Cloud Control with Communication Delay Prediction for Intelligent Connected Vehicles

In this paper, we propose a cloud control method with communication delay prediction for intelligent connected vehicles (ICVs), which not only constructs a prediction model using real-world 5G communication delay data, but also evaluate the effectiveness of the cloud control method considering delay in typical application scenarios. Firstly, for the application data interaction of 5G vehicle-to-network-to-vehicle (V2N2V) full-link, we collect a large amount of communication delay data through vehicle test. Then, a novel data-driven delay prediction method based on the Long Short-Term Memory (LSTM) network is introduced. Finally, a cloud control method considering communication delay is constructed at unsignalized intersection. The test results show that our method can not only achieve high delay prediction accuracy, but also significantly reduce vehicle velocity fluctuations and avoid collisions.