Investigating Drivers’ Awareness of Automated Vehicle Modes Using the State Diagram Method

Author:

Rheem Hansol1,Lee Joonbum1,Lee John D.1,Szczerba Joseph F.2,Mathieu Roy2,Rajavenkatanarayanan Akilesh2

Affiliation:

1. University of Wisconsin-Madison, Madison, WI, USA

2. General Motors Global Research and Development Center, Warren, MI, USA

Abstract

Driving automation introduces multiple driving modes to maximize the system’s benefits, but drivers must monitor and stay aware of these modes, which can sometimes lead to mode confusion. We modified Degani and Heymann’s state diagram method to assess the mode structure of a hypothetical driving automation system and the likelihood of discrepancies between drivers’ mode awareness and the system’s actual mode. We used the modified method and driving simulation data from participants who weren’t fully informed about all automation modes. The modified method visualized all possible combinations of automation modes and drivers’ mode awareness, highlighting where they diverge and estimating the frequency of the divergence. The diagram identified areas where human-machine interface (HMI) design can help drivers maintain accurate mode awareness. The modified state diagram method provides actionable insights for designing HMIs to reduce mode confusion and can be used to develop computational models of automation mode structures.

Funder

General Motors Global Research and Development Center

Publisher

SAGE Publications

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3