Characteristics analysis for travel behavior of transportation hub passengers using mobile phone data
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The travel behavior of passengers from the transportation hub within the city area is critical for travel demand analysis, security monitoring, and supporting traffic facilities designing. However, the traditional methods used to study the travel behavior of the passengers inside the city are time and labor consuming. The records of the cellular communication provide a potential huge data source for this study to follow the movement of passengers. This study focuses on the passengers’ travel behavior of the Hongqiao transportation hub in Shanghai, China, utilizing the mobile phone data. First, a systematic and novel method is presented to extract the trip information from the mobile phone data. Several key travel characteristics of passengers, including passengers traveling inside the city and between cities, are analyzed and compared. The results show that the proposed method is effective to obtain the travel trajectories of mobile phone users. Besides, the travel behavior of incity passengers and external passengers are quite different. Then, the correlation analysis of the passengers’ travel trajectories is provided to research the availability of the comprehensive area. Moreover, the results of the correlation analysis further indicate that the comprehensive area of the Hongqiao hub plays a relatively important role in passengers’ daily travel.
KeywordsMobile phone data Travel behavior Transportation hub Digital travel trajectory Correlation analysis
This study is partially supported by the Information Technology Research Project of Ministry of Transport of China (No. 2015364X16030) and the National Natural Science Foundation of China (No. 61620106002). The support provided by China Scholarship Council (CSC) during a visit of G. Zhong to UW-Madison is acknowledged.
Compliance with ethical standards
Conflict of interest
On behalf of all authors, the corresponding author states that there is no conflict of interest.
- Fang, J., Xue, M., Qiu, T.Z. (2014): Anonymous cellphone-based large-scale origin–destination data collection: case studies in China. In: Proceedings of Transportation Research Board 93rd Annual Meeting, Washington, D.C., No. 14-1567 (2014)Google Scholar
- Frias-Martinez, V., Soguero, C., Frias-Martinez, E.: Estimation of urban commuting patterns using cellphone network data. In: Proceedings of the ACM SIGKDD International Workshop on Urban Computing, Beijing, China, pp. 9–16 (2012)Google Scholar
- He, S., Cheng, Y., Ding, F., Zhang, J., Ran, B.: Extended Kalman filter-based freeway traffic state estimation using cellphone activity data. In: Proceedings of Transportation Research Board 95th Annual Meeting, Washington, D.C., No. 16-3728 (2016)Google Scholar
- Li, H.: Using mobile phone data to analyze origin–destination travel flow dynamics for city of Pasadena, CA and surrounding area. In: Proceedings of Transportation Research Board 94th Annual Meeting, Washington, D.C., No. 15-0804 (2015)Google Scholar
- Phithakkitnukoon, S., Horanont, T., Di Lorenzo, G., Shibasaki, R., Ratti, C.: Activity-aware map: identifying human daily activity pattern using mobile phone data. In: International Workshop on Human Behavior Understanding, Istanbul, Turkey, pp. 14–25 (2010)Google Scholar
- Rokib, S.A., Karim, M.A., Qiu, T.Z., Kim, A.: Origin–destination trip estimation from anonymous cell phone and foursquare data. In: Proceedings of Transportation Research Board 94th Annual Meeting, Washington, D.C., No. 15-2379 (2015)Google Scholar
- Shanghai City Comprehensive Transportation Planning Institute. The fourth travel survey of residents in Shanghai. Shanghai (2010)Google Scholar
- Shanghai Hongqiao Central Business District. Passenger flow information of Hongqiao hub in 2013. http://www.shhqcbd.gov.cn/html/shhq/shhq_2013/Info/Detail_6403.htm (2013). Accessed 15 May 2015
- Zhang, Y., Qin, X., Dong, S., Ran, B. (2010): Daily OD matrix estimation using cellular probe data. In: Proceedings of Transportation Research Board 89rd Annual Meeting, Washington, D.C., No. 10-2472 (2010)Google Scholar
- Zhong, G., Wan, X., Zhang, J., Yin, T., Ran, B.: Characterizing passenger flow for a transportation hub based on mobile phone data. IEEE T. Intell. Transp. 18(6), 1507–1518 (2017)Google Scholar