一个概念框架,用于自动化解锁
1Department Transport and Planning, Delft University of Technology, Delft, The Netherlands. s.nordhoff@tudelft.nl.
Scientific reports
|April 15, 2024
概括
了解自动化脱节是安全自动化系统的关键. 这项研究揭示了人类因素和自动化问题,比如感知到的故障和环境限制,导致脱离,改善未来的技术.
科学领域:
- 人与计算机的交互
- 汽车工程 汽车工程
- 认知心理学 认知心理学
背景情况:
- 自动化系统,包括特斯拉的自动驾驶和FSD Beta等驾驶辅助技术,越来越普遍.
- 了解自动化失效的原因对于提高安全性和效率至关重要.
- 人类操作员和自动化本身可以启动脱离,需要全面分析.
研究的目的:
- 调查人类操作员和自动化的自动化脱离所导致的多方面的因素.
- 在现实世界的使用场景中,识别和分类这些脱离背后的主要驱动因素.
- 基于经验数据,开发一个概念框架来理解基于实证数据的自动化脱离.
主要方法:
- 与特斯拉的自动驾驶和FSD Beta的103名用户进行了半结构化采访.
- 分析了采访数据,以识别和分类导致自动化脱离的因素.
- 将发现综合到一个概念框架中,从人为因素和控制理论中汲取.
主要成果:
- 确定了五个主要类别和三十五个子类别的自动化脱离因素.
- 关键因素包括人类操作员状态 (例如,不信任,丧),对自动化行为的感知,自动化对操作员的感知 (警) 和环境限制.
- 人类操作员因预期的故障,不自然的自动化行为和在某些条件下无法安全操作而脱离.
- 由于检测到操作员警问题或违反规则,自动化断开.
- 乘客和其他道路使用者的社会影响也会影响运营商脱离道的决定.
结论:
- 自动化脱离受到人类操作因素,自动化性能和环境环境的复杂相互作用的影响.
- 解决运营商的担忧,提高自动化局势意识,考虑社会动态对于提高自动化系统安全至关重要.
- 这些发现为自动驾驶汽车技术的边缘案例提供了洞察力,指导了提高安全性和效率的未来发展.
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