Traffic Problems of Linjiao's Turning Passage in Lhasa City from the Perspective of Traffic Sociology

Abstract

The transportation problem of Linjiao transit passage in Lhasa City from the perspective of traffic sociology is studied.Methods: Firstly, the research history and current situation of experts in the field of traffic congestion prediction are studied. The common parameters and models of congestion prediction are analyzed. Results:Combined with the complexity of road traffic structure and the possession of a large number of high-dimensional traffic data records, the use of a prediction model is finally determined based on RNN-RBM deep learning network. Through the research and analysis of all-day road traffic flow data, accurate judgment and prediction of traffic congestion status are made. Conclusion: In this paper, the role of the RNN model on the time axis and the state judgment of the RBM network are used to predict the traffic congestion based on the characterization of the congestion sequence.