Search

With the continuous growth of vehicle ownership and the popularization of Internet of Vehicles applications， vehicle terminals generate large amounts of data messages that need to be processed in real time. In the scene of high-speed vehicle movement， the traditional Internet of Vehicles navigation system has a transmission delay due to vehicle differential positioning data， which results in a certain deviation in vehicle positioning results and cannot obtain high-precision positioning results in time. Based on this， this paper proposes a technology solution for car networking navigation based on BDS positioning and edge computing. It uses an improved genetic algorithm to allocate resources for terminal positioning requests， effectively reduces the service delay of the entire edge network， and uses optimize the lossless Kalman filter algorithm based on edge node to improve the positioning accuracy of the car network node. Experiments show that the method proposed in this paper can provide real-time accurate， low-latency and high-precision positioning services for large-scale Internet of Vehicles terminals， and has high practical application value. [ABSTRACT FROM AUTHOR]