ABSTRACT
Modeling human mobility patterns from CDR(Call Detail Record) data is an efficient way to understand the effects of human movements on transportation, society and the environment. Previous human mobility models are focused on single cellphone network CDR data. In the poster, we present a framework to model human mobility patterns on CDR data from multiple cellphone networks. Based on data analysis from multiple cellphone networks, our target is to provide statistic features and mobility patterns in multiple granularities of spatio-temporal resolutions to support novel urban services. Compared with previous work, our approaches aim to establish a more diverse and more stable framework, which is a crucial prerequisite for various smart city services and applications.
- Sibren Isaacman, Richard A. Becker, Ramón Cáceres, Margaret Martonosi, James Rowland, Alexander Varshavsky, and Walter Willinger. 2012. Human mobility modeling at metropolitan scales. In The 10th International Conference on Mobile Systems, Applications, and Services, MobiSys'12, Ambleside, United Kingdom - June 25-29, 2012. 239--252. DOI:http://dx.doi.org/10.1145/2307636.2307659 Google ScholarDigital Library
- Fei Miao, Shuo Han, Shan Lin, John A. Stankovic, Qian Wang, Desheng Zhang, Tian He, and George J. Pappas. 2016. Data-Driven Robust Taxi Dispatch Approaches. In 7th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2016, Vienna, Austria, April 11-14, 2016. 37:1. DOI:http://dx.doi.org/10.1109/ICCPS.2016.7479094 Google ScholarCross Ref
- Desheng Zhang, Ye Li, Fan Zhang, Mingming Lu, Yunhuai Liu, and Tian He. 2013. coRide: Carpool Service with a Win-win Fare Model for Large-scale Taxicab Networks (SenSys '13).Google Scholar
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