Semantic Fusion Infrastructure for Unmanned Vehicle System Based on Cooperative 5G MEC

Since local sensing system is inherently limited, it is a trend to combine Cooperative Vehicle Infrastructure System (CVIS) and autonomous driving technologies to address the limitations of the vehicle-centric perception. However, problems such as high vehicle cost and perception limitations still exist. In this paper, from the perspective of distributed cooperative processing, a scalable 5G multi-access edge computing (MEC) driven vehicle infrastructure cooperative system is proposed. Based on the edge offload capability of 5G MEC, this system supports mapping sensor observations into a semantic description of the vehicle's environment. Through interactive perception fusion, it provides environment awareness of high-precision maps for autonomous driving. The experiment confirms that the cooperative sensing network can achieve 33 fps and improve the detection precision by around 10% as opposed to the typical detection method. In addition, compared with single viewpoint perception, the accuracy of the fusion scheme is further improved. In particular, over the 5G telecommunication network, the cooperative system can be more scalable to connect distributed sensors and is expected to lead to efficient autonomous driving.

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