TY - GEN
T1 - An Autonomous Vehicle Group Formation Method based on Risk Assessment Scoring
AU - Cheng, Jiujun
AU - Hou, Mengnan
AU - Zhou, Meng Chu
AU - Yuan, Guiyuan
AU - Mao, Qichao
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
KW - autonomous vehicle group
KW - risk assessment scoring
KW - vehicle group formation
UR - http://www.scopus.com/inward/record.url?scp=85145353149&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85145353149&partnerID=8YFLogxK
U2 - 10.1109/DASC/PiCom/CBDCom/Cy55231.2022.9927817
DO - 10.1109/DASC/PiCom/CBDCom/Cy55231.2022.9927817
M3 - Conference contribution
AN - SCOPUS:85145353149
T3 - 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
BT - 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
A2 - Fortino, Giancarlo
A2 - Gravina, Raffaele
A2 - Guerrieri, Antonio
A2 - Savaglio, Claudio
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 20th IEEE International Conference on Dependable, Autonomic and Secure Computing, 20th IEEE International Conference on Pervasive Intelligence and Computing, 7th IEEE International Conference on Cloud and Big Data Computing, 2022 IEEE International Conference on Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2022
Y2 - 12 September 2022 through 15 September 2022
ER -