G.X. Gao, Y. Hong

Pages: 3-12

Abstract
Real time allocation of urban dynamic traffic flow can effectively improves urban traffic congestion and travel efficiency. Aiming at the problems of poor road network capacity and high traffic congestion index under the current allocation methods, this paper proposes a real-time allocation method of urban dynamic traffic flow in social governance. Firstly, use wireless sensor networks to collect real-time traffic flow data and perform dimensionality reduction processing on the collected data; Then, based on the data dimension reduction results, the urban dynamic traffic flow is predicted using the generated adversarial network; Finally, use the shortest path algorithm to allocate urban dynamic traffic flow in real time, calculate the shortest driving path of vehicles, and achieve optimal allocation of traffic flow. The experimental results show that the traffic congestion index and the road network capacity of the proposed method in this article are effectively improved. The research results provide a new approach to preventing congestion and improving traffic efficiency.
Keywords: social governance; urban transportation; generative adversarial network; shortest path algorithm