The New Intelligent Prediction for Bus Congestion Based on History Information Processing

The volume of traffic has increased in urban areas because of the expansion of modern cities and towns and the continued rapid urbanization, especially the mega city. To tackle this problem, governments tend to propose and strengthen the bus congestion coordination while the research about analyzation of the bus operation and congestion prediction are underdeveloped, which are vital to ensure traffic unhampered. In this paper, a new model, including the improved gold segmentation method and the intersection for cast supported by the PSO-SVM and ARIMA forecasting model, is applied in data processing and an accurate congestion prediction, applying data support for bus operators, scheduling, service level evaluating and route planning.