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Electric Public Bus Charging Stations Topography Modelling

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Management Perspective for Transport Telematics (TST 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 897))

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Abstract

The subject of the paper is a method of dynamic planning of batteries charging process the electric bus, operated in urban agglomerations, and with a distributed system of the stations in the form of a network. For the operated bus, based on the assessment of the condition of its batteries and location in the urban space of the transport network, the requested place and time of batteries charging is selected. The model also takes into account the ambient conditions of the bus operation process, in particular weather conditions, passengers line load, the intensity of vehicle traffic on specific routes, the operation schedule of a given vehicle. The effectiveness of the system in the sense of communication (dynamic databases, data mining) between actors of the transport system is supported by telematics.

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References

  1. Andrenacci, N., Genovese, A., Ragona, R.: Determination of the level of service and customer crowding for electric charging stations through fuzzy models and simulation techniques. Appl. Energy 208, 97–107 (2017)

    Article  Google Scholar 

  2. Barbosa, S.B., et al.: Multi-criteria analysis model to evaluate transport systems: an application in Florianópolis, Brazil. Transp. Res. Part A 96, 1–13 (2017)

    Article  Google Scholar 

  3. Boreiko, O., Teslyuk, V.: Structural model of passenger counting and public transport tracking system of smart city. In: MEMSTECH, Polyana-Svalyava, 20–24 April 2016

    Google Scholar 

  4. Cáceres, P., Cuesta, C.E., Cavero, J.M., Vela, B., Sierra-Alonso, A.: Towards knowledge modeling for sustainable transport. In: Counsell, S., Núñez, M. (eds.) SEFM 2013. LNCS, vol. 8368, pp. 271–287. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-05032-4_20

    Chapter  Google Scholar 

  5. Castelain, E., Mesghouni, K.: Regulation of a public transport network with consideration of the passenger flow: modeling of the system with high-level Petri Nets. In: IEEE SMC (2002)

    Google Scholar 

  6. Cats, O., Gkioulou, Z.: Modeling the impacts of public transport reliability and travel information on passengers’ waiting-time uncertainty. EURO J. Transp. Logist. 6, 247–270 (2017)

    Article  Google Scholar 

  7. EMBARQ. Exhaust emissions of transit buses (2015)

    Google Scholar 

  8. von Ferber, C., et al.: Public transport networks: empirical analysis and modeling. Eur. Phys. J. 68, 261–275 (2009)

    Article  Google Scholar 

  9. Gudowski, B., Wąs, J.: Modeling of people flow in public transport vehicles. In: Wyrzykowski, R., Dongarra, J., Meyer, N., Waśniewski, J. (eds.) PPAM 2005. LNCS, vol. 3911, pp. 333–339. Springer, Heidelberg (2006). https://doi.org/10.1007/11752578_40

    Chapter  Google Scholar 

  10. IEA: Transport, Energy and CO2: Moving toward Sustainability, International Energy Agency (2009)

    Google Scholar 

  11. Kujalaa, R., et al.: Travel times and transfers in public transport: comprehensive accessibility analysis based on Pareto-optimal journeys. Comput. Environ. Urban Syst. 67, 41–54 (2018)

    Article  Google Scholar 

  12. Kulakov, A., Trofimenko, K.: Transport planning and transport modeling. In: Blinkin, M., Koncheva, E. (eds.) Transport Systems of Russian Cities, Transportation Research, pp. 1–37. Economics and Policy. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-47800-5_1

    Chapter  Google Scholar 

  13. Kurzcvezil, T., Schnieder, L., Burmeister, F.: Optimized energy management of inductively charged electric buses reflecting operational constraints and traffic conditions. In: Models and Technologies for Intelligent Transportation Systems (MT-ITS), Budapest, 3–5 June 2015

    Google Scholar 

  14. Leea, J., Madanatb, S.: Optimal design of electric vehicle public charging system in an urban network for greenhouse gas emission and cost minimization. Transp. Res. Part C 85, 494–508 (2017)

    Article  Google Scholar 

  15. Levchenkov, A., Gorobetz, M.: Evolutionary algorithms and dynamic parameters for public electric transport modeling. In: 16th Mediterranean Conference on Control and Automation Congress Centre, Ajaccio, 25–27 June 2008

    Google Scholar 

  16. Li, W., Wang, T., Zhang, X.: Study on optimization and adjustment method of urban public transport network based on evolutionary analysis. In: Wang, W., Bengler, K., Jiang, X. (eds.) GITSS 2016. LNEE, vol. 419, pp. 607–617. Springer, Singapore (2018). https://doi.org/10.1007/978-981-10-3551-7_48

    Chapter  Google Scholar 

  17. Li, X.: TOPSIS model for urban public transport network optimization based on AHP and entropy. In: IEEE International Conference on Transportation, Mechanical, and Electrical Engineering (TMEE), 16–18 December 2011, Changchun, China (2011)

