Cooperative Adaptive Cruise Control for Connected Autonomous Vehicles by Factoring Communication-Related Constraints

This study proposes the idea of dynamically optimizing the information flow topology (IFT) for cooperative adaptive cruise control (CACC), labeled the CACC-OIFT strategy to explicitly factor IFT dynamics and to leverage it to enhance the performance of CACC strategies. Under CACC-OIFT, the vehicles in the platoon cooperatively determine in real-time which vehicles will dynamically deactivate or activate the “send” functionality of their V2V communication devices to generate IFTs that optimize the platoon performance in terms of string stability under the ambient traffic conditions. Given the CACC controller with a one-predecessor-following scheme, and the ambient traffic conditions and the platoon size just before the start of a time period, the IFT optimization model determines the optimal IFT (in terms of the activated and deactivated status of the “send” functionalities of the vehicles in the platoon) that maximizes the expected string stability. This expectation is because each IFT has specific degeneration scenarios whose probabilities are determined by the communication failure probabilities for that time period based on the ambient traffic conditions. The optimal IFT is deployed for that time period, and the CACC controller continuously determines the car-following behaviors of the vehicles based on the unfolding degeneration scenario for each time instant within that period. The effectiveness of the proposed CACC-OIFT is validated through numerical experiments in NS-3 based on NGSIM field data. The results indicate that the proposed CACC-OIFT can significantly enhance the string stability of platoon control in an unreliable V2V communication context.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee AHB30 Standing Committee on Vehicle-Highway Automation.
  • Corporate Authors:

    Transportation Research Board

  • Authors:
    • Wang, Chaojie
    • Gong, Siyuan
    • Peeta, Srinivas
  • Conference:
  • Date: 2019


  • English

Media Info

  • Media Type: Digital/other
  • Features: References; Tables;
  • Pagination: 6p

Subject/Index Terms

Filing Info

  • Accession Number: 01697426
  • Record Type: Publication
  • Report/Paper Numbers: 19-00155
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 7 2018 9:27AM