The Impact of Modality, Technology Suspicion, and NDRT Engagement on the Effectiveness of AV Explanations-Reference-Cited by-同舟云学术

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The Impact of Modality, Technology Suspicion, and NDRT Engagement on the Effectiveness of AV Explanations

Published:2023 Issue: Volume:11 Page:81981-81994
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Zhang Qiaoning¹^ORCID,Esterwood Connor¹^ORCID,Pradhan Anuj K.²^ORCID,Tilbury Dawn³^ORCID,Yang X. Jessie⁴^ORCID,Robert Lionel P.¹^ORCID

Affiliation:

1. School of Information, University of Michigan, Ann Arbor, MI, USA

2. Department of Mechanical and Industrial Engineering, University of Massachusetts Amherst, Amherst, MA, USA

3. Robotics Department, University of Michigan, Ann Arbor, MI, USA

4. Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI, USA

Funder

University of Michigan (MCity) through the University of Michigan Office of Research

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10209159.pdf?arnumber=10209159

Reference81 articles.

1. Speech Auditory Alerts Promote Memory for Alerted Events in a Video-Simulated Self-Driving Car Ride

2. Improving automotive safety by pairing driver emotion and car voice emotion

3. The effects of adverse condition warning system characteristics on driver performance: An investigation of alarm signal type and threshold level

4. Perceived stress in a probability sample of the United States;cohen;The Social Psychology of Health,1988

5. Intent to purchase a plug-in electric vehicle: A survey of early impressions in large US cites

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. TimelyTale: A Multimodal Dataset Approach to Assessing Passengers' Explanation Demands in Highly Automated Vehicles;Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies;2024-08-22

2. Enhancing Pedestrian Group Detection and Tracking Through Zone-Based Clustering;IEEE Access;2023

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