In the foreseeable Intelligent Transportation System (ITS), Intelligent Connected Vehicles (ICVs) will play an important role in improving travel efficiency and safety. However, it is challenging for ICVs to support the resource-hungry autonomous driving applications due to the limitation of hardware computing power. Fortunately, the emergence of Multi-access Edge Computing (MEC) helps overcome this limitation effectively. In this paper, we investigate the vehicle and edge server collaborative computation offloading problem by jointly optimizing the partial offloading ratio and resource allocation ratio.