A Dynamic Evolution Method for Autonomous Vehicle Groups in an Urban Scene

Guiyuan Yuan, Jiujun Cheng, Mengchu Zhou, Sheng Cheng, Shangce Gao, Changjun Jiang, Abdullah Abusorrah

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Accurately processing dynamic evolution events is extremely challenging for autonomous vehicle groups in an urban scene, which can be disturbed by manned vehicles, roadside obstacles, traffic lights, and pedestrians. Existing work focuses on a dynamic evolution method for such groups in a highway scene only. Its outcomes cannot be directly used to an urban scene due to different environmental factors, incomplete dynamic evolution events, and lack of simulation evaluation with real road networks. In this work, we present a dynamic evolution method for such groups in an urban scene. First, we analyze their dynamic evolution reasons. Then, we abstract five dynamic evolution events, i.e., joining, leaving, merging, splitting, and disappearing, and introduce a dynamic evolution method to process them. Finally, we deduce the evolvability that can reflect dynamic evolution states of a vehicle group. The simulation results in synthetic and real urban scenes show that the connectivity, coupling, timeliness, and evolvability of vehicle groups using the proposed dynamic evolution method are higher than those of using a dynamic evolution method for a highway scene.

Original languageEnglish (US)
Pages (from-to)3450-3460
Number of pages11
JournalIEEE Transactions on Systems, Man, and Cybernetics: Systems
Issue number6
StatePublished - Jun 1 2023

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Systems Engineering
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering


  • Autonomous vehicle group
  • dynamic evolution event
  • dynamic evolution event processing
  • evolvability
  • urban scene


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