Blockchain-Enabled Internet of Vehicles With Cooperative Positioning: A Deep Neural Network Approach
Yanxing Song, Yuchuan Fu, F. Richard Yu, Li Zhou
Abstract
Although vehicular global positioning system (GPS) has been widely applied in many traffic scenarios, it is far from achieving lane-level positioning due to its low accuracy. Existing cooperative positioning (CP) methods have improved vehicular positioning accuracy to varying degrees, which still have challenges in further improving the system's robustness and security. In this article, we propose a novel framework of blockchain-enabled Internet of Vehicles (IoV) with CP for improving vehicular GPS positioning accuracy, system robustness, and security. First, a self-positioning correction scheme for the intelligent vehicles is proposed to improve their positioning accuracy, which uses the multitraffic signs as benchmarks to correct the vehicular position (given by GPS) by deep neural network (DNN) algorithm. We further design a multi-intelligent vehicle positioning error sharing model to reduce GPS positioning error of common vehicles (CoVs) in the same segment or area. In addition, to realize information sharing between vehicles and ensure system security, the connections among intelligent vehicles, CoVs, and roadside units are built by proposing a blockchain-enabled architecture that includes IoV subsystem and blockchain subsystem, where the corresponding mechanism of the information choosing, information sharing, and penalty is designed. Extensive simulation results show the accuracy, robustness, and security of our proposal in terms of vehicular positioning, information transferring, and sharing.