of instrumented vehicles data

Transportation Research Part C: Emerging Technologies

Volumn 92, Issue , 2018, Pages 504-524

  Wali, Behram ^a   Khattak, Asad J ^a   Bozdogan, Hamparsum ^a   Kamrani, Mohsen ^a  

^a UNIVERSITY OF TENNESSEE   (United States)

Author keywords

Connected vehicles; Driving volatility; Full Bayes estimation; Gibbs sampler; Heterogeneity; Intersection crashes; Markov Chain Monte Carlo; Poisson Poisson log normal regressions; Proactive safety; Random parameters

Indexed keywords

BAYESIAN NETWORKS; HIGHWAY TRAFFIC CONTROL; MARKOV CHAINS; MONTE CARLO METHODS; NORMAL DISTRIBUTION; PARAMETER ESTIMATION; VEHICLES;

DRIVING VOLATILITY; FULL BAYES ESTIMATIONS; GIBBS SAMPLERS; HETEROGENEITY; INTERSECTION CRASHES; LOG-NORMAL; MARKOV CHAIN MONTE-CARLO; RANDOM PARAMETERS;

ACCIDENTS;

BAYESIAN ANALYSIS; DATA SET; HETEROGENEITY; MARKOV CHAIN; MONTE CARLO ANALYSIS; POISSON RATIO; REGRESSION ANALYSIS; TRANSPORTATION SAFETY;

EID: 85047600880     PISSN: 0968090X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.trc.2018.05.017     Document Type: Article

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