论文标题

节能高清地图数据分配机制,用于自动驾驶

An Energy-Efficient High Definition Map Data Distribution Mechanism for Autonomous Driving

论文作者

Xie, Jinliang, Tang, Jie, Liu, Shaoshan

论文摘要

现在,自动驾驶是运输的前途未来。作为自主驾驶的一个基础,高清图(HD MAP)提供了对环境的高精度描述,因此可以更准确地感知和本地化,同时提高路径计划的效率。但是,在驾驶过程中需要传输大量的地图数据,因此对自动驾驶的实时和安全要求构成了巨大挑战。为此,我们首先演示了现有的数据分配机制如何支持高清地图服务。此外,考虑到车辆电源,车速,基站带宽等的限制,我们提出了在车辆到基础设施(V2I)数据传输之上的高清图数据分配机制。通过这种机制,将MAP配置任务分配给所选的RSU节点,并合作传输相符的HD MAP数据。他们在地图数据加载上的作品旨在通过优化的车载能源消耗来提供高清地图数据服务。最后,我们将RSU节点的选择对部分背包问题进行建模,并提出基于贪婪的策略数据传输算法。实验结果证实,在有限的能源消耗中,提出的机制可以通过协调多个RSU与最短数据传输时间来确保HD MAP数据服务。

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.

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