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Crash analysis and development of safety performance functions for Florida roads in the framework of the context classification system

机译:在上下文分类系统框架下对佛罗里达道路进行碰撞分析和开发安全性能函数

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Introduction: Safety performance functions (SPF) are employed to predict crash counts at the different roadway elements. Several SPFs were developed for the various roadway elements based on different classifications such as functional classification and area type. Since a more detailed classification of roadway elements leads to more accurate crash predictions, multiple states have developed new classification systems to classify roads based on a comprehensive classification. In Florida, the new roadway context classification system incorporates geographic, demographic, and road characteristics information. Method: In this study, SPFs were developed in the framework of the FDOT roadway context classification system at three levels of modeling, context classification (CC-SPFs), area type (AT-SPFs), and statewide (SW-SPF) levels. Crash and traffic data from 2015-2019 were obtained. Road characteristics and road environment information have also been gathered along Florida roads for the SPF development. Results: The developed SPFs showed that there are several variables that influence the frequency of crashes, such as annual average daily traffic (AADT), signalized intersections and access point densities, speed limit, and shoulder width. However, there are other variables that did not have an influence in crash occurrence such as concrete surface and the presence of bicycle slots. CC-SPFs had the best performance among others. Moreover, network screening to determine the most problematic road segments has been accomplished. The results of the network screening indicated that the most problematic roads in Florida are the suburban commercial and the urban general roads. Practical Applications: This research provides a solid reference for decision-makers regarding crash prediction and safety improvement along Florida roads. (c) 2021 National Safety Council and Elsevier Ltd. All rights reserved.
机译:简介:安全性能函数 (SPF) 用于预测不同道路元素的碰撞次数。根据不同的分类(例如功能分类和区域类型)为各种道路元素开发了几种 SPF。由于对道路元素进行更详细的分类可以带来更准确的碰撞预测,因此多个州开发了新的分类系统,以根据综合分类对道路进行分类。在佛罗里达州,新的道路环境分类系统整合了地理、人口统计和道路特征信息。方法:本研究在FDOT道路环境分类系统的框架下,在建模、环境分类(CC-SPFs)、区域类型(AT-SPFs)和全州(SW-SPF)三个层面开发了SPF。获取了2015-2019年的碰撞和交通数据。佛罗里达沿线的道路特征和道路环境信息也被收集起来,用于SPF的开发。结果:开发的 SPF 表明,有几个变量会影响碰撞频率,例如年平均每日交通量 (AADT)、信号交叉路口和接入点密度、限速和路肩宽度。但是,还有其他变量对碰撞发生没有影响,例如混凝土表面和自行车槽的存在。CC-SPFs的性能最好。此外,还完成了网络筛选,以确定问题最严重的路段。网络筛选结果表明,佛罗里达州问题最大的道路是郊区商业道路和城市一般道路。实际应用:本研究为决策者在佛罗里达道路沿线的碰撞预测和安全改进方面提供了坚实的参考。(c) 2021年国家安全委员会和爱思唯尔有限公司。保留所有权利。

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