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高速公路驾驶风险评估的复合安全潜力领域

Dachuan Zuo¹, Zilin Bian¹, Fan Zuo¹

¹Department of Civil and Urban Engineering, Tandon School of Engineering, New York University, 6 MetroTech Center, 4th Floor, Brooklyn, NY, USA.

Accident; analysis and prevention

|June 9, 2025

概括

一个新的复合安全潜力场 (C-SPF) 框架通过整合主观风险感知和客观碰撞概率来改善驾驶风险评估. 这种方法增强了先进汽车技术的实时安全评估.

科学领域:

车辆安全车辆安全
人与计算机的交互
运输工程运输工程

背景情况:

驾驶风险评估对于先进的车辆安全系统,如碰撞预警和自动驾驶至关重要.
现有的安全潜力现场模型在对纵向和横向风险进行校准和概括方面存在局限性.
需要实时,类似人类的风险评估,以实现无的车辆与车辆之间的互动.

研究的目的:

为全面的驾驶风险评估提出一个新的复合安全潜力领域 (C-SPF) 框架.
解决现有模型在校准和捕捉纵向和横向风险方面的局限性.
开发一种风险评估指标,反映出与人类类似的推理,以提高车辆安全.

主要方法:

开发了一个C-SPF框架,结合了风险感知的主观领域和碰撞概率的客观领域.
使用来自车辆轨迹数据集的广泛的二维间距数据对C-SPF进行校准.
分析了自然驾驶数据集,以验证框架捕捉安全操作的能力.

主要成果:

该C-SPF有效地捕捉驾驶员的近距离风险感知,并为驾驶行为提供现实的解释.
证明了框架能够识别纵向和横向风险,从而引发安全操作.
案例研究证实了C-SPF在解释复杂的横向行为,如车道更改调整方面的有效性.

结论:

拟议的C-SPF框架为驾驶风险评估提供了更现实的,更全面的方法.
C-SPF克服了以前安全潜力现场模型的校准和概括限制.
这一进步对于开发更安全,更具互动性的自动驾驶和半自动驾驶汽车至关重要.

关键词:

驾驶员行为驾驶员行为高速公路风险评估高速公路风险评估人类类似的风险感知.道路碰撞事故发生在道路上.安全潜力领域安全潜力领域交通安全交通安全交通安全

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