What factors predict drivers' self-reported lane change violation behavior at urban intersections? A study in China

• Published in: PloS one Vol. 14; no. 5; p. e0216751
• Main Authors: Wang, Xiaoxiao, Xu, Liangjie, Hao, Yanping
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 15.05.2019; Public Library of Science (PLoS)
• Subjects: Accidents; Accidents, Traffic - prevention & control; Accidents, Traffic - psychology; Adolescent; Adult; Altruism; Analysis; Attitude; Automobile Driving - legislation & jurisprudence; Automobile Driving - psychology; Behavior; Biology and Life Sciences; China; Cities; Computer and Information Sciences; Fatalities; Female; Gender differences; Human behavior; Humans; Hypotheses; Intention; Lane changing; Laws, regulations and rules; Literature reviews; Male; Medicine and Health Sciences; Middle Aged; Models, Psychological; Motivation; Motivation (Psychology); Motor vehicle drivers; Motor vehicle driving; Norms; People and Places; Physical Sciences; Psychological aspects; Psychological factors; Psychology; Research and Analysis Methods; Safety research; Self Report; Sex roles; Skewness; Social aspects; Social Sciences; Studies; Surveys; Surveys and Questionnaires; Theory; Traffic accidents & safety; Traffic conflicts; Urban areas; Women; Young Adult; China; Cities
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0216751

Lane change violations are a major cause of traffic conflicts and accidents at urban intersections and one of many road-safety issues in China. This study aims to explore the socio-psychological factors underlying drivers' motivation for lane change violation behavior at urban intersections and examines how these factors predict this violation behavior. A self-reported questionnaire is designed by applying the construct of the theory of planned behavior (TPB) to collect data. Five hundred-six valid responses are received from the questionnaire survey conducted on the Internet in China. The data are then analyzed using structural equation modeling (SEM). The results of the analysis show that behavioral intention is the strongest predictor of self-reported lane change violation behavior at urban intersections. Perceived behavioral control has both direct and indirect effects on self-reported lane change violation behavior. Furthermore, attitude, subjective norms and perceived behavioral control are found to have significant correlations with drivers' intention of lane change violations at urban intersections. The results of this study could provide a reference for designing more effective interventions to modify drivers' lane change violation behavior at urban intersections.