从工作区的驾驶行为和心理生理学中推导出工作负载
Chi Zhao1, Siyang Zhang1, Zherui Zhang1
1The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, Shanghai 201804, China; College of Transportation, Tongji University, 4800 Cao'an Road, Shanghai 201804, China.
Accident; analysis and prevention
|September 13, 2025
概括
工作区驾驶增加了驾驶员的不确定性和工作量. 这项研究开发了一种机器学习模型,通过分析驾驶行为和生理反应,准确识别工作负载水平.
科学领域:
- 人类因素和人体工程学
- 运输工程 运输工程
- 认知心理学 认知心理学
背景情况:
- 工作区带来独特的驾驶挑战,增加不确定性,行为偏差和心理工作量,与典型的驾驶场景不同.
- 由于复杂而独特的驾驶环境,现有的模型无法充分解释工作区的驾驶行为和心理生理学.
- 了解工作区驾驶行为,驾驶者心理和生理学之间的动态相互作用对于安全至关重要.
研究的目的:
- 研究工作区驾驶行为,驾驶者心理和生理学的动态相互作用.
- 开发一个可解释的框架来表示驾驶员在工作区的工作量.
- 提高驾驶员辅助和自动驾驶系统的设计和优化.
主要方法:
- 用基线和三个工作区场景进行了驾驶模拟器研究.
- 收集的数据包括驾驶行为,生理指标 (心率,心率变化,瞳孔直径,目光) 和模拟后调查.
- 使用贝叶斯式超参数调 (Optuna) 优化的一种堆叠集团学习模型用于识别工作负载水平.
主要成果:
- 开发的堆叠组合模型在识别工作负载水平方面实现了93.14%的准确性,优于其他机器学习模型.
- 使用SHapley添加式扩张 (SHAP) 的分析显示,高工作量和特定的驾驶行为 (侧向位置转移,制动) 和生理反应 (心率,心率变化,瞳孔直径,目光) 之间存在显著的相关性.
- 较高的工作量与较大的横向位置转移,更频繁的车踏板使用,心率升高,心率变化减少以及瞳孔直径和目光变化增加有关.
结论:
- 该研究成功地揭示了在各种工作区条件下驾驶行为,驾驶者心理和生理学之间的动态关系.
- 这些发现为改善工作区环境的驾驶辅助和自动驾驶系统的设计和优化提供了关键的见解.
- 可解释的工作负载表示框架为理解复杂驾驶场景中的驾驶员状态提供了一种新的方法.
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