Abstract
Human mobility data play an important role in addressing various urban issues. However, when a new mobility paradigm emerges and continuously evolves with time, it is usually hard to obtain a large-scale and evolving mobility dataset due to various factors such as social and privacy concerns. In this paper, we focus on modeling the evolving mobility of metropolitan-scale electric taxis (ETs), which have different mobility patterns with petroleum vehicles and continuously evolve with the expansion of the ET fleet and the charging station network. To this end, the E2M system is proposed to generate trajectories for large-scale ET fleets by learning the mobility from only a small-scale ET fleet and the corresponding charging station network. First, the ET mobility is decomposed and modeled with transition, charging, and resting patterns. Second, the E2M system generates trajectories with a fleet generation algorithm. Extensive experiments are conducted on a real-world dataset, which has ET trajectories during both the early stage and mature stage in the taxi electrification process in Shenzhen, China, and the results verify the effectiveness of E2M.
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Acknowledgements
This work was supported in part by the National Key Research and Development Program of China under Grant 2018AAA0101200; in part by the National Natural Science Foundation of China under Grant 61972044 and Grant 61732017; in part by the Fundamental Research Funds for the Central Universities under Grant 2020XD-A09-3; in part by the Funds for International Cooperation and Exchange of NSFC under Grant 61720106007; and in part by the 111 Project under Grant B18008.
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Wang, Y., Wang, H., Zhao, D., Yang, F., Ma, H. (2022). E2M: Evolving Mobility Modeling in Metropolitan-Scale Electric Taxi Systems. In: Wang, L., Segal, M., Chen, J., Qiu, T. (eds) Wireless Algorithms, Systems, and Applications. WASA 2022. Lecture Notes in Computer Science, vol 13471. Springer, Cham. https://doi.org/10.1007/978-3-031-19208-1_11
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DOI: https://doi.org/10.1007/978-3-031-19208-1_11
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