A Collaborative Error Detection and Correction Scheme for Safety Message in V2X

Vehicle-to-Everything (V2X) technology plays a pivotal role in enabling real-time traffic coordination and safety, warning, and decision support. Within V2X, the Basic Safety Message (BSM) serves as the core to transmit critical vehicle status, location, and intention information to provide a foundation for ensuring reliable traffic safety and coordination mechanisms. Data accuracy stands as a key to the effectiveness and reliability of the V2X system, in which the transmission of error data can potentially result in severe traffic accidents. During vehicular operation, sensors may generate error data owing to looseness or external conditions. However, immediate sensor replacement is often impractical or infeasible. Therefore, this paper introduces a collaborative scheme involving vehicles, Road Side Units (RSUs), and Data Center (DC) to jointly enhance the accuracy of vehicle-transmitted BSMs. Our scheme involves analyzing statistical features of vehicle driving information to detect error BSMs. Subsequently, these detected errors are corrected by leveraging historical data from the vehicle and its relative relationship with surrounding vehicles. In addition, we propose a time optimization method to reduce the average processing time of each data by RSUs. The extensive experimental results demonstrate that the proposed scheme can accurately detect error BSMs and effectively correct error BSMs. The entire scheme also meets the requisite computational latency requirements.