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Bus Stop Refinement Based on Hot Spot Extraction

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11448))

Abstract

During rush hour, numerous residents travel to their destinations by a multi-mode transfer way (e.g. bus & taxi) due to lack of direct buses, which sharply increases trip expense and even heavy traffic. The root of such inconvenience in bus service is that obsolete and incorrect bus stop information cannot satisfy residents’ time-dependent travel demand. In this work, we put forward a framework, called BSRF, to optimize the existing bus route using the mined bus stops from trajectory data of taxis’ short-haul order, including identifying candidate bus stop based on hot drop-off point and matching new bus stop with the existing bus line. We build a demo system to showcase the effectiveness of BSRF, which can offer reliable suggestion on bus stop setting for public transport companies.

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References

  1. Chen, C., Zhang, D., Li, N., Zhou, Z.: B-planner: planning bidirectional night bus routes using large-scale taxi GPS traces. Trans. Intell. Transp. Syst. 15(4), 1451–1465 (2014)

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Acknowledgements

The authors are very grateful to the editors and reviewers for their valuable comments and suggestions. This work is supported by NSFC (No. 61702423, U1501252).

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Correspondence to Jiali Mao .

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© 2019 Springer Nature Switzerland AG

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Xin, Y., Mao, J., Yu, S., Li, M., Jin, C. (2019). Bus Stop Refinement Based on Hot Spot Extraction. In: Li, G., Yang, J., Gama, J., Natwichai, J., Tong, Y. (eds) Database Systems for Advanced Applications. DASFAA 2019. Lecture Notes in Computer Science(), vol 11448. Springer, Cham. https://doi.org/10.1007/978-3-030-18590-9_89

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  • DOI: https://doi.org/10.1007/978-3-030-18590-9_89

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-18589-3

  • Online ISBN: 978-3-030-18590-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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