TY - JOUR
T1 - IoV and blockchain-enabled driving guidance strategy in complex traffic environment
AU - Fu, Yuchuan
AU - Li, Changle
AU - Luan, Tom H.
AU - Zhang, Yao
N1 - Publisher Copyright:
© 2013 China Institute of Communications.
PY - 2023/12/1
Y1 - 2023/12/1
N2 - Diversified traffic participants and complex traffic environment (e.g., roadblocks or road damage exist) challenge the decision-making accuracy of a single connected and autonomous vehicle (CAV) due to its limited sensing and computing capabilities. Using Internet of Vehicles (IoV) to share driving rules between CAVs can break limitations of a single CAV, but at the same time may cause privacy and safety issues. To tackle this problem, this paper proposes to combine IoV and blockchain technologies to form an efficient and accurate autonomous guidance strategy. Specifically, we first use reinforcement learning for driving decision learning, and give the corresponding driving rule extraction method. Then, an architecture combining IoV and blockchain is designed to ensure secure driving rule sharing. Finally, the shared rules will form an effective autonomous driving guidance strategy through driving rules selection and action selection. Extensive simulation proves that the proposed strategy performs well in complex traffic environment, mainly in terms of accuracy, safety, and robustness.
AB - Diversified traffic participants and complex traffic environment (e.g., roadblocks or road damage exist) challenge the decision-making accuracy of a single connected and autonomous vehicle (CAV) due to its limited sensing and computing capabilities. Using Internet of Vehicles (IoV) to share driving rules between CAVs can break limitations of a single CAV, but at the same time may cause privacy and safety issues. To tackle this problem, this paper proposes to combine IoV and blockchain technologies to form an efficient and accurate autonomous guidance strategy. Specifically, we first use reinforcement learning for driving decision learning, and give the corresponding driving rule extraction method. Then, an architecture combining IoV and blockchain is designed to ensure secure driving rule sharing. Finally, the shared rules will form an effective autonomous driving guidance strategy through driving rules selection and action selection. Extensive simulation proves that the proposed strategy performs well in complex traffic environment, mainly in terms of accuracy, safety, and robustness.
KW - autonomous driving guidance
KW - blockchain
KW - communication range
KW - Internet of Vehicles
KW - reinforcement learning
UR - http://www.scopus.com/inward/record.url?scp=85159813866&partnerID=8YFLogxK
U2 - 10.23919/JCC.ea.2020-0174.202302
DO - 10.23919/JCC.ea.2020-0174.202302
M3 - 文章
AN - SCOPUS:85159813866
SN - 1673-5447
VL - 20
SP - 230
EP - 243
JO - China Communications
JF - China Communications
IS - 12
ER -