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

Document Type

Article

Publication Date

6-1-2023

Abstract

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.

Identifier

85146238162 (Scopus)

Publication Title

IEEE Transactions on Systems Man and Cybernetics Systems

External Full Text Location

https://doi.org/10.1109/TSMC.2022.3226424

e-ISSN

21682232

ISSN

21682216

First Page

3450

Last Page

3460

Issue

6

Volume

53

Grant

23K24899

Fund Ref

Japan Society for the Promotion of Science

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