The extended theory of planned behavior considering heterogeneity under a connected vehicle environment: A case of uncontrolled non-signalized intersections

With the emergence of connected vehicle (CV) technology, there is a doubt whether CVs can improve driver intentions and behaviors, thus protect them from accidents with provision real-time information. In order to understand possible impacts information provided by CV technology on drivers, this paper aims develop model which considers heterogeneity between drivers aid extended theory planned behavior. At uncontrolled non-signalized intersections, stated preference (SP) questionnaire survey was conducted build dataset consisting 1001 drivers. Based collected dataset, proposed examines relationships subjective norms, attitudes, risk perceptions, perceived behavioral control driving intentions, studies how such are simultaneously related characteristics experiences in environment. Furthermore, groups homogenous respect personality traits formed, then employed analyze responses intentions. Four key findings obtained when analyzing technology: 1) H-ETPB verified good fitness measure; 2) irrespective traits, attitudes have direct indirect association accelerate; 3) high-neurotic accelerate significantly while that low-neurotic not; 4) elder who unstable salaries or ever joined online car hailing service strong intention accelerating. The study could provide theoretical framework optimize traffic performance design, as well in-vehicle personalized CAV environments assist authorities design most acceptable rules for different at an intersection.