Spatio-temporal data analysis and accessibility method for IoV in an urban scene - Jiujun CHENG; Guiyuan YUAN; Jie CUI; Aiguo ZHOU; Bo LYU; Guangyao LI (Tongxin xuebao)
In order to solve the problems of diversity spatio-temporal data and low connectivity efficiency in a single road side unit for Internet of vehicles (IoV) in an urban scene, a spatio-temporal data analysis and accessibility method was presented.First, a spatio-temporal data analysis method based on de-noising and data filling was introduced, and a tensor factor aggregation-based neural network was constructed to predict connectivity intensity among vehicles.Then, a connectivity intensity prediction-based accessibility method was proposed.The simulation results demonstrate that the proposed connectivity intensity prediction method can accurately predict connectivity intensity among vehicles, and the proposed accessibility method can effectively reduce connectivity redundancy and loads of road side units.