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 Cellular Vehicle-to-Everything Mode 4 (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%.

Platoon-based autonomous driving is indispensable for traffic automation, but it confronts substantial constraints in rugged terrains with unreliable links and scarce communication resources. This paper proposes a novel hierarchical Digital Twin (DT) and consensus empowered cooperative control framework for safe driving in harsh areas. Specifically, leveraging intra-platoon information exchange, one platoon-level DT is constructed on the leader and multiple vehicle-level DTs are distributed among platoon members. The leader first makes critical platoon-driving decisions based on the platoon-level DT. Then, considering the impact of unreliable links on the platoon-level DT accuracy and the consequent risk of unsafe decision-making, a distributed consensus scheme is proposed to negotiate critical decisions efficiently. Upon successful negotiation, vehicles proceed to execute critical decisions, relying on their vehicle-level DTs. Otherwise, a Space-Air-Ground-Integrated-Network (SAGIN) enabled information exchange is utilized to update the platoon-level DT for subsequent safe decision-making in scenarios with unreliable links, no roadside units, and obstructed platoons. Furthermore, based on this framework, an adaptive platooning scheme is designed to minimize total delay and ensure driving safety. Simulation results indicate that our proposed scheme improves driving safety by 21.1% and reduces total delay by 24.2% in harsh areas compared with existing approaches.