Abstract
AbstractUnmanned aerial vehicle (UAV) technology was introduced in traffic surveillance in sparse road networks, and a UAV allocation method with/without UAV continuous flight distance constraint was proposed. First, the method of choosing the surveillance targets was proposed. The UAV traffic surveillance problem without maximum flight distance constraint was then formulated as a traveling salesman problem, and the simulated annealing algorithm was introduced to solve this problem. As for UAV traffic surveillance problem with continuous flight distance constraint, the K-means clustering algorithm was used to divide the UAV surveillance area into multiple sub-zones to convert this problem into UAV traffic surveillance scenarios without continuous flight distance constraint. Finally, taking the Korla-Kuqa expressway of Xinjiang and its road network as the example, the proposed UAV-based traffic surveillance allocation method for sparse road networks was demonstrated and validated using several field experi...
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More From: Journal of Highway and Transportation Research and Development (English Edition)
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