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Project

Cross-cultural differences in risky driving behavior and active intervention under the intelligent&connected transportation system. (R-11129)

In the process of globalization and urban internationalization, more and more drivers with different nationalities, languages, and cultural backgrounds gather in the same traffic environment, also in China, Belgium and many other countries. Due to cross-cultural diversity of drivers, driving behavior is highly heterogeneous in nature, even under similar time and road conditions, and with identical decision-making scenarios. This heterogeneity is directly related to the stability and smoothness of the road traffic flow, and consequent roadcongestion and -crashes. Therefore, this project focuses on the risky driving behavior of individuals with crosscultural backgrounds under different road traffic contexts. With both naturalistic driving techniques and driving simulators, we analyze cross-cultural differences in risky driving behavior of drivers from different countries. Moreover, we analyze thoroughly, and reveal comprehensively, which are the influencing human factors and traffic environment factors. Furthermore, we build a prediction model of driving behavior choice in the multicultural traffic environment, so as to reveal the choice mechanism of risky driving behavior. Based on this, we also aim to develop active intervention methods under ICTS, and test the recognition and response of different drivers to the active intervention in samples of drivers with different cultural backgrounds and under different road traffic contexts. By this project, we aim to effectively tackle the similar cross-cultural road safety management issues in the process of globalization and urban internationalization in both China and Belgium, and the results will provide a theoretical basis and technical support for a worldwide road safety improvement as well.
Date:1 Apr 2021 →  Today
Keywords:risk and evaluation studies, road user behavior
Disciplines:Intelligent transportation systems, Intelligent vehicles
Project type:Collaboration project