Ford Motor Company, United States.
Ford Motor Company, United States.
Appl Ergon. 2017 Nov;65:90-104. doi: 10.1016/j.apergo.2017.05.009. Epub 2017 Jun 13.
This paper describes a new method, a 'mirage scenario,' to support formative evaluation of driver alerting or warning displays for manual and automated driving. This method provides driving contexts (e.g., various Times-To-Collision (TTCs) to a lead vehicle) briefly presented and then removed. In the present study, during each mirage event, a haptic steering display was evaluated. This haptic display indicated a steering response may be initiated to drive around an obstacle ahead. A motion-base simulator was used in a 32-participant study to present vehicle motion cues similar to the actual application. Surprise was neither present nor of concern, as it would be for a summative evaluation of a forward collision warning system. Furthermore, no collision avoidance maneuvers were performed, thereby reducing the risk of simulator sickness. This paper illustrates the mirage scenario procedures, the rating methods and definitions used with the mirage scenario, and analysis of the ratings obtained, together with a multi-attribute utility theory (MAUT) approach to evaluate and select among alternative designs for future summative evaluation.
本文描述了一种新方法,即“幻象场景”,用于支持手动和自动驾驶的驾驶员警报或警告显示的形成性评估。该方法提供短暂呈现然后移除的驾驶情境(例如,与前车的各种碰撞时间 (TTC))。在本研究中,在每个幻象事件期间,评估了触觉转向显示。这种触觉显示表明可能会启动转向响应以绕过前方的障碍物。使用运动基础模拟器进行了一项 32 名参与者的研究,以呈现类似于实际应用的车辆运动提示。由于这不是对前方碰撞警告系统的总结性评估,因此既没有出现也没有出现关注的意外情况。此外,没有执行避碰操纵,从而降低了模拟器病的风险。本文说明了幻象场景的程序、幻象场景中使用的评分方法和定义,以及对获得的评分的分析,以及多属性效用理论 (MAUT) 方法来评估和选择未来总结性评估的替代设计。