• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>International Journal of Automotive Engineering >Effect of Automation Instructions and Vehicle Control Algorithms on Eye Behavior in Highly Automated Vehicles
【24h】

Effect of Automation Instructions and Vehicle Control Algorithms on Eye Behavior in Highly Automated Vehicles

机译：自动化指令和车辆控制算法对高度自动化车辆的眼睛行为的影响

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Increasingly vehicle automation may convey greater capability than it actually possesses. The emergence of highly capable vehicle automation (e.g., SAE Level 4) and the promise of driverless vehicles in the near future can lead drivers to inappropriately cede responsibility for driving to the vehicle with less capable automation (e.g., SAE Level 2). This inappropriate reliance on automation can compromise safety, and so we investigated how algorithms and instructions might mitigate overreliance. Seventy-two drivers, balanced by gender, between the ages of 25 and 55, participated in this study using a fixed-base driving simulator. Drivers were exposed to one of three vehicle steering algorithms: lane centering, lane keeping, or an adaptive combination. A gaze tracker was used to track eye glance behavior. While automation was engaged, participants were told they could interact with an email sorting task on a tablet positioned near the center stack. Changes in roadway demand—traffic approaching in the adjacent lane—varied across the drive. Instructions indicating the driver was responsible, in combination with the adaptive algorithm, led drivers to be particularly attentive to the road as the traffic approached them. These results also have implications for evaluating more capable automation (SAE Levels 4 and 5), where drivers need not attend to the road: unnecessary attention to roadway demands might indicate lack of trust and acceptance of control algorithms that guide driverless vehicles.
机译：越来越多的车辆自动化可以传达比其实际拥有的更大的功能。高性能车辆自动化（例如SAE Level 4）的出现以及无人驾驶车辆的承诺在不久的将来会导致驾驶员不恰当地放弃驾驶自动化能力较低的车辆（例如SAE Level 2）的责任。这种对自动化的不适当依赖会损害安全性，因此我们研究了算法和指令如何减轻过度依赖。七十二名年龄在25至55岁之间的男女驾驶员，使用固定基准的驾驶模拟器参加了这项研究。驾驶员会遇到以下三种车辆转向算法之一：车道居中，车道保持或自适应组合。使用凝视追踪器来追踪眼睛的扫视行为。在启用自动化的同时，参与者被告知可以与位于中心堆栈附近的平板电脑上的电子邮件分类任务进行交互。道路需求的变化（相邻车道上的交通驶近）在整个行驶过程中各不相同。指示驾驶员负责的指令与自适应算法相结合，使驾驶员在交通接近时特别注意道路。这些结果也对评估功能更强大的自动化（SAE 4级和5级）具有影响，因为驾驶员无需上路：对道路需求的不必要关注可能表明缺乏对引导无人驾驶车辆的控制算法的信任和接受。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号