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Rolling Out the Red (and Green) Carpet: Supporting Driver Decision Making in Automation-to-Manual Transitions

机译:推出红色(和绿色)地毯:在自动化到手动过渡中支持驾驶员决策

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摘要

This paper assessed four types of human-machine interfaces (HMIs), classified according to the stages of automation proposed by Parasuraman et al. ["A model for types and levels of human interaction with automation," IEEE Trans. Syst. Man, Cybern. A, Syst. Humans, vol. 30, no. 3, pp. 286-297, May 2000]. We hypothesized that drivers would implement decisions (lane changing or braking) faster and more correctly when receiving support at a higher automation stage during transitions from conditionally automated driving to manual driving. In total, 25 participants with a mean age of 25.7 years (range 19-36 years) drove four trials in a driving simulator, experiencing four HMIs having the following different stages of automation: baseline (information acquisition-low), sphere (information acquisition-high), carpet (information analysis), and arrow (decision selection), presented as visual overlays on the surroundings. The HMIs provided information during two scenarios, namely a lane change and a braking scenario. Results showed that the HMIs did not significantly affect the drivers' initial reaction to the take-over request. Improvements were found, however, in the decision-making process: When drivers experienced the carpet or arrow interface, an improvement in correct decisions (i.e., to brake or change lane) occurred. It is concluded that visual HMIs can assist drivers in making a correct braking or lane change maneuver in a take-over scenario. Future research could be directed toward misuse, disuse, errors of omission, and errors of commission.
机译:本文评估了四种类型的人机界面(HMI),根据Parasuraman等人提出的自动化阶段对其进行分类。 [“用于与自动化的人类交互的类型和级别的模型,” IEEE Trans。 Syst。赛伯恩A,系统人类,第一卷30号3,第286-297页,2000年5月]。我们假设驾驶员在从有条件的自动驾驶到手动驾驶的过渡过程中,在更高的自动化阶段获得支持时,驾驶员将更快,更正确地执行决策(换道或制动)。共有25名平均年龄为25.7岁(介于19-36岁之间)的参与者在驾驶模拟器中进行了四次试验,经历了四个具有以下不同自动化阶段的HMI:基线(信息获取低),领域(信息获取) -高),地毯(信息分析)和箭头(决策选择),以可视叠加的形式呈现在周围。 HMI在两种情况下提供信息,即变道和制动情况。结果表明,HMI并没有显着影响驾驶员对接管请求的最初反应。但是,在决策过程中发现了改进:当驾驶员体验到地毯或箭头接口时,正确决策(即制动或更改车道)发生了改进。结论是,可视化的人机界面可以帮助驾驶员在接管情况下进行正确的制动或换道。未来的研究可能针对滥用,废弃,遗漏错误和佣金错误。

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  • 来源
    《Human-Machine Systems, IEEE Transactions on》 |2019年第1期|20-31|共12页
  • 作者单位

    Inst Transport Econ, N-210349 Oslo, Norway|Univ Southampton, Fac Engn & Environm, Transportat Res Grp, Southampton SO16 7QF, Hants, England;

    Tech Univ Munich, Fac Mech Engn, Dept Ergon, D-85747 Garching, Germany;

    Tech Univ Munich, Fac Mech Engn, Dept Ergon, D-85747 Garching, Germany;

    Delft Univ Technol, Fac Mech Engn, Dept Biomech Engn, NL-2628 CD Delft, Netherlands;

    Tech Univ Munich, Fac Mech Engn, Dept Ergon, D-85747 Garching, Germany;

    Univ Southampton, Fac Engn & Environm, Transportat Res Grp, Southampton SO16 7QF, Hants, England;

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