Application of Fractal theory for crash rate prediction: Insights from random parameters and latent class tobit models

Accident Analysis and Prevention

Volumn 112, Issue , 2018, Pages 30-38

  Chand, Sai ^a   Dixit, Vinayak V ^a,b  

^a UNIVERSITY OF NEW SOUTH WALES   (Australia)

^b IAG Research Centre   (Australia)

Author keywords

Congestion; Crash rate; Hurst exponent; Latent class model; Random parameters; Tobit regression

Indexed keywords

ACCIDENTS; TRANSPORTATION;

CONGESTION; CRASH RATE; HURST EXPONENTS; LATENT CLASS MODEL; RANDOM PARAMETERS; TOBIT REGRESSION;

FRACTALS;

AUSTRALIA; ENVIRONMENTAL PLANNING; FRACTAL ANALYSIS; HUMAN; PREVENTION AND CONTROL; SAFETY; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA; TRAFFIC ACCIDENT;

ACCIDENTS, TRAFFIC; AUSTRALIA; ENVIRONMENT DESIGN; FRACTALS; HUMANS; MODELS, STATISTICAL; SAFETY;

EID: 85039991003     PISSN: 00014575     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.aap.2017.12.023     Document Type: Article

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