Study On The Highway Traffic Volume Prediction Based On Toll Station Big Data

Traffic volume represents the achievement of transportation development, which is the core indication of transportation development contribution, development construction and development quality. At present, the statistical prediction of highway transportation volume is basically conducted by Highway and Waterway Transportation Statistics Implement Program released by the Ministry of Transportation, according to the sampling survey method, whose result is interfered by many factors and meanwhile some feature samples is easy to get lost, so the predicted result is not accurate enough. Chinese economic development is at the crucial transitional phase, but the conventional statistics of highway transportation cannot report the transporting achievement timely and effectively. Real and reliable transportation statistics is the basis for the enaction of relative policies and regulations, the supervision of transportation industry, the monitoring of industry operating and the guidance of transportation market.This thesis puts forward a new predicting method of regional highway transportation volume based on highway network tolling statistics. By the adoption of big data mining analysis technology, this paper will calculate and analyze the highway network data all over the country, and predict the regional highway transportation volume by the application of the improved four-stage method, a combination of the traditional four-stage method and the practical situation.Taking the Fujian province as the example of highway transportation volume prediction,the research result can show that four-stage method is effective in operable, reliable and stable.This research method can be promoted to other provinces in highway transportation volume prediction, which can support the efficient analysis of highway transportation volume development in our country.