On-Ramp Merging Strategies of Connected and Automated Vehicles Considering Communication Delay

• Published in: IEEE transactions on intelligent transportation systems 2022-09, Vol.23 (9), p.15298-15312
• Main Authors: Fang, Yukun, Min, Haigen, Wu, Xia, Wang, Wuqi, Zhao, Xiangmo, Mao, Guoqiang
• Format: Article
• Language: English
• Subjects: Automation; Communication; Connected and automated vehicles; Control theory; Cooperative control; Delay; Delays; Field tests; Fuel economy; Mathematical models; Merging; Normal distribution; on-ramp merging; Optimal control; Optimization; Planning; Probability density function; Probability density functions; Risk management; Statistical analysis; statistical techniques; V2I communication delay; Vehicle dynamics; Vehicle-to-infrastructure; Vehicles
• ISSN: 1524-9050; 1558-0016
• DOI: 10.1109/TITS.2022.3140219

Improper handling of on-ramp merging may cause severe decrease of traffic efficiency and contribute to lower fuel economy, even increasing the collision risk. Cooperative control for connected and automated vehicles (CAVs) has the potential to significantly reduce the negative impact and improve safety and traffic efficiency. Implementation of cooperative on-ramp merging requires the assistance of the vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communication, wherein the communication delay may cause negative impact on CAV cooperative control. In this paper, scenario of on-ramp merging for CAVs considering the V2I communication delay are studied. Statistical characteristics of the V2I communication delay are explored from both literature and real field test, and a communication delay estimation model based on statistical techniques are proposed. Specifically, we firstly model the CAV on-ramp merging scenario using optimal control in ideal situation. Then, several statistical characteristics of the V2I communication are investigated especially the probability density function of the V2I communication delay in several application scenarios. Further, we proposed a communication delay estimation model and used the modified vehicle state to compute the corresponding control law. Real field test of V2I communication delay indicated that distribution of V2I communication delay could correlate with the application scenario and normal distribution can be generally adopted to approximate the probability density function (PDF) when the number of samples is large enough. Numerical simulation of the CAV on-ramp merging scenario considering the V2I communication delay revealed that dynamic performance of the control process would be deteriorated impacted by the V2I communication delay and it might further impact the final control effect and lead to potential lateral collision in the merging area.