Short-term Traffic Volume Forecasting Based on ARMA and Kalman Filter
[1]Yang Gaofei,Xu Rui,Qin Ming,et al.Short-term Traffic Volume Forecasting Based on ARMA and Kalman Filter[J].Journal of Zhengzhou University (Engineering Science),2017,38(02):36-.[doi:10.13705/j.issn.1671-6833.2017.02.009]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
38卷
Number of periods:
2017 02
Page number:
36-
Column:
Public date:
2017-04-28
- Title:
- Short-term Traffic Volume Forecasting Based on ARMA and Kalman Filter
- Keywords:
-
intelligent transportation; short-term traffic volume forecasting; ARMA; Kalman filter; prediction error
- CLC:
- -
- DOI:
- 10.13705/j.issn.1671-6833.2017.02.009
- Abstract:
- The traffic prediction was an important component in the intelligent transportation system.The effective short-term traffic flow prediction was conducive to ensure the intersection unimpeded and reduce the traffic delay.According to the uncertainty of road conditions and the nonlinear change of traffic flow,the ARMA model and kalman filter mode was combined through the error magnitude of predicting results to predict the short-term traffic flow in the road.The example indicated that the combined model could achieve the higher prediction precision and made the prediction accuracy up to 5.79 percent.Besides,the combined model had an advantage over the single model in the forecasting accuracy.The combined model can not only predict the short-term traffic flow more accurately,but provided the necessary theoretical basis and technical guidance for the intersection signal timing.Besides,it had definitely application value in reducing the traffic delay and improving the road service level.
- References:
- -
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