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

Songtao Xie, Junyan Hu, Farshad Arvin, Zhengtao Ding

Research output: Contribution to journalArticlepeer-review

Abstract

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.
Original languageEnglish
Article number1939-9359
Pages (from-to)1-14
Number of pages14
JournalIEEE Transactions on Vehicular Technology
DOIs
Publication statusPublished - 1 Nov 2022

Keywords

  • Autonomous vehicles
  • Cruise control
  • Protocols
  • Springs
  • Thermal stability
  • Topology
  • Vehicle dynamics
  • Vehicular ad hoc networks
  • cooperative adaptive cruise control
  • distributed multi-vehicle systems
  • spring damping energy model
  • vehicle-to-vehicle communication

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