边缘计算对自动驾驶的好处的测量

Yang Yu, Sanghwan Lee
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引用次数: 1

摘要

随着自动驾驶(AD)水平的提高,单辆车的传感器数量也在增加,所需的计算能力也在迅速提高。人工智能的智能水平取决于算法和硬件性能。然而,由于生产成本或计算资源有限等问题,一些车辆可能没有足够的计算能力来实现高水平的自动驾驶。为了克服这些障碍,基于边缘计算的分布式AD系统架构已成为一种趋势。我们在机器人操作系统(ROS2)的基础上构建了一个基于边缘计算的分布式AD系统,并在不同的设置下对其性能进行了测试。我们的测试结果表明了以边缘计算单元为中心的AD系统的可行性,这为以更多样化的方式利用边缘计算开辟了新的研究方向。
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Measurements of the Benefits of Edge Computing on Autonomous Driving
As the level of autonomous driving(AD) increases, the number of sensors in a single vehicle increases, and the required computing power also increases rapidly. The intelligence level of AD depends on algorithms and hardware performance. However, due to the problems such as limited production cost or computing resources, some vehicles may not have enough computation power for high level of AD. To overcome such obstacles, the distributed AD system architecture based on edge computing has become a trend. We build an edge computing-based distributed AD system on top of Robot Operating System(ROS2) and measure the performance with different settings. Our test results show the feasibility of AD systems centered on edge computing units, which open new research directions for exploiting edge computing in a more diverse way.
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