Cooperative Adaptive Cruise Control for Connected Autonomous Vehicles Using Spring Damping Energy Model

Cooperative adaptive cruise control (CACC) has been widely considered as a potential solution for reducing traffic congestion, increasing road capacity, reducing fossil fuel consumption and improving traffic safety. Traditional CCAC methods rely heavily on the vehicle-to-vehicle communications to achieve cooperation. However, in the real-world scenarios, unreliable communication will degrade CACC to adaptive cruise control, which may bring negative influences on safety (i.e., increase the risk of collisions). To overcome this drawback, this paper innovatively applies a spring damping energy model to construct a robust autonomous vehicle platoon system. The proposed design of the energy model ensures that the stability and safety of the platoon system be maintained in the event of such sudden degradation. Based on this technique, a distributed control protocol which only utilizes local information from neighbors is then proposed. Furthermore, some practical constraints such as the connectivity of the vehicle platoon system and the bound of the control inputs are guaranteed. Finally, the effectiveness of the proposed CCAC strategy is validated by multiple simulation experiments in Unreal Engine.

Automated summary

Cooperative adaptive cruise control (CACC) is considered a potential solution for reducing traffic congestion, increasing road capacity, reducing fossil fuel consumption and improving traffic safety. This paper innovatively applies a spring damping energy model to construct a robust autonomous vehicle platoon system in order to overcome the negative influence of unreliable communication on CACC. Based on this model, a distributed control protocol utilizing only local information from neighbors is proposed, guaranteeing the connectivity and control input bounds of the vehicle platoon system. Finally, the proposed CCAC strategy is validated through multiple simulation experiments in Unreal Engine.