Impact of Heterogeneous Dispersion Parameter on the Expected Crash Frequency

이질적 과분산계수가 기대 교통사고건수 추정에 미치는 영향

  • Shin, Kangwon (Department of Urban Design and Development Engineering, Kyungsung University)
  • 신강원 (경성대학교 도시공학과)
  • Received : 2014.08.11
  • Accepted : 2014.09.11
  • Published : 2014.09.30


This study tested the hypothesis that the significance of the heterogeneous dispersion parameter in safety performance function (SPF) used to estimate the expected crashes is affected by the endogenous heterogeneous prior distributions, and analyzed the impacts of the mis-specified dispersion parameter on the evaluation results for traffic safety countermeasures. In particular, this study simulated the Poisson means based on the heterogeneous dispersion parameters and estimated the SPFs using both the negative binomial (NB) model and the heterogeneous negative binomial (HNB) model for analyzing the impacts of the model mis-specification on the mean and dispersion functions in SPF. In addition, this study analyzed the characteristics of errors in the crash reduction factors (CRFs) obtained when the two models are used to estimate the posterior means and variances, which are essentially estimated through the estimated hyper-parameters in the heterogeneous prior distributions. The simulation study results showed that a mis-estimation on the heterogeneous dispersion parameters through the NB model does not affect the coefficient of the mean functions, but the variances of the prior distribution are seriously mis-estimated when the NB model is used to develop SPFs without considering the heterogeneity in dispersion. Consequently, when the NB model is used erroneously to estimate the prior distributions with heterogeneous dispersion parameters, the mis-estimated posterior mean can produce large errors in CRFs up to 120%.


dispersion parameter;Poisson-gamma mixture;crash frequency;heterogeneous negative binomial model


Supported by : 경성대학교


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