  Autonomous Driving is now the promising future of transportation. As one
basis for autonomous driving, High Definition Map (HD map) provides
high-precision descriptions of the environment, therefore it enables more
accurate perception and localization while improving the efficiency of path
planning. However, an extremely large amount of map data needs to be
transmitted during driving, thus posing great challenge for real-time and
safety requirements for autonomous driving. To this end, we first demonstrate
how the existing data distribution mechanism can support HD map services.
Furthermore, considering the constraints of vehicle power, vehicle speed, base
station bandwidth, etc., we propose a HD map data distribution mechanism on top
of Vehicle-to-Infrastructure (V2I) data transmission. By this mechanism, the
map provision task is allocated to the selected RSU nodes and transmits
proportionate HD map data cooperatively. Their works on map data loading aims
to provide in-time HD map data service with optimized in-vehicle energy
consumption. Finally, we model the selection of RSU nodes into a partial
knapsack problem and propose a greedy strategy-based data transmission
algorithm. Experimental results confirm that within limited energy consumption,
the proposed mechanism can ensure HD map data service by coordinating multiple
RSUs with the shortest data transmission time.
