识别影响受不安全驾驶行为影响的碰撞事故的重要道路走廊因素,帮助执法部门积极减少碰撞事故

John McCombs, H. Al-Deek, Adrian Sandt, Grady Carrick
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引用次数: 0

摘要

交通执法人员的有效分配可以在交通事故发生前阻止不安全的驾驶者,从而主动减少交通事故,但由于人员编制的限制,这可能很难做到。因此,必须找出可能助长不安全驾驶行为的道路因素,以便采取适当的主动执法方法。本文对佛罗里达州的信号干道走廊进行了建模,以确定影响七种不安全驾驶行为碰撞率的重要因素。采用标准化的走廊定义,确定了佛罗里达州七个城市县的 406 条走廊。从 2017 年到 2021 年,这些走廊共发生了 18518 起涉及所研究行为的碰撞事故,其中包括 5053 起致命和受伤(FI)碰撞事故。我们建立了三个随机森林回归模型,以确定影响所有碰撞事故(模型 1)、FI 碰撞事故(模型 2)以及仅由粗心或鲁莽驾驶导致的 FI 碰撞事故(模型 3)的碰撞率的重要走廊级因素。帕斯科县的交通走廊、信号灯交叉口密度较大的交通走廊以及拥有六条或六条以上车道的交通走廊在所有三个模型中的预测碰撞率都高于平均水平。此外,限速大于 45 英里/小时(模型 1)、双车道(模型 1 和 3)、无学校区(模型 1 和 3)、自行车道(模型 2 和 3)以及无水平弯道(模型 2 和 3)的走廊的碰撞率预计也高于平均水平。执法机构在进行分配决策时,如果考虑到这些因素,就有可能减少因这些不安全行为造成的车祸、人员伤亡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identifying Important Roadway Corridor Factors which Affect Crashes Influenced by Unsafe Driving Behaviors to Help Law Enforcement Proactively Reduce Crashes
Effective allocation of traffic law enforcement officers can proactively reduce crashes by stopping unsafe drivers before crashes occur, but this can be difficult because of staffing limitations. Therefore, it is important to identify roadway factors that could encourage unsafe driving behaviors so appropriate proactive enforcement methods can be taken. In this paper, signalized arterial roadway corridors in Florida are modeled to identify the important factors that affect the crash rate for seven unsafe driving behaviors. Using a standardized corridor definition, 406 corridors in seven urban Florida counties were identified. These corridors contained 18,518 crashes, including 5053 fatal and injury (FI) crashes, from 2017 to 2021 involving the studied behaviors. Three random forest regression models were developed to identify the important corridor-level factors that affect the crash rate for all crashes (model 1), FI crashes (model 2), and only FI crashes caused by careless or reckless driving (model 3). Corridors in Pasco County, corridors with greater signalized intersection densities, and corridors with six or more lanes had above average predicted crash rates for all three models. In addition, corridors with speed limits greater than 45 mph (model 1), two lanes (models 1 and 3), no school zones (models 1 and 3), bike lanes (models 2 and 3), and no horizontal curvature (models 2 and 3) were predicted to have higher than average crash rates. By considering these factors when making allocation decisions, law enforcement agencies can likely reduce crashes, injuries, and fatalities caused by these unsafe behaviors.
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