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Title:Public Perception of the Collection and Use of Connected Vehicle Data
Authors:Sailesh Acharya and Michelle Mekker
University:Utah State University
Publication Date:Sep 2021
Report #:MPC-21-439
Project #:MPC-621
TRID #:01787366
Keywords:attitudes, connected vehicles, consumer preferences, data privacy, data sharing, surveys

Abstract

With the recent increase in connectivity in vehicle technologies, connected vehicles (CVs) offer a number of potential improvements (e.g., safety, mobility, environmental efficiency, etc.) to the existing transportation system. However, to maximize these benefits, sufficient market penetration of CV is needed. The existing literature on CV technology (CVT) lacks in-depth understanding of public perception regarding the adoption of CVs in the near future. Past studies have highlighted data privacy and security associated with CVT as possible barriers to acceptance of CV. Thus, the objectives of this study were to understand the data sharing intention among the public for CV applications, ascertain the associations of CV data privacy and security with data sharing intention and CV acceptance, and to develop the acceptance model of CV. To accomplish these objectives, a number of exploratory and confirmatory factor analyses and structural equation models were fitted.

The results showed that perceived data privacy and security about CVT was found to lower the CV acceptance directly and indirectly through data sharing intention. Perceived data privacy and security was also found to lower the trust toward the technology. These findings imply that CV developers and stakeholders should act to reduce the data issues associated with CVT by strengthening the technology and by educating users about their data privacy and security efforts. In addition, this study investigated the data sharing intention for CVT. The data sharing intention was found to depend on the use of CV data but not the type of data. Thus, CV stakeholders should assure the public about the specific intended uses of data. Overall, it was found that enforcement and fee assessments were the least desirable use of CV data. Another contribution of this study is the development of a novel connected vehicle acceptance model (CAVM), which explains the overall process of development of public attitude and behavioral intention to use CVs. The associations of individual characteristics (socio-demographic, driving related, etc.) with CV acceptance and its determinants were also investigated. Finally, the number of possible ways to improve CV acceptance is discussed.

How to Cite

Acharya, Sailesh, and Michelle Mekker. Public Perception of the Collection and Use of Connected Vehicle Data, MPC-21-439. North Dakota State University - Upper Great Plains Transportation Institute, Fargo: Mountain-Plains Consortium, 2021.

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