Research on Traffic Flow Prediction Based on ARIMA Model

Jiamu He

2024

Abstract

Nowadays, road traffic has become the most mainstream mode of transportation, and its impact on people's lives is significant in terms of transportation efficiency and safety. Therefore, the accurate prediction of traffic flow is a research topic with high application value. This paper aims to establish a model for fitting and predicting the collected traffic flow data. Firstly, the ADF test will be conducted along with ACF and PACF plots to determine the approximate range of each input parameter of the model. Then, ARIMA models with different parameters will be applied to fit the data, and their mean square errors will be compared to identify the best-fitting model. The result indicates that the fitted values of this model closely align with the distribution of actual values, this proves the feasibility of ARIMA model for traffic flow fitting. Finally, the study will utilize this model to forecast data changes over a period of time in the future.

Paper Citation

in Harvard Style

He J. (2024). Research on Traffic Flow Prediction Based on ARIMA Model. In Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI; ISBN 978-989-758-713-9, SciTePress, pages 16-21. DOI: 10.5220/0012887800004508

in Bibtex Style

@conference{emiti24,
author={Jiamu He},
title={Research on Traffic Flow Prediction Based on ARIMA Model},
booktitle={Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI},
year={2024},
pages={16-21},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012887800004508},
isbn={978-989-758-713-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI
TI - Research on Traffic Flow Prediction Based on ARIMA Model
SN - 978-989-758-713-9
AU - He J.
PY - 2024
SP - 16
EP - 21
DO - 10.5220/0012887800004508
PB - SciTePress