Abstract
An analysis of urban traffic operation pattern and spatiotemporal mode is an important basis to solve the problems of traffic congestion, emergency and extreme weather. Traditional studies on the urban traffic operation pattern and spatiotemporal mode usually are restricted by issues as poor time effectiveness, large space scale and coarse time granularity of traffic flow data, thus this essay choose to use the urban traffic speed data based on floating vehicle trajectory to dissect the urban traffic operation pattern and spatiotemporal mode in Beijing in a multi-dimensional and fine granularity. Differences of features in weekdays and weekends are also compared. This paper reports that “two-peak” mode is obvious in the urban traffic condition. Besides, the morning peak of weekends is postponed to 11-12 am, and the night peak appears shorter in 5 pm compared to weekdays. Finally, four modes of traffic and its driving mechanism are concluded.
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Acknowledgment
The authors would like to thank the support of the National Natural Science Foundation of China (Study on Pre-qualification Theory and Method for Influences of Disastrous Meteorological Events, Grant No. 91224004), the youth talent plan program of Beijing City College (Study on Semantic Information Retrieval of Decision Analysis of Emergency Management for Typical Disastrous Meteorological Events, Grant No. YETP0117) and the National Natural Science Foundation of China (Key Scientific Problems and Integrated Research Platform for Scenario Response Based National Emergency Platform System, Grant No. 91024032) and Key Program of the National Natural Science Foundation of China, No. 71433008 and Key Research Program of the Chinese Academy of Sciences, No. KZZD-EW-06-04.
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Sun, C., Deng, Y., Tang, B., Zhong, S. (2016). Urban Traffic Operation Pattern and Spatiotemporal Mode Based on Big Data (Taking Beijing Urban Area as an Example). In: Bian, F., Xie, Y. (eds) Geo-Informatics in Resource Management and Sustainable Ecosystem. GRMSE 2015 2015. Communications in Computer and Information Science, vol 569. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49155-3_4
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DOI: https://doi.org/10.1007/978-3-662-49155-3_4
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