在水平曲线中使用代用安全措施和机器学习评估安全性
Navid Nadimi1, Hojjat Fathipour2, Abbas Sheykhfard3
1Faculty of Engineering, Shahid Bahonar University, Pajoohesh Sq., Kerman, Iran. navidnadimi@uk.ac.ir.
Scientific reports
|April 11, 2025
概括
在水平曲线 (HCs) 上使用替代安全措施 (SSM) 和决策树算法分析了道路安全. 曲线半径和曲线前速度显著影响HC安全,驾驶员经验也发挥着关键作用.
科学领域:
- 道路安全工程工程 道路安全工程
- 交通工程是交通工程.
- 交通运输安全运输安全
背景情况:
- 水平曲线 (HCs) 是关键的道路元素,与高事故风险相关.
- 直接分析罕见的碰撞事件具有挑战性,需要使用替代安全措施 (SSM).
- 之前的研究还没有全面利用机器学习和SSM来评估HC安全性.
研究的目的:
- 评估各种因素对水平曲线安全性的影响.
- 用决策树算法和SSM识别影响HC安全的关键变量.
- 建立对HCs关键安全影响变量的关键值.
主要方法:
- 应用决策树算法来分析HC安全数据.
- 使用替代安全措施 (SSM) 作为事故事件的代理.
- 包括各种变量:驱动器特性,HC规格和环境因素.
主要成果:
- 曲线的半径和前面的触角截面上的速度被确定为影响HC安全性的最重要的因素.
- 确定了关键值:358米的曲线半径和23米/秒的曲线前速度.
- 驾驶员的经验,事故史和教育水平被发现是驾驶员的关键特征,而环境条件没有显著影响.
结论:
- 道路几何 (曲线半径) 和接近条件 (速度) 对水平曲线安全至关重要.
- 驾驶员特定的因素显著影响驾驶员安全驾驶HC的能力.
- 开发的方法提供了一个强大的框架来评估和提高HC安全性,特别是在数据稀缺的环境中.
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