Abstract：
:This study attempts to investigate spatial autocorrelation and spillover effects in micro traffic safety analysis. To achieve the objective, a Poisson-based count regression with consideration of these spatial effects is proposed for modeling crash frequency on freeway segments. In the proposed hybrid model, the spatial autocorrelation and the spillover effects are formulated as the conditional autoregressive (CAR) prior and the exogenous variables of adjacent segments, respectively. The proposed model is demonstrated and compared to the models with only one kind of spatial effect, using one-year crash data collected from Kaiyang Freeway, China. The results of Bayesian estimation conducted in WinBUGS show that significant spatial autocorrelation and spillover effects simultaneously exist in the freeway crash-frequency data. The lower value of deviance information criterion (DIC) and more significant exogenous variables for the hybrid model compared to the other alternatives, indicate the strength of accounting for both spatial autocorrelation and spillover effects on improving model fit and identifying crash contributing factors. Moreover, the model results highlight the importance of daily vehicle kilometers traveled, and horizontal and vertical alignments of targeted segments and adjacent segments on freeway crash occurrences.
journal_name
Int J Environ Res Public Healthauthors
Wen H,Zhang X,Zeng Q,Lee J,Yuan Qdoi
10.3390/ijerph16020219subject
Has Abstractpub_date
2019-01-14 00:00:00issue
2eissn
1661-7827issn
1660-4601pii
ijerph16020219journal_volume
16pub_type
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journal_title：International journal of environmental research and public health
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abstract：:The authors wish to correct the following erratum in this paper [...]. ...
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pub_type： 已发布勘误
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更新日期：2019-04-25 00:00:00
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pub_type： 杂志文章
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更新日期：2019-08-29 00:00:00
