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PRISMA:一种新的方法来推导风险评估的概率替代安全措施
Erwin de Gelder1, Kingsley Adjenughwure2, Jeroen Manders3
1TNO, Integrated Vehicle Safety, Helmond, The Netherlands; Delft University of Technology, Delft Center for Systems and Control, Delft, The Netherlands.
一种新的概率风险测量推导方法 (PRISMA) 可以生成实时的道路安全风险评估. 这种以数据为导向的方法可以预测交通参与者的轨迹,从而能够在没有严格假设的情况下准确地估计碰撞概率.
科学领域:
- 道路安全工程工程 道路安全工程
- 交通冲突分析分析
- 交通运输中的预测建模.
背景情况:
- 替代安全措施 (SSM) 评估交通冲突中的道路安全风险.
- 当前的SSM通常依赖于轨迹假设,限制了它们在现实世界的适用性.
- 需要可适应的SSM,提供实时风险估计.
研究的目的:
- 介绍概率风险测量推导 (PRISMA) 方法,用于推导新的SSM.
- 使用数据驱动方法实现实时计算崩概率.
- 在没有限制性假设的情况下,开发可适应各种交通场景的SSM.
主要方法:
- 利用数据驱动的方法来预测未来的交通参与者轨迹.
- 采用模拟来确定特定事件的概率 (例如,碰撞).
- 集成了一个回归模型与模拟结果进行实时风险估计.
主要成果:
- 导出了一个SSM用于评估纵向交通相互作用中的风险.
- 开发了一种基准分析方法,以评估SSM的绩效与预期的风险趋势相比.
- 证明衍生SSM与预期的风险趋势保持一致.
结论:
- PRISMA方法提供了一种灵活的,数据驱动的方法来导出SSM用于实时风险评估.
- 由此衍生的SSM显示出改善道路安全分析的前景.
- 未来的研究将将PRISMA扩展到其他冲突类型,包括横向交互和脆弱的道路使用者.
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