Application of comprehensive traffic flow monitoring in vehicle path planning system

Zhen Ye; Zhengjun Liu; Boyuan Jiang; Zhirun Zhu; Gang Huang

doi:10.1117/12.2589347

27 January 2021 Application of comprehensive traffic flow monitoring in vehicle path planning system

Zhen Ye, Zhengjun Liu, Boyuan Jiang, Zhirun Zhu, Gang Huang

Proceedings Volume 11720, Twelfth International Conference on Graphics and Image Processing (ICGIP 2020); 117201K (2021) https://doi.org/10.1117/12.2589347
Event: Twelfth International Conference on Graphics and Image Processing, 2020, Xi'an, China

Abstract

In this paper, a new vehicle counting and traffic flow monitoring system is designed based on deep learning and image recognition. For accurate recognition of vehicles, Mask R-CNN model has been adopted and improved. Vehicle dataset is set up to obtain the corresponding model weight as recognition backbone in software. In addition, two counting methods, regional counting method and tracking counting method, have been analyzed and combined for effective counting. The experimental results show that the recognition rate of the proposed system is almost 100% and the counting rate is about 93.5%. According to the counting results, the planning requirement of vehicle path optimization is realized.

Citation Download Citation

Zhen Ye, Zhengjun Liu, Boyuan Jiang, Zhirun Zhu, and Gang Huang "Application of comprehensive traffic flow monitoring in vehicle path planning system", Proc. SPIE 11720, Twelfth International Conference on Graphics and Image Processing (ICGIP 2020), 117201K (27 January 2021); https://doi.org/10.1117/12.2589347

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