Influence of the feedback links of connected and automated vehicle on rear-end collision risks with vehicle-to-vehicle communication

Abstract

Objective: Connected and automated vehicles (CAV) can monitor multiple vehicles ahead via vehicle-to-vehicle (V2V) communication. Although feedback information from more vehicles ahead may be more helpful for anticipations, it also makes control more complex and increases the probability of data packet loss. Then it needs an appropriate number of CAV feedback links, and the maximum number may be not suitable. Therefore, this article focuses on the influence of CAV feedback links on rear-end collision risks.

Methods: To deal with this, stability analysis of a CAV car-following model was conducted to obtain the designs of CAV feedback gains for maintaining stable CAV flow. Simulation experiments were performed to describe a traffic accident on freeway, using car-following models of manually driven vehicles (MDVs) and CAV under different CAV penetration rates. Four scenarios are considered in simulation experiments; that is, the CAV monitors 1, 2, 3, and 4 preceding vehicles, respectively. Based on the simulation experiments, surrogate safety indicators, time-exposed time-to-collision (TET), and time-integrated time-to-collision (TIT) are used to evaluate risks of rear-end collisions.

Results: Results indicated that CAV helped to decrease the collision risks, especially the more serious collision risks with smaller threshold values of time-to-collision (TTC). In addition, the reductions in collision risks are more obvious when CAV feedback changes from one link to 2 links. In addition, reducing amplitudes are not significant if the CAV feedback is extended from 2 links to 3 or 4 links.

Conclusions: Two links of CAV feedback are appropriate when control complexity is a priority, whereas 3 links is the better choice when reductions in collisions are a priority. The findings of this study provide helpful reference for CAV control and design before larger-scale implementation in real vehicles.

Keywords:

• Connected and automated vehicles
• rear-end collision risk
• feedback link
• car-following model
• safety

Additional information

Funding

This work was financially supported by the National Natural Science Foundation of China (51478113; 51878161), the Scientific Research Foundation of Graduate School of Southeast University (YBJJ1792), and the Fundamental Research Funds for the Central Universities and the Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX17_0146).