Off-campus UMass Amherst users: To download campus access dissertations, please use the following link to log into our proxy server with your UMass Amherst user name and password.
Non-UMass Amherst users: Please talk to your librarian about requesting this dissertation through interlibrary loan.
Dissertations that have an embargo placed on them will not be available to anyone until the embargo expires.
Author ORCID Identifier
https://orcid.org/0000-0003-3448-1239
AccessType
Campus-Only Access for Five (5) Years
Document Type
dissertation
Degree Name
Doctor of Philosophy (PhD)
Degree Program
Civil and Environmental Engineering
Year Degree Awarded
2020
Month Degree Awarded
May
First Advisor
Dr Michael Knodler
Subject Categories
Experimental Analysis of Behavior | Transportation Engineering
Abstract
The automated driving system is expected to enhance traffic safety and flow; however, the system will not be as effective if users do not accept it or do not utilize it appropriately (Lee and See 2004). Appropriate acceptance and use of technology depends on different attributes such as perceived risk, mental workload, self-confidence, and appropriate level of trust that matches system performance. An inappropriate level of trust in technology, whether it is over-trust or under-trust, would negatively affect the benefit of that technology. Based on the literature, trust is a dynamic construct that is constituted of initial or dispositional trust that is shaped before experiencing the system performance and history-based trust that constantly changes by users’ experience of the system. This study first reviews the history of research on humans’ trust in automation and the factors that have shown to be correlated with trust. It will also give a brief overview of some of the previous models of trust in automation. Then based on the gaps in the literature, a survey study and a simulator-based experiment are proposed to further study the factors affecting initial or dispositioned and history-based trust. The result of this study is expected to help better understand drivers’ trust in automated vehicles and help enhance human-automation interaction models.
DOI
https://doi.org/10.7275/17156419
Recommended Citation
Hajiseyedjavadi, Foroogh, "EVALUATION OF DRIVERS' TRUST IN AUTOMATED VEHICLES" (2020). Doctoral Dissertations. 1966.
https://doi.org/10.7275/17156419
https://scholarworks.umass.edu/dissertations_2/1966