Department of Civil, Environmental, and Construction Engineering, University of Central Florida, Orlando, FL 32816, USA.
J Safety Res. 2021 Dec;79:1-13. doi: 10.1016/j.jsr.2021.08.004. Epub 2021 Aug 21.
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.
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.
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.
安全性能函数 (SPF) 用于预测不同道路元素的碰撞次数。已经为不同的道路元素开发了多个 SPF，这些 SPF 是基于不同的分类方法，如功能分类和区域类型。由于对道路元素进行更详细的分类可以导致更准确的碰撞预测，因此多个州已经开发了新的分类系统，根据综合分类来对道路进行分类。在佛罗里达州，新的道路环境分类系统结合了地理、人口统计和道路特征信息。
在本研究中，在 FDOT 道路环境分类系统的框架内，在三个建模级别（上下文分类 (CC-SPF)、区域类型 (AT-SPF) 和全州 (SW-SPF)）开发了 SPF。从 2015 年到 2019 年，获得了碰撞和交通数据。还收集了佛罗里达州道路的道路特征和道路环境信息，以用于 SPF 开发。
开发的 SPF 表明，有几个变量会影响碰撞的频率，例如年平均日交通量 (AADT)、信号交叉口和接入点密度、限速和路肩宽度。然而，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道的存在。CC-SPF 在其他 SPF 中表现最好。此外，还完成了网络筛选，以确定最有问题的道路段。网络筛选的结果表明，佛罗里达州最有问题的道路是郊区商业和城市普通道路。
本研究为佛罗里达州的决策者提供了有关沿道路碰撞预测和安全改进的可靠参考。