    Google Scholar 

  18. Li, Y., et al.: Least transfer cost model for optimizing public transport travel routes. In: 2nd International Conference on Signal Processing Systems (ICSPS). IEEE (2010)

    Google Scholar 

  19. Lianxiong, G., Hong, L., Ru, L.: Hub nodes identification in public transport networks using Markov chain model. In: Proceedings of the 12th International IEEE Conference on Intelligent Transportation Systems, St. Louis, 3–7 October 2009

    Google Scholar 

  20. Liu, K.S.: Studies on the transfer data modeling in the public transport information system, 1-4244-1 178-5/0. IEEE (2007)

    Google Scholar 

  21. Ly, T., Goehlich, D., Heide, L.: Assessment of the interaction of charging system and battery technology for the use in urban battery electric bus systems. IEEE (2016)

    Google Scholar 

  22. Makarova, I., Khabibullin, R., Belyaev, E., Mavrin, V.: Increase of city transport system management efficiency with application of modeling methods and data intellectual analysis. In: Sładkowski, A., Pamuła, W. (eds.) Intelligent Transportation Systems – Problems and Perspectives. SSDC, vol. 32, pp. 37–80. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-19150-8_2

    Chapter  Google Scholar 

  23. McGlade, C., Ekins, P.: The geographical distribution of fossil fuels unused when limiting global warming to 2 °C. Nature 517(7533), 187–190 (2015)

    Article  Google Scholar 

  24. Meinshausen, M., et al.: Greenhouse-gas emission targets for limiting global warming to 2 °C. Nature 458(7242), 1158–1162 (2009)

    Article  Google Scholar 

  25. Morri, N., Hadouaj, S., Ben Said L.: Multi-agent optimization model for multi-criteria regulation of multi-modal public transport. IEEE (2015)

    Google Scholar 

  26. Murray, A.T.: Strategic analysis of public transport coverage. Socio-Econ. Plan. Sci. 35, 175–188 (2001)

    Article  Google Scholar 

  27. Nait Sidi Moh, A., Manier, A.A., El Moudni, A.: A control policy for a public transport network modelled by Petri nets and max-plus algebra. IEEE (2002)

    Google Scholar 

  28. Roggea, M., et al.: Electric bus fleet size and mix problem with optimization of charging infrastructure. Appl. Energy 211, 282–295 (2018)

    Article  Google Scholar 

  29. Sinhuber, P., Rohlfs, W., Sauer, D.U.: Connectional considerations for electrification of public city buses. In: Energy Storage System and Charging Stations. IEEE (2010)

    Google Scholar 

  30. Somov, E.V., Tikunov, V.S.: Approach to geoinformation modeling of provision of the population with public transport in Moscow. Reg. Res. Russia 5(2), 178–192 (2015). Pleiades Publishing Ltd.

    Article  Google Scholar 

  31. TOSA (Trolleybus Optimisation Systeme Alimentation) 2013 (2016)

    Google Scholar 

  32. UNFCC. United Nations Framework Convention on Climate Change (UNFCC) Report of the Conference of the Parties on its Fifteenth Session, Copenhagen, 7–19 December 2009. Part Two: Action taken by the Conference of the Parties at its Fifteenth Session. United Nations Climate Change Conference, Report 43 (2009)

    Google Scholar 

  33. Wang, J., Chen, X.: Cluster algorithm based on LDA model for public transport passengers’ trip purpose identification in specific area. In: IEEE International Conference on Intelligent Transportation Engineering (2016)

    Google Scholar 

  34. WPP. World Population Prospects, United Nations (2014)

    Google Scholar 

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Acknowledgement

The work has been financially supported by the Polish Ministry of Science and Higher Education in the year 2018.

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Authors and Affiliations

  1. Technological University of Havana, Havana, Cuba

    Yorlandys Salgado

  2. AGH University of Science and Technology, Ave A. Mickiewicza 30, 30-059, Krakow, Poland

    Janusz Szpytko

Authors
  1. Yorlandys Salgado
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  2. Janusz Szpytko
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Corresponding author

Correspondence to Yorlandys Salgado .

Editor information

Editors and Affiliations

  1. Polish Association of Transport Telematics, Katowice, Poland

    Jerzy Mikulski

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Salgado, Y., Szpytko, J. (2018). Electric Public Bus Charging Stations Topography Modelling. In: Mikulski, J. (eds) Management Perspective for Transport Telematics. TST 2018. Communications in Computer and Information Science, vol 897. Springer, Cham. https://doi.org/10.1007/978-3-319-97955-7_14

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  • DOI: https://doi.org/10.1007/978-3-319-97955-7_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-97954-0

  • Online ISBN: 978-3-319-97955-7

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