一种离散选择隐性类方法,用于捕捉在步行者十字路口的骑自行车者穿越行为中未被观察到的异质性
Rulla Al-Haideri1, Adam Weiss1, Karim Ismail1
1Department of Civil and Environmental Engineering, Carleton University, 1125 Colonel By Dr, Ottawa, ON K1S 5B6, Canada.
Accident; analysis and prevention
|December 5, 2024
概括
骑自行车的人在环形行人过道上表现出不同的行为,分类为:
科学领域:
- 交通安全和行为科学.
- 城市规划和交通工程.
- 人与计算机的交互和自主系统.
背景情况:
- 在行人交叉路口发生的骑自行车者与车辆冲突带来了重大安全风险.
- 骑自行车者的行为中未被观察到的异质性使安全分析复杂化.
- 在了解环形十字路口的骑自行车者行为方面存在研究差距.
研究的目的:
- 开发和应用一个离散选择隐性类方法,以捕捉骑自行车者在环形行人交叉路口的交叉行为中的多层次异质性.
- 根据个人和交互层面的因素来确定不同的骑自行车者行为类别.
- 提高对骑自行车者决策的理解,以改善安全措施.
主要方法:
- 利用离散选择隐性类模型来分析骑自行车者的行为.
- 将模型应用于8个圆圈站点的自然道路使用者轨迹的无人机捕获数据集.
- 整合了个人层面 (入口速度) 和交互层面 (车辆存在) 的因素,以捕捉潜在的异质性.
主要成果:
- 确定了两种不同的骑自行车者行为类别:"路人" (以速度为重点) 和"追随者" (谨慎).
- 发现初始速度显著影响后续骑自行车者的行为和决策.
- 隐性类型模型表现出高于基本模型的性能,通过较低的BIC和AIC值来表示.
结论:
- 在环形行人过道上的骑自行车者的行为中隐藏的异质性可以使用隐藏类模型有效地捕捉到.
- 区分"路过者"和"追随者"骑自行车者的行为可以提高对十字路口决策的理解和预测.
- 研究结果为提高骑自行车者的安全性和开发更安全的自动驾驶车辆与骑自行车者的互动提供了关键的见解.
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