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Distinguishing between rural and urban road segment traffic safety based on zero-inflated negative binomial regression models

机译:基于零膨胀负二项式回归模型的城乡路段交通安全判别

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摘要

In this study, the traffic crash rate, total crash frequency, and injury and fatal crash frequency were taken into consideration for distinguishing between rural and urban road segment safety. The GIS-based crash data during four and half years in Pikes Peak Area, US were applied for the analyses. The comparative statistical results show that the crash rates in rural segments are consistently lower than urban segments. Further, the regression results based on Zero-Inflated Negative Binomial (ZINB) regression models indicate that the urban areas have a higher crash risk in terms of both total crash frequency and injury and fatal crash frequency, compared to rural areas. Additionally, it is found that crash frequencies increase as traffic volume and segment length increase, though the higher traffic volume lower the likelihood of severe crash occurrence; compared to 2-lane roads, the 4-lane roads have lower crash frequencies but have a higher probability of severe crash occurrence; and better road facilities with higher free flow speed can benefit from high standard design feature thus resulting in a lower total crash frequency, but they cannot mitigate the severe crash risk.
机译:在这项研究中,为了区分城乡路段的安全性,考虑了交通事故发生率,总事故发生频率,伤害和致命事故发生频率。应用了美国派克峰地区四年半中基于GIS的崩溃数据。比较统计结果表明,农村地区的交通事故率始终低于城市地区。此外,基于零膨胀负二项式(ZINB)回归模型的回归结果表明,与农村地区相比,城市地区的总体交通事故发生频率,伤害和致命交通事故发生频率都更高。另外,发现交通事故频率随着交通量和路段长度的增加而增加,尽管交通量越高,发生严重交通事故的可能性就越小。与2车道的道路相比,4车道的道路发生事故的频率较低,但发生严重车祸的可能性较高;更高的自由流动速度和更好的道路设施可受益于高标准的设计功能,从而降低了总的撞车频率,但无法减轻严重的撞车风险。

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