关键词: 智能交通, 交通流量预测, 多维时间序列模型, 电子不停车收费, 相似性度量

Abstract:

ETC short term traffic flow prediction is one of the fundamental processes in ETC management. The precise prediction of traffic flow provides instructions for transportation hub management solution planning and ETC lane construction. At present, some of studies are proposed in forecasting short term traffic flow. However, most studies of model presentation are in the form of mathematical expressions, and it is difficult to describe the trend accurately. Therefore, an ETC short term traffic flow prediction model based on multidimensional time series is proposed, which takes the effect of external factors like holiday, the free of highway and weather etc. into consideration. Moreover, considering the fact of the traffic restrictions based on the last digit of license plate numbers somewhere, the day of week factor is considered in this prediction model. The traffic flow data of highway ETC lane somewhere is used for prediction. The prediction results indicate that the total average absolute relative error is 8.10%. The accuracy suggests its advantage in traffic flow prediction and on site application.

Key words: intelligent transportation, traffic flow prediction, multidimensional time series model, electronic toll collection (ETC), similarity measure