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Traffic Flow Fluctuation Analysis Based on Beijing Taxi GPS Data

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Knowledge Science, Engineering and Management (KSEM 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11062))

Abstract

The processes of urbanization and the expansion of urban scale are growing rapidly in China. Therefore, it is important to determine the influencing factors of the traffic flow. In order to evaluate the impact of internal and external flows, the area inside the Five Ring of Beijing is divided into several square-shaped areas. Each segment is defined as a node, and traffic flows between nodes serve as edges of a network. Then a traffic network is constructed based on above. After that, an empirical analysis of the network is implemented to reveal the dynamic changes of the power law exponent that characterizes the relationship between the mean value and division of traffic flows among nodes, in order to discover the fluctuation of traffic flow. The results show that, when the time interval is small, the internal flow and the external flow have similar effect on the traffic network. With the increase of time interval, the external flow has a greater influence on the network, rather than the internal traffic flow. This paper can help government officials in implementing the regulation of traffic.

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Acknowledgement

The authors would like to thank all editors and the anonymous reviewers for their constructive comments and suggestions. This work is supported by Fundamental Research Funds for the Central Universities (No. XDJK2016B029), the National Natural Science Foundation of China (Nos. 61403315, 61402379) and Natural Science Foundation of Chongqing (No.cstc2018jcyjAX0274), and in part by the Training Programs of Innovation and Entrepreneurship for Undergraduates of Southwest University (20173601001).

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Correspondence to Xianghua Li .

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Guo, J., Li, X., Zhang, Z., Zhang, J. (2018). Traffic Flow Fluctuation Analysis Based on Beijing Taxi GPS Data. In: Liu, W., Giunchiglia, F., Yang, B. (eds) Knowledge Science, Engineering and Management. KSEM 2018. Lecture Notes in Computer Science(), vol 11062. Springer, Cham. https://doi.org/10.1007/978-3-319-99247-1_40

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  • DOI: https://doi.org/10.1007/978-3-319-99247-1_40

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-99247-1

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