检查任务复杂性和应对能力对驾驶风险的影响:跨国和运输方式比较研究
Stella Roussou1, Thodoris Garefalakis1, Eva Michelaraki1
1Department of Transportation Planning and Engineering, National Technical University of Athens, 5 Iroon Polytechniou Str., 157 73 Athens, Greece.
Sensors (Basel, Switzerland)
|December 23, 2023
概括
该i-DREAMS项目发现,驾驶任务复杂度增加提高了驾驶员应对能力,这对安全至关重要. 这种理解支持数据驱动的干预措施,以实现更安全的道路.
科学领域:
- 人类因素和行为科学 人类因素和行为科学
- 运输安全研究 运输安全研究
- 在驾驶行为中的统计建模.
背景情况:
- 在i-DREAMS项目中,为实时驾驶员安全干预引入了"安全容忍区" (STZ).
- 人类行为是驾驶安全和碰撞风险的关键决定因素.
研究的目的:
- 模拟驾驶任务复杂性,操作员/车辆应对能力和碰撞风险之间的复杂相互关系.
- 分析不同国家和运输方式的驾驶行为和模式.
主要方法:
- 利用了与比利时,德国和葡萄牙的80名司机进行的自然驾驶实验,收集了来自19,000次行程的数据.
- 采用通用线性模型 (GLM) 来识别潜在因素的关键变量.
- 应用结构方程模型 (SEMs) 来分析变量之间的直接和间接关系.
主要成果:
- 在任务复杂性和应对能力之间发现了显著的积极关系.
- 司机在更复杂的驾驶任务中表现出更强的应对挑战的能力.
结论:
- 对任务复杂性,应对能力和风险的综合分析可以通过不引人注目的监控来提高旅客的安全性.
- 当局应该利用人口层面的驾驶数据进行知情的移动规划,安全干预和社区建设.
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