Traffic flow prediction algorithm of dangerous curved slope section based on random forest algorithm and open source cloud computing platform

Hongtao Ni; Lixia Yan

doi:10.1117/12.3011958

7 December 2023 Traffic flow prediction algorithm of dangerous curved slope section based on random forest algorithm and open source cloud computing platform

Hongtao Ni, Lixia Yan

Author Affiliations +

Proceedings Volume 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023); 129411N (2023) https://doi.org/10.1117/12.3011958
Event: Third International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 203), 2023, Yinchuan, China

Abstract

In order to improve the accuracy of traffic flow prediction on dangerous curve sections and shorten the time consumption, this paper designs a traffic flow prediction algorithm on dangerous curve sections based on Random Forest algorithm and open-source cloud computing platform. Firstly, collect traffic flow data for dangerous bend slope sections, and design a traffic flow data storage system architecture for dangerous bend slope sections based on open-source cloud computing using Ceph open-source distributed storage system; Then, the stored data is repeatedly cleaned, and the cleaned data is used as the test data. Finally, a traffic flow prediction algorithm based on Random Forest is designed for dangerous curve sections. So far, the design of traffic flow prediction algorithm for dangerous curve sections based on Random Forest algorithm and open-source cloud computing platform has been completed. The experimental results show that the overall effect of the traffic flow forecast of the dangerous curve slope section designed in this paper is good. When the number of vehicles reaches 150, the prediction error of the proposed method is only 6.17%, and the prediction time is 12.4 s. It is proved that the design method in this paper can significantly improve the traffic flow prediction of dangerous curve slope sections and can be used in dangerous curve slope sections.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Hongtao Ni and Lixia Yan "Traffic flow prediction algorithm of dangerous curved slope section based on random forest algorithm and open source cloud computing platform", Proc. SPIE 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023), 129411N (7 December 2023); https://doi.org/10.1117/12.3011958

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KEYWORDS

Random forests

Cloud computing

Data storage

Data modeling

Roads

Data analysis

Computer architecture

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