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Analysis of Traffic Flow Based on Toll Data

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DOI: 10.23977/ftte.2024.040102 | Downloads: 1 | Views: 49

Author(s)

Xiangmin Zhu 1, Jian Luo 2, Meng Yang 2

Affiliation(s)

1 Shandong Hi-speed Company Limited, Ji'nan, 250101, China
2 China Merchants Chongqing Communications Technology Research & Design Institute CO., LTD., Chongqing, China

Corresponding Author

Jian Luo

ABSTRACT

Utilizing data mining technology, this study proposes a methodology for traffic flow analysis based on toll data. Initially, the OD information pertaining to the analyzed toll station is extracted from expressway toll data. Subsequently, traffic flow analysis is conducted employing time series methods over various temporal scales, including years, months, and days. Comparative assessment of traffic flow across different road sections within the expressway network elucidates variations in traffic flow status. Quantitative analysis serves as the cornerstone for this investigation. Taking the Xi'an Ringo Expressway Toll Station as a case study, this paper delves into the temporal and spatial distribution of traffic flow along the roadway. The deterministic, explosive, and growth-type evaluation indices for the road network provide quantitative metrics for assessing the operational and managerial efficacy of the expressway. Moreover, the establishment of a visualization platform for public service facilitates the dissemination of theoretical frameworks and data-backed insights concerning road traffic flow and road network operations.

KEYWORDS

Expressway; Data mining; Traffic; OD

CITE THIS PAPER

Xiangmin Zhu, Jian Luo, Meng Yang, Analysis of Traffic Flow Based on Toll Data. Frontiers in Traffic and Transportation Engineering (2024) Vol. 4: 9-17. DOI: http://dx.doi.org/10.23977/ftte.2024.040102.

REFERENCES

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[2] Weng Jiancheng, Wang Yuanyuan, Rong Liang, et al. Expressway travel speed extraction model based on ETC transaction data [J]. Journal of Transport Information and Safety, 2017, 35(5):76-82.
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[5] Jiang Yiyue. Research on spatiotemporal correlation of traffic distribution based on highway toll data [D]. Beijing Jiaotong University, 2019.
[6] Han Kunlin. Research on highway abnormal state identification based on vehicle detector and toll data fusion [D]. Chongqing University, 2014.

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