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农村多车道公路多种处理措施的碰撞修正系数的探索和比较。

Exploration and comparison of crash modification factors for multiple treatments on rural multilane roadways.

机构信息

Department of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, FL 32816-2450, United States.

Department of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, FL 32816-2450, United States.

出版信息

Accid Anal Prev. 2014 Sep;70:167-77. doi: 10.1016/j.aap.2014.03.016. Epub 2014 May 3.

DOI:10.1016/j.aap.2014.03.016
PMID:24793034
Abstract

As multiple treatments (or countermeasures) are simultaneously applied to roadways, there is a need to assess their combined safety effects. Due to a lack of empirical crash modification factors (CMFs) for multiple treatments, the Highway Safety Manual (HSM) and other related studies developed various methods of combining multiple CMFs for single treatments. However, the literature did not evaluate the accuracy of these methods using CMFs obtained from the same study area. Thus, the main objectives of this research are: (1) develop CMFs for two single treatments (shoulder rumble strips, widening shoulder width) and one combined treatment (shoulder rumble strips+widening shoulder width) using before-after and cross-sectional methods and (2) evaluate the accuracy of the combined CMFs for multiple treatments estimated by the existing methods based on actual evaluated combined CMFs. Data was collected for rural multi-lane highways in Florida and four safety performance functions (SPFs) were estimated using 360 reference sites for two crash types (All crashes and Single Vehicle Run-off Roadway (SVROR) crashes) and two severity levels (all severity (KABCO) and injury (KABC)). The results of both before-after and cross-sectional methods show that the two single treatments and the combined treatment produced safety improvement. It was found that safety effects were higher for the roadway segments with shoulder rumble strips and wider shoulder width. It was also found that the treatments were more safety effective (i.e. lower CMF) for the roadway segments with narrower original shoulder width in the before period. However, although CMFs for multiple treatments were generally lower than CMFs for single treatments, they were similar for the roadway segments with shoulder width of 8-12 feet. More specifically, CMFs for single treatments were lower than CMFs for multiple treatments for the roadway segments with shoulder width of 9 feet or higher. Among different methods of combining CMFs, the HSM, Systematic Reduction of Subsequent CMFs, Applying only the most effective CMF, and Weighted average of multiple CMFs (Meta-Analysis) showed good estimates of the combined CMFs for multiple treatments with 2.2% difference between actual and estimated CMFs. The findings suggest that the existing methods of combining multiple CMFs are generally valid but they need to be applied for different crash types and injury levels separately. Lastly, an average of the combined CMFs from the best two methods was closer to the actual CMF than the combined CMF from only one best method. This indicates that it is better not to rely on only one specific existing method of combining CMFs for predicting CMF for multiple treatments.

摘要

由于同时对道路采用了多种处理方法(或对策),因此需要评估它们的综合安全效果。由于缺乏多种处理方法的经验性碰撞修正系数(CMF),《公路安全手册》(HSM)和其他相关研究开发了多种方法来组合单一处理方法的多个 CMF。然而,文献中并没有使用来自同一研究区域的相同 CMF 来评估这些方法的准确性。因此,本研究的主要目的是:(1)使用前后对比法和横断面法为两种单一处理方法(路肩颠簸带、拓宽路肩宽度)和一种联合处理方法(路肩颠簸带+拓宽路肩宽度)制定 CMF;(2)根据实际评估的联合 CMF 评估现有方法估计的多种处理方法的联合 CMF 的准确性。本研究在佛罗里达州的农村多车道公路上收集数据,并使用 360 个参考点为两种碰撞类型(所有碰撞和单车驶出路外(SVROR)碰撞)和两种严重程度水平(所有严重程度(KABCO)和伤害(KABC))估计了四个安全性能函数(SPF)。前后对比法和横断面法的结果均表明,两种单一处理方法和联合处理方法均提高了安全性。结果发现,路肩颠簸带和更宽的路肩宽度的路段具有更高的安全效果。还发现,在前一时期,原始路肩宽度较窄的路段的处理方法更安全有效(即 CMF 较低)。然而,尽管多种处理方法的 CMF 通常低于单一处理方法的 CMF,但对于路肩宽度为 8-12 英尺的路段,它们的 CMF 较为相似。具体来说,对于路肩宽度为 9 英尺或更高的路段,单一处理方法的 CMF 低于多种处理方法的 CMF。在组合 CMF 的不同方法中,HSM、后续 CMF 的系统减少、仅应用最有效的 CMF 和多个 CMF 的加权平均值(荟萃分析)对多种处理方法的联合 CMF 进行了较好的估计,实际和估计的 CMF 之间的差异为 2.2%。研究结果表明,现有的多种 CMF 组合方法通常是有效的,但需要分别针对不同的碰撞类型和伤害水平进行应用。最后,最佳两种方法的联合 CMF 的平均值比仅使用一种最佳方法的联合 CMF 更接近实际 CMF。这表明,最好不要仅依赖于预测多种处理方法的 CMF 的一种特定的现有 CMF 组合方法。

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