Concerning the large number of computing needs of vehicle task offloading and the limited computing capacity of local edge servers in the Internet of Vehicles （IoV）， a Hierarchical Resource Allocation Mechanism of cooperative mobile edge computing （HRAM） was proposed. In this algorithm， the computing resources of Mobile Edge Computing （MEC） servers were reasonably allocated and effectively utilized with a multi-layer architecture，so that the data multi-hop forwarding delay between different MEC servers was reduced， and the delay of task offloading requests was optimized. Firstly， the system model， communication model， decision model， and calculation model of the IoV edge computing were built. Next， the Analytic Hierarchy Process （AHP） was used to comprehensively consider multiple factors to determine the target server the offloaded task transferred to. Finally， a task routing strategy with dynamic weights was proposed to make use of communication capabilities of the overall network to shorten the request delay of task offloading. Simulation results show that compared with Resource Allocation of Task Offloading in Single-hop （RATOS） algorithm and Resource Allocation of Task Offloading in Multi-hop （RATOM） algorithm， HRAM algorithm reduces the request delay of task offloading by 40.16% and 19.01% respectively， and this algorithm can satisfy the computing needs of more offloaded tasks under the premise of meeting the maximum tolerable delay.