The extended theory of planned behavior considering heterogeneity under a connected vehicle environment: A case of uncontrolled non-signalized intersections
•Develop a mode considering the heterogeneity between drivers in the extended theory of planned behavior (H-ETPB).•Analyze the differences in responses to the variables in the H-ETPB model between driver groups which are homogenous with respect to personality traits.•Used a hybrid model integrating...
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Veröffentlicht in: | Accident analysis and prevention 2021-03, Vol.151, p.105934-105934, Article 105934 |
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Sprache: | eng |
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Zusammenfassung: | •Develop a mode considering the heterogeneity between drivers in the extended theory of planned behavior (H-ETPB).•Analyze the differences in responses to the variables in the H-ETPB model between driver groups which are homogenous with respect to personality traits.•Used a hybrid model integrating a structural equation model (SEM) with a multiple indicators multiple cause model (MIMIC).•Provided implications in optimizing traffic performance and information design and service, as well as designing the most acceptable traffic rules for drivers at an uncontrolled non-signalized intersection.
With the emergence of connected vehicle (CV) technology, there is a doubt whether CVs can improve driver intentions and behaviors, and thus protect them from accidents with the provision of real-time information. In order to understand the possible impacts of the real-time information provided by CV technology on drivers, this paper aims to develop a model which considers the heterogeneity between drivers with the aid of the extended theory of planned behavior. At the uncontrolled non-signalized intersections, a stated preference (SP) questionnaire survey was conducted to build the dataset consisting of 1001 drivers. Based on the collected dataset, the proposed model examines the relationships between subjective norms, attitudes, risk perceptions, perceived behavioral control and driving intentions, and studies how such driving intentions are simultaneously related to driver characteristics and experiences in the CV environment. Furthermore, driver groups which are homogenous with respect to personality traits are formed, and then are employed to analyze the heterogeneity in responses to driving intentions. Four key findings are obtained when analyzing driver responses to the real-time information provided by CV technology: 1) the proposed H-ETPB model is verified with a good fitness measure; 2) irrespective to driver personality traits, attitudes and perceived behavioral control have a direct and indirect association with driving intentions to accelerate; 3) driving intentions of high-neurotic drivers to accelerate are significantly related to subjective norms, while that of low-neurotic drivers are not; 4) elder high-neurotic drivers, and low-neurotic drivers who have unstable salaries or ever joined in online car hailing service have a strong intention in accelerating. The findings of this study could provide the theoretical framework to optimize traffic performance |
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ISSN: | 0001-4575 1879-2057 |
DOI: | 10.1016/j.aap.2020.105934 |