An Autonomous Vehicle Group Formation Method based on Risk Assessment Scoring

Document Type

Conference Proceeding

Publication Date

1-1-2022

Abstract

Forming a secure autonomous vehicle group is extremely challenging since we have to consider threats and vulnerability of autonomous vehicles. Existing studies focus on communications among risk-free autonomous vehicles, which lack metrics to measure passenger security and cargo values. This work proposes a novel autonomous vehicle group formation method. We introduce risk assessment scoring to assess passenger security and cargo values, and propose an autonomous vehicle group formation method based on it. Our vehicle group is composed of a master node, and a number of core and border ones. Finally, the extensive simulation results show that our method is better than a Connectivity Prediction-based Dynamic Clustering model and a Low-InDependently clustering architecture in terms of node survival time, average change count of master nodes, and average risk assessment scoring.

Identifier

85145353149 (Scopus)

ISBN

[9781665462976]

Publication Title

Proceedings of the 2022 IEEE International Conference on Dependable Autonomic and Secure Computing International Conference on Pervasive Intelligence and Computing International Conference on Cloud and Big Data Computing International Conference on Cyber Science and Technology Congress Dasc Picom Cbdcom Cyberscitech 2022

External Full Text Location

https://doi.org/10.1109/DASC/PiCom/CBDCom/Cy55231.2022.9927817

Grant

61872271

Fund Ref

National Natural Science Foundation of China

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