The development and validation of the perceived safety of intelligent connected vehicles scale

Whether the public feels psychologically safe about intelligent connected vehicles (ICVs) is crucial for this new technology to prevail. While researchers have realized the importance of perceived safety, a direct and psychometrically sound measure is still needed. This paper aimed to develop and validate a scale to measure the perceived safety of ICVs. In Study 1, an 8-item scale of the perceived safety was developed based on a literature review and used with a sample from Beijing (n = 373), among the people who are very likely to be the first wave of users. Exploratory factor analysis retained six items and found that a two-dimensional model (three items for cognitive safety and three items for emotional safety) best suited the data. Correlational analyses suggested that the two components may have unique causes and consequences. In Study 2, using a different sample from Shenzhen (n = 352), confirmatory factor analysis consolidated the two-factor model. Further correlational analyses showed that the scale had good criterion-related validity. Across two studies, cognitive safety was related to perceived controllability, the tendency to seek new technologies, ICV driving experience, perceived government support, drive intention and intention to be other road users. Emotional safety was correlated with social support, familiarity, benefit perception, purchase and recommend intention. These results suggest that the scale developed in this study is a useful and reliable tool to measure perceived safety. Implications for future studies and relevant policies are discussed.

• Record URL:
  https://doi.org/10.1016/j.aap.2021.106092
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0001457521001238
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00014575
• Supplemental Notes:
  • © 2021 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Cao, Jianqin
  • Lin, Li
  • 0000-0002-8093-9565
  • Zhang, Jingyu
  • Zhang, Liang
  • Wang, Ya
  • Wang, Jifang
• Publication Date: 2021-5

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Serial:
  • Accident Analysis & Prevention
  • Volume: 154
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0001-4575
  • Serial URL: http://www.sciencedirect.com/science/journal/00014575

Subject/Index Terms

• TRT Terms: Attitudes; Connected vehicles; Emotions; Factor analysis; Intelligent vehicles; Public opinion; Technological innovations
• Geographic Terms: Beijing (China)
• Subject Areas: Highways; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01769035
• Record Type: Publication
• Files: TRIS
• Created Date: Mar 27 2021 3:15PM