The great improvement of traffic conditions has changed people's travel modes, and it has also made it difficult for the existing road network structure to meet the growing demand for transportation. Therefore, in order to improve the quality of the network connection and road network, and alleviate the urban traffic congestion, new path planning methods need to be adopted. One of the most prominent is the shortest path in edge computing. This paper mainly uses the comparative analysis and experimental methods to analyze the role of edge computing in the path planning of connected vehicles, and describes the resource allocation. In the experimental results, when the number of populations reaches 240, the number of iterations of the edge detection algorithm reaches a minimum of 21.8. This shows that the algorithm has a fast convergence speed and is suitable for the preliminary path planning of connected vehicles.
Connected Vehicle Path Planning and Resource Allocation in Edge Computing Environment
2022-11-01
1067276 byte
Conference paper
Electronic Resource
English
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