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China’s Belt and Road Initiative (BRI) has attracted increasing attention worldwide since its inception in 2013. Although the research is fast increasing in terms of publications, there is a lack of knowledge about the intellectual structure, research trends, and appropriate theories underpinning. Using bibliometric data from 1583 articles from 2013 to 2019 in the Web of Science and Scopus databases, we used bibliometric techniques and scientometric analyses to identify and analyze the intellectual structure, hotspots, and emerging trends in this field. We identified 18 clusters that we categorized into three groups for thematic discussion. Research gaps and future research directions were identified and proposed after qualitative content analysis. By providing the big picture of the latest research on BRI since it was initiated, this paper serves as a one-stop shop for multi-disciplinary research on the topic.

In the process of vehicle anti-rollover, the driver's behavioral characteristics have a great influence on the vehicle rollover stability. However, the existing researches on anti-rollover rarely consider the driver in the human-vehicle-road closed loop system, which may directly affects the rollover dynamics characteristics of the vehicle. Aiming at this problem, this work analyzes the influence of different driver parameters on vehicle dynamics and establishes a driver model considering the vehicle rollover stability. Based on this, a collaborative control strategy of vehicle anti-rollover considering the driver's characteristics is designed to assist the driving stability requirements of different types of drivers. It includes the upper layer of supervision decision control and the lower layer of cooperative execution control. The supervisory decision control layer sets different rollover constraint boundaries for different types of drivers, and makes six control decision modes combining driver input and vehicle path tracking error. Aiming at different types of drivers, the lower cooperative execution control layer constrains the front wheel angle by the active steering system to reduce yaw rate and the risk of rollover. Moreover, it reasonably distributes the braking force of four tires by the active braking system to reduce the path tracking error while preventing rollover. The simulation results show that, the proposed cooperative control strategy can provide different control effects for different drivers, and ensure the effective anti-rollover control of the vehicle and achieve good path tracking performance. INDEX TERMS Driver model, rollover, parameter identification, active steering, active braking.