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Designing for Prediction-Level Collaboration Between a Human Driver and an Automated Driving System

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AutomotiveUI '21 Adjunct: 13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

Pages 213 - 216

https://doi.org/10.1145/3473682.3481873

Published: 22 September 2021 Publication History

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Abstract

Although automated driving (AD) systems progress fast in recent years, there are still various corner cases that such systems cannot handle well especially for predicting the behavior of surrounding traffic. This may result in discomfort or even dangerous situations. Results from a previous Wizard-of-OZ study suggest that the collaboration between human and system at the prediction level can effectively enhance the experience and comfort of automated driving. For an in-depth investigation of the confluence between AD and driver, a prototype was implemented in a driving simulator driven by a functional AD system that has been partially validated on the public road. Furthermore, we designed and implemented a gaze-button input for intuitive vehicle referencing and a graphical user interface (GUI) for enhancing the explainability of the AD system. Three typical driving scenarios in which an AD could take advantage of the human driver’s anticipation to drive more comfortable and personalized were created for subsequent evaluation.

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Cited By

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Peintner JEscher BDetjen HManger CRiener A(2024)How to Design Human-Vehicle Cooperation for Automated Driving: A Review of Use Cases, Concepts, and InterfacesMultimodal Technologies and Interaction10.3390/mti80300168:3(16)Online publication date: 26-Feb-2024
https://doi.org/10.3390/mti8030016
You FYan XZhang JCui W(2022)Design Factors of Shared Situation Awareness Interface in Human–Machine Co-DrivingInformation10.3390/info1309043713:9(437)Online publication date: 16-Sep-2022
https://doi.org/10.3390/info13090437
Zhang J(2022)Researches advanced in human-computer collaboration and human-machine cooperation: from variances to common prospect2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022)10.1117/12.2641865(142)Online publication date: 10-Nov-2022
https://doi.org/10.1117/12.2641865

Designing for Prediction-Level Collaboration Between a Human Driver and an Automated Driving System
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms

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AutomotiveUI '21 Adjunct: 13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

September 2021

234 pages

ISBN:9781450386418

DOI:10.1145/3473682

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Published: 22 September 2021

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AutomotiveUI '21: 13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

September 9 - 14, 2021

Leeds, United Kingdom

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Overall Acceptance Rate 248 of 566 submissions, 44%

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Peintner JEscher BDetjen HManger CRiener A(2024)How to Design Human-Vehicle Cooperation for Automated Driving: A Review of Use Cases, Concepts, and InterfacesMultimodal Technologies and Interaction10.3390/mti80300168:3(16)Online publication date: 26-Feb-2024
https://doi.org/10.3390/mti8030016
You FYan XZhang JCui W(2022)Design Factors of Shared Situation Awareness Interface in Human–Machine Co-DrivingInformation10.3390/info1309043713:9(437)Online publication date: 16-Sep-2022
https://doi.org/10.3390/info13090437
Zhang J(2022)Researches advanced in human-computer collaboration and human-machine cooperation: from variances to common prospect2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022)10.1117/12.2641865(142)Online publication date: 10-Nov-2022
https://doi.org/10.1117/12.2641865

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Hybrid Eyes: Design and Evaluation of the Prediction-Level Cooperative Driving with a Real-World Automated Driving System

“Watch out!”: Prediction-Level Intervention for Automated Driving

Driver drowsiness in automated and manual driving: insights from a test track study

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