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Two Way Allocation Methods in SAVS for Large Depopulated Area

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Part of the book series: Proceedings in Adaptation, Learning and Optimization ((PALO,volume 12))

Abstract

In depopulated areas, many areas are introducing On-Demand transportation to improve local traffic. Hiyama southern region is a depopulated area located in the southern part of Hokkaido. It is necessary to secure efficient means of transportation due to the decline of the means of transportation and the aging of the area. This research aims to introduce Smart Access Vehicle Service (SAVS) for wide and depopulated area. In order to introduce SAVS in Hiyama southern region, it analyzed problems and issues with SAVS simulation. From the analysis results, an improved assignment algorithm was proposed and analyzed by simulation.

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References

  1. Noda, I., Shinoda, K., Ohta, M., Nakashima, H.: Evaluation of usability of dial-a-ride system using simulation. Inf. Process. Soc. J. 49(1), 242–252 (2008)

    Google Scholar 

  2. Tsubouchi, K., Yamato, H., Hiekata, K.: On the advantage of the on-demand bus system in less populated area. J. Robot. S. Jpn. 27(1), 115–121 (2009)

    Article  Google Scholar 

  3. Yamato, H., Tsubouchi, K., Hiketa, K.: A research on real-time scheduling algorithm for on-demand bus and evaluation by simulation. Transp. Policy Stud. Rev. 10(4), 02–10 (2008)

    Google Scholar 

  4. Koshiba, H., Noda, I., Yamashita, T., Nakashima, H.: Evaluation of Demand Bus for Real Operation by Bus Simulator SAVSQUID Considering Real Environment. Computer software journal 31(3), 141–155 (2014)

    Google Scholar 

  5. Nakashima, H., Noda, I., Matsubara, H., Hirata, K., Tayanagi, E., Shiraishi, Y., Sano, S., Koshiba, H., Kanamori, R.: Concept and implementation of a new transportation system that unifies the bus and taxi services. In: Proceedings of JSCE, vol. 71, no. 5, pp. I875–I888 (2015)

    Google Scholar 

  6. NakaShima, H., Koshiba, H., Sano, S., Ochiai, J., Shiraishi, Y., Hirata, K., Noda, I., Matsubara, H.: Smart access vehicle system: implementation and evaluation of a vehicle operation system for demand responsive public transportation. Inf. Process. Soc. J. 57(4), 1290–1302 (2016)

    Google Scholar 

  7. Hirata, K., Suzuki, K., Noda, I., Ochiai, J., Kanamori, R., Matsudate, W., Nakashima, H., Sano, S., Shiraishi, Y., Matsubara, H.: Design and implementation of a platform for fully automatic real-time full-demand traffic system SAVS. IPSJ-Technical reports, vol. 2017-ITS-68, no. 1, pp. 1–6 (2017)

    Google Scholar 

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Correspondence to Sho Iwata or Keiji Suzuki .

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Iwata, S., Suzuki, K. (2020). Two Way Allocation Methods in SAVS for Large Depopulated Area. In: Sato, H., Iwanaga, S., Ishii, A. (eds) Proceedings of the 23rd Asia Pacific Symposium on Intelligent and Evolutionary Systems. IES 2019. Proceedings in Adaptation, Learning and Optimization, vol 12. Springer, Cham. https://doi.org/10.1007/978-3-030-37442-6_4

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