1. Intention of Risk-Taking Behavior at Unsignalized Intersections Under the Connected Vehicle Environment
- Author
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Peng Li, Qianshan Jiang, Farrukh Baig, Helai Huang, Wenjing Zhao, and Jaeyoung Lee
- Subjects
General Computer Science ,media_common.quotation_subject ,Control (management) ,Economic shortage ,unsignalized intersections ,Structural equation modeling ,Connected vehicles ,Connected vehicle ,Perception ,0502 economics and business ,0501 psychology and cognitive sciences ,General Materials Science ,050107 human factors ,media_common ,050210 logistics & transportation ,structural equation model ,05 social sciences ,General Engineering ,Theory of planned behavior ,risky driving intentions ,Vehicle to infrastructure ,theory of planned behavior ,lcsh:Electrical engineering. Electronics. Nuclear engineering ,Risk taking ,Psychology ,lcsh:TK1-9971 ,Social psychology - Abstract
With the rapid emergence of connected vehicle (CV) technologies, there is a shortage of research to understand CV technology’s effect on drivers’ risk-taking behavioral intentions. This article aims to analyze driver responses to the real-time information by comparing their reactions to driving intentions between the CV and non-CV environments. A multi-group structural equation model (SEM) is employed to explore the heterogeneity in the relationships between behavioral intentions, attitudes, subjective norms, perceived behavioral control, and risk perceptions under the two different environments. This study reveals two key findings: 1) regarding driver responses to the theory of planned behavior (TPB) model, there are significant differences in attitudes and risk perceptions between the CV and non-CV environments; 2) irrespective of driving environments, risk-taking behavioral intentions are directly related to perceived behavioral control and risk perceptions. While intentions are directly related to attitudes but not associated with subjective norms under the non-CV environment. In contrast, intentions are directly related to subjective norms but not associated with attitude under the CV environment. The findings provide a theoretical basis for using TPB to evaluate CV technology’s effects and understanding the differences between the CV and non-CV environments.
- Published
- 2021
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