  This paper investigates autonomous driving safety improvement via task
offloading from cellular vehicles (CVs) to a multi-access edge computing (MEC)
server using vehicle-to-infrastructure (V2I) links. Considering that the latter
links can be reused by vehicle-to-vehicle (V2V) communications to improve
spectrum utilization, the receiver of the V2I link may suffer from severe
interference that can cause outages during the task offloading. To tackle this
issue, we propose the deployment of a reconfigurable intelligent computational
surface (RICS) whose computationally capable metamaterials are leveraged to
jointly enable V2I reflective links as well as to implement interference
cancellation at the V2V links. We devise a joint optimization formulation for
the task offloading ratio between the CVs and the MEC server, the spectrum
sharing strategy between V2V and V2I communications, as well as the RICS
reflection and refraction matrices to maximize an autonomous driving safety
task. Due to the non-convexity of the problem and the coupling among its free
variables, we transform it into a more tractable equivalent form, which is then
decomposed into three sub-problems solved via an alternate approximation
method. Our simulation results showcase that the proposed RICS-assisted
offloading framework significantly improves the safety of the considered
autonomous driving network, yielding a nearly 34\% improvement in the safety
coefficient of the CVs. In addition, it is demonstrated that the V2V data rate
can be improved by around 60\% indicating that the RICS-induced adjustment of
the signals can effectively mitigate interference at the V2V link.
