  Enabling high-definition (HD)-map-assisted cooperative driving among
autonomous vehicles (AVs) to improve the navigation safety faces technical
challenges due to increased communication traffic volume for data dissemination
and increased number of computing/storing tasks on AVs. In this article, a new
architecture that combines multi-access edge computing (MEC) and
software-defined networking (SDN) is proposed for flexible resource management
and enhanced resource utilization. With MEC, the interworking of multiple
wireless access technologies can be realized to exploit the diversity gain over
a wide range of radio spectrum, and at the same time, computing/storing tasks
of an AV are collaboratively processed by servers and other AVs. Moreover, by
enabling SDN and network function virtualization (NFV) control modules at each
cloud-computing and MEC server, an efficient resource allocation framework is
proposed to enhance global resource sharing among different network
infrastructures. A case study is presented to demonstrate the effectiveness of
the proposed resource allocation framework.
