[1] Xu Jian, Sun Lu, Conditional autoregressive negative binomial modelfor analysis of crash count using Bayesian methods [J]. Journal of Southeast University (English Edition), 2014, 30 (1): 96-100. [doi:10.3969/j.issn.1003-7985.2014.01.018]

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Conditional autoregressive negative binomial modelfor analysis of crash count using Bayesian methods()

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

30

Issue:

2014 1

Page:

96-100

Research Field:

Traffic and Transportation Engineering

Publishing date:

2014-03-31

Info

Title:

Conditional autoregressive negative binomial modelfor analysis of crash count using Bayesian methods

Author(s):

Xu Jian¹;  2;  Sun Lu¹;  3

¹School of Transportation, Southeast University, Nanjing 210096, China
²Center for Transportation Research, University of Texas at Austin, Austin 78712, USA
³Department of Civil Engineering, Catholic University of America, Washington DC 20064, USA

Keywords:

traffic safety;  crash count;  conditional autoregressive negative binomial model;  Bayesian analysis;  Markov chain Monte Carlo

PACS:

U491.31

DOI:

10.3969/j.issn.1003-7985.2014.01.018

Abstract:

In order to improve crash occurrence models to account for the influence of various contributing factors, a conditional autoregressive negative binomial(CAR-NB)model is employed to allow for overdispersion(tackled by the NB component), unobserved heterogeneity and spatial autocorrelation(captured by the CAR process), using Markov chain Monte Carlo methods and the Gibbs sampler. Statistical tests suggest that the CAR-NB model is preferred over the CAR-Poisson, NB, zero-inflated Poisson, zero-inflated NB models, due to its lower prediction errors and more robust parameter inference. The study results show that crash frequency and fatalities are positively associated with the number of lanes, curve length, annual average daily traffic(AADT)per lane, as well as rainfall. Speed limit and the distances to the nearest hospitals have negative associations with segment-based crash counts but positive associations with fatality counts, presumably as a result of worsened collision impacts at higher speed and time loss during transporting crash victims.

References:

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Memo

Memo:

Biographies: Xu Jian(1985—), male, graduate; Sun Lu(corresponding author), male, doctor, professor, sunl@cua.edu.
Foundation items: The National Science Foundation by Changjiang Scholarship of Ministry of Education of China(No.BCS-0527508), the Joint Research Fund for Overseas Natural Science of China(No.51250110075), the Natural Science Foundation of Jiangsu Province(No.SBK200910046), the Postdoctoral Science Foundation of Jiangsu Province(No.0901005C).
Citation: Xu Jian, Sun Lu. Conditional autoregressive negative binomial model for analysis of crash count using Bayesian methods[J].Journal of Southeast University(English Edition), 2014, 30(1):96-100.[doi:10.3969/j.issn.1003-7985.2014.01.018]

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