A Model for Identifying Road Risk Class

IF 1.1 Q3 TRANSPORTATION SCIENCE & TECHNOLOGY Transport and Telecommunication Journal Pub Date : 2023-04-01 DOI:10.2478/ttj-2023-0015
A. Ryguła, K. Brzozowski, A. Maczyński
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Abstract

Abstract In many road safety, traffic management, and travel planning analyses, it is useful to classify road sections according to risk level. Such classification is labour-intensive and needs to be reviewed periodically. The authors propose a model for identifying a discrete risk class for road sections based on selected traffic flow parameters, which are available in most measurement systems monitoring current traffic conditions. The Surrogate Safety Measures approach was applied in the model formulated using Principal Components Analysis. As input to the model SSMs are used in the form of a set of hourly average traffic flow parameters. The SSMs used are: the percentage of light vehicles exceeding the speed limit by a value in the range 21 to 30 km/h; the percentage of light vehicles exceeding the speed limit by more than 30 km/h; the traffic volume of light vehicles; the traffic volume of heavy vehicles and the mean speeds of light vehicles and heavy vehicles. This paper presents results of calculations of risk class obtained from the model for different locations on single-carriageway two-lane roads in Poland. Satisfactory compliance of risk classes designated by the road operator and identified by the model based on current traffic data was achieved. The proposed model can be used as the core of an effective alternative road safety screening method.
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道路风险等级识别模型
在许多道路安全、交通管理和出行规划分析中,根据风险等级对路段进行分类是很有用的。这种分类是劳力密集的,需要定期审查。作者提出了一个基于选定的交通流参数来识别路段离散风险等级的模型,这在大多数监测当前交通状况的测量系统中都是可用的。在使用主成分分析制定的模型中应用替代安全措施方法。ssm以一组每小时平均交通流量参数的形式作为模型的输入。使用的SSMs是:轻型车辆超过速度限制的百分比在21至30公里/小时的范围内;轻型车辆超过限速30公里/小时以上的百分比;轻型车辆的交通量;重型车辆的交通量以及轻型车辆和重型车辆的平均速度。本文给出了该模型在波兰单行双车道道路不同位置的风险等级计算结果。该模型基于当前交通数据,对道路运营者指定的风险等级进行了识别,达到了令人满意的符合性。该模型可作为一种有效的替代道路安全筛选方法的核心。
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来源期刊
Transport and Telecommunication Journal
Transport and Telecommunication Journal TRANSPORTATION SCIENCE & TECHNOLOGY-
CiteScore
3.00
自引率
0.00%
发文量
21
审稿时长
35 weeks
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