Performance Analysis for Digital Twin Enabled Vehicular Platoon based V2V Communication

Digital twin technology has emerged as a promising strategy to augment the safety level of intelligent transportation systems by predicting the driving states of neighboring vehicles. Furthermore, with the capacity to anticipate the location of neighboring vehicles, a reduction in driving state exchanges can be achieved, which in turn decreases communication network loads and enhances system performance. However, a theoretical analysis of the performance benefits of digital twin technology in vehicular networks remains a challenge. To address this issue, this paper employs Network Calculus theory to derive the theoretical delay upper bounds of a digital twin-enabled vehicular network. Initially, we analyze the delays of constant interval arrival applications and Poisson arrival applications under Vehicle-to-Vehicle (V2V) communication in the C-V2X Mode 4 protocol. Subsequently, we examine the relationship between the driving state exchange interval and location prediction error within the digital twin framework. These two theoretical models are then integrated to formulate a method for modeling delays under varying tolerance errors. The validity of these theoretical models is confirmed by numerical outcomes. Simulation results indicate that in most scenarios, digital twin technology can diminish network loads, with a typical reduction of approximately 40% in driving state messages. Meanwhile, the average communication delay can be reduced by approximately 10%.