Parked Vehicle (PV) assistance in vehicular edge computing and networks is proposed to exploit underutilized computing resources from PVs for enhancing the resource capacity at the edge vehicular network. Containerization is used to improve task execution of PVs with fast start-up time, less hardware overheads and safe resource isolation. To this end, we introduce a task-container matching market to provide on-demand offloading services. For network implementation, the related entities including requesters, PVs with containers as performers and a service provider are described. Considering parking behaviors and resource availability, we measure the serviceabilities of PVs to select appropriate PVs for reliable and efficient task processing. According to utility functions, preference profiles of requesters and performers in the task-container matching market are modeled through the best response analysis. Finally, we apply matching game approach to cope with associations between tasks and containers deployed inside PVs. Numerical results demonstrate that compared with baseline schemes, our scheme accomplishes more tasks and acquires a higher overall utility in computation offloading.