To circumvent the poor prediction accuracy of traffic volume models available due to the lack of traffic data and inaccurate judgments on the traffic influence factors, in this paper we established a traffic volume prediction model using grey forecasting model GM(1,1) based on the real traffic data from the highway toll database. The GM(1,1) method has advantage of the strong adaptiveness to Complex system, thus getting a great advantage over other methods for modeling such a complex nonlinear traffic volume system with many uncertain influence factors. Simulation results show that our GM(1,1) model has mean relative prediction error of 3.9%, which accomplishes our intended prediction accuracy.
Modeling Traffic Volume Based on Highway Toll Database Using GM (1,1)
Applied Mechanics and Materials ; 66-68 ; 563-568
2011-07-04
6 pages
Article (Journal)
Electronic Resource
English
SimToll: A Highway Toll, Lane Selection, and Traffic Modeling Dataset
Springer Verlag | 2023
|SimToll: A Highway Toll, Lane Selection, and Traffic Modeling Dataset
Springer Verlag | 2023
|Toll bridge influence on highway traffic operation
Engineering Index Backfile | 1947
|Highway Toll Management and Traffic Prediction Using Data Mining
Springer Verlag | 2020
|