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Short‐Term High-Speed Traffic Flow Prediction Based on ARIMA-GARCH-M Model

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Abstract

The traditional traffic flow prediction model acquired the poor characteristics of the traffic flow time series, which led to the low prediction accuracy. Therefore, the short-term high-speed traffic flow prediction based on arima-garch-m model was proposed. According to the urban traffic flow theory, ARIMA model and GARCH model are combined to obtain the corresponding fluctuation characteristics and realize the prediction of traffic flow. The experimental results show that the NRMSE and MAPE of the model in this paper are only 3.13 % and 8.76 %, respectively, with good prediction accuracy and better stability and accuracy than the other two models, proving that the model has good performance and can meet the needs of practical application.

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Acknowledgements

This work is supported by Innovation Fund for Production, Education and Research of Universities and Colleges -New-generation Information Innovation Project Initiated by Science and Technology Development Center, Ministry of Education (No. 2018A02025).

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  1. Department of Economic and Management, Fuzhou Polytechnic, Fuzhou, 350108, China

    Xianfu Lin & Yuzhang Huang

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  1. Xianfu Lin
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  2. Yuzhang Huang
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Correspondence to Xianfu Lin.

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Lin, X., Huang, Y. Short‐Term High-Speed Traffic Flow Prediction Based on ARIMA-GARCH-M Model . Wireless Pers Commun 117, 3421–3430 (2021). https://doi.org/10.1007/s11277-021-08085-z

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  • DOI: https://doi.org/10.1007/s11277-021-08085-z

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