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New Structured Data Collection Approach for Real-Time Trust Measurement In Human-Autonomous Vehicle Interactions
- Date Issued:
- 2018
- Abstract/Description:
- Most of recent studies indicate that people are negatively predisposed toward utilizing autonomous systems. These findings highlight the necessity of conducting research to better understand the evolution of trust between humans and growing autonomous technologies such as self-driving cars (SDC). This research therefore presents a new approach for real-time trust measurement between passengers and SDCs. We utilized a new structured data collection approach along with a virtual reality (VR) SDC simulator to understand how various autonomous driving scenarios can increase or decrease human trust and how trust can be re-built in the case of incidental failures. To verify our methodology, we designed and conducted an empirical experiment on 50 human subjects. The results of this experiment indicated that most subjects could rebuild trust during a reasonable timeframe after the system demonstrated faulty behavior. Furthermore, we discovered that the cultural background and past trust-related experiences of the subjects affect how they lose or regain their trust in SDCs. Our analysis showed that this model is highly effective for collecting real-time data from human subjects and lays the foundation for more-involved future research in the domain of human trust and autonomous driving.
Title: | New Structured Data Collection Approach for Real-Time Trust Measurement In Human-Autonomous Vehicle Interactions. |
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Name(s): |
Shahrdar, Shervin, author Nojoumian, Mehrdad, Thesis advisor Florida Atlantic University, Degree grantor College of Engineering and Computer Science Department of Computer and Electrical Engineering and Computer Science |
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Type of Resource: | text | |
Genre: | Electronic Thesis Or Dissertation | |
Date Created: | 2018 | |
Date Issued: | 2018 | |
Publisher: | Florida Atlantic University | |
Place of Publication: | Boca Raton, Fla. | |
Physical Form: | application/pdf | |
Extent: | 79 p. | |
Language(s): | English | |
Abstract/Description: | Most of recent studies indicate that people are negatively predisposed toward utilizing autonomous systems. These findings highlight the necessity of conducting research to better understand the evolution of trust between humans and growing autonomous technologies such as self-driving cars (SDC). This research therefore presents a new approach for real-time trust measurement between passengers and SDCs. We utilized a new structured data collection approach along with a virtual reality (VR) SDC simulator to understand how various autonomous driving scenarios can increase or decrease human trust and how trust can be re-built in the case of incidental failures. To verify our methodology, we designed and conducted an empirical experiment on 50 human subjects. The results of this experiment indicated that most subjects could rebuild trust during a reasonable timeframe after the system demonstrated faulty behavior. Furthermore, we discovered that the cultural background and past trust-related experiences of the subjects affect how they lose or regain their trust in SDCs. Our analysis showed that this model is highly effective for collecting real-time data from human subjects and lays the foundation for more-involved future research in the domain of human trust and autonomous driving. | |
Identifier: | FA00013033 (IID) | |
Degree granted: | Thesis (M.S.)--Florida Atlantic University, 2018. | |
Collection: | FAU Electronic Theses and Dissertations Collection | |
Note(s): | Includes bibliography. | |
Subject(s): |
Autonomous vehicles Trust Measurement |
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Held by: | Florida Atlantic University Libraries | |
Sublocation: | Digital Library | |
Persistent Link to This Record: | http://purl.flvc.org/fau/fd/FA00013033 | |
Use and Reproduction: | Copyright © is held by the author, with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder. | |
Use and Reproduction: | http://rightsstatements.org/vocab/InC/1.0/ | |
Host Institution: | FAU | |
Is Part of Series: | Florida Atlantic University Digital Library Collections. |