An Energy-Efficient High Definition Map Data Distribution Mechanism for Autonomous Driving
This addresses real-time and safety issues in autonomous driving by optimizing energy use during map data distribution, though it is incremental as it builds on existing V2I frameworks.
The paper tackles the challenge of transmitting large High Definition Map data for autonomous driving under energy and bandwidth constraints by proposing a Vehicle-to-Infrastructure mechanism that coordinates multiple RSUs to distribute map data efficiently. Experimental results show it ensures HD map service with the shortest transmission time while limiting energy consumption.
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.