To address the serious problem of delay and energy consumption increase and service quality degradation caused by complex network status and huge amounts of computing data in the scenario of vehicle-to-everything (V2X), a vehicular network architecture combining Multi-Access Edge Computing (MEC) is constructed. MEC services the edge of the wireless network to compensate for the delay fluctuation caused by remote cloud computing. By modeling the MEC-based V2X offloading and resource allocation in a typical 4-leg unsignalized intersection, the optimal offloading decision, communication and computing resource allocation scheme are derived. The waste of communication resources caused by the uneven distribution of vehicles on each entrance is reduced obviously. An experiment is conducted and the results showed that, as compared to other mechanisms, the proposed mechanism can utilize MEC resources and reduce system cost-effectively.