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Infrastructure Access Policies to Promote Sustainable Driving Behaviours in Railway Contexts

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Web, Artificial Intelligence and Network Applications (WAINA 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1150))

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Abstract

The free movement of people and goods in the European Union has led to the introduction of a cost to the infrastructure access in the rail sector. However, the current access policies do not encourage the adoption of environmentally sustainable behaviours of the transport service providers. In this context, our proposal provides a methodology for estimating suitable incentives (in terms of access cost reductions) in order to encourage companies to adopt proper driving speed profiles aimed to implement energy-saving strategies. Initial results have shown that the adoption of sustainable driving behaviours may provide a reduction in access costs up to 48%.

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References

  1. Chuang, H.J., Chen, C.S., Lin, C.H., Hsieh, C.H., Ho, C.Y.: Design of optimal coasting speed for saving social cost in mass rapid transit systems. In: Proceedings of the 3rd International Conference on Deregulation and Restructuring and Power Technologies (DRPT 2008), Nianjing, China (2008). https://doi.org/10.1109/DRPT.2008.4523892

  2. De Martinis, V., Gallo, M., D’Acierno, L.: Estimating the benefits of energy-efficient train driving strategies: a model calibration with real data. WIT Trans. Built Environ. 130, 201–211 (2013). https://doi.org/10.2495/UT130161

    Article  Google Scholar 

  3. De Martinis, V., Weidmann, U., Gallo, M.: Towards a simulation-based framework for evaluating energy-efficient solutions in train operation. WIT Trans. Built Environ. 135, 721–732 (2014). https://doi.org/10.2495/CR140601

    Article  Google Scholar 

  4. Guastafierro, A., Lauro, G., Pagano, M., Roscia, M.: A method for optimizing coasting phases in railway speed profiles: an application to an Italian route. In: Proceedings of the International Conference on Electrical Systems for Aircraft, Railway, Ship Propulsion and Road Vehicles & International Transportation Electrification Conference (ESARS-ITEC), Toulouse, France (2016). https://doi.org/10.1109/ESARS-ITEC.2016.7841442

  5. Alfieri, L., Botte, M., D’Acierno, L., Pagano, M.: Effects of urban metro energy-saving strategy on the distribution electrical power system. In: Proceedings of the 2019 IEEE Vehicle Power and Propulsion Conference (IEEE VPPC 2019), Hanoi, Vietnam (2019). https://doi.org/10.1109/VPPC46532.2019.8952489

  6. Gallo, M., D’Acierno, L., Montella, B.: A multimodal approach to bus frequency design. WIT Trans. Built Environ. 116, 193–204 (2011). https://doi.org/10.2495/UT110171

    Article  Google Scholar 

  7. Cascetta, E., Cartenì, A., Carbone, A.: The quality in public transportation. The Campania regional metro system. Ingegneria Ferroviaria 68(3), 241–261 (2013). http://www.ingegneriaferroviaria.it/web/it/content/ingegneria-ferroviaria-marzo-n03-anno-2013

  8. Cartenì, A.: Accessibility indicators for freight transport terminals. Arab. J. Sci. Eng. 39(11), 7647–7660 (2014). https://doi.org/10.1007/s13369-014-1333-y

    Article  MathSciNet  Google Scholar 

  9. Cartenì, A.: Urban sustainable mobility. Part 2: simulation models and impacts estimation. Transp. Probl. 10(1), 5–16 (2015). https://doi.org/10.21307/tp-2015-001

    Article  Google Scholar 

  10. Montella, A., Galante, F., Mauriello, F., Pariota, L.: Effects of traffic control devices on rural curve driving behavior. Transp. Res. Rec. 2492, 10–22 (2015). https://doi.org/10.3141/2492-02

    Article  Google Scholar 

  11. Pariota, L., Bifulco, G.N.: Experimental evidence supporting simpler action point paradigms for car-following. Transp. Res. Part F 35, 1–15 (2015). https://doi.org/10.1016/j.trf.2015.08.002

    Article  Google Scholar 

  12. Botte, M., Di Salvo, C., Caropreso, C., Montella, B., D’Acierno, L.: Defining economic and environmental feasibility thresholds in the case of rail signalling systems based on satellite technology. In: Proceedings of the 16th IEEE International Conference on Environment and Electrical Engineering (IEEE EEEIC 2016), Florence, Italy (2016). https://doi.org/10.1109/EEEIC.2016.7555878

  13. Cartenì, A., Pariota, L., Henke, I.: Hedonic value of high-speed rail services: quantitative analysis of the students’ domestic tourist attractiveness of the main Italian cities. Transp. Res. Part A 100, 348–365 (2017). https://doi.org/10.1016/j.tra.2017.04.018

    Article  Google Scholar 

  14. Henke, I.: The effect of railway accessibility on the choice of university studies. Int. J. Transp. Dev. Integr. 1(3), 339–347 (2017). https://doi.org/10.2495/TDI-V1-N3-339-347

    Article  Google Scholar 

  15. D’Acierno, L., Botte, M.: A passenger-oriented optimization model for implementing energy-saving strategies in railway contexts. Energies 11(11), 1–25 (2018). https://doi.org/10.3390/en11112946

    Article  Google Scholar 

  16. Gallo, M.: The impact of urban transit systems on property values: a model and some evidences from the city of Naples. J. Adv. Transp. 2018, 1–22 (2018). https://doi.org/10.1155/2018/1767149

    Article  Google Scholar 

  17. Markkula, G., Romano, R., Jamson, A.H., Pariota, L., Bean, A., Boer, E.R.: Using driver control models to understand and evaluate behavioral validity of driving simulators. IEEE Trans. Hum.-Mach. Syst. 48(6), 592–603 (2018). https://doi.org/10.1109/THMS.2018.2848998

    Article  Google Scholar 

  18. Gallo, M., Amo Guevara, A.: A model for estimating the impact of national transport investments on the rail modal share and greenhouse gas emissions. In: Proceedings of the 19th IEEE International Conference on Environment and Electrical Engineering (IEEE EEEIC 2019) and 3rd Industrial and Commercial Power Systems Europe (I&CPS 2019), Genoa, Italy (2019). https://doi.org/10.1109/EEEIC.2019.8783712

  19. Botte, M., D’Acierno, L., Montella, B., Placido, A.: A stochastic approach for assessing intervention strategies in the case of metro system failures. In: Proceedings of 2015 AEIT Annual Conference (AEIT 2015), Naples, Italy (2015). https://doi.org/10.1109/AEIT.2015.7415258

  20. Botte, M., D’Acierno, L., Gallo, M.: Effects of rolling stock unavailability on the implementation of energy-saving policies: a metro system application. In: ICCSA 2019. Lecture Notes in Computer Science, vol. 11620, pp. 120–132 (2019). https://doi.org/10.1007/978-3-030-24296-1_12

  21. Gonzalez-Gil, A., Palacin, R., Batty, P.: Sustainable urban rail systems: strategies and technologies for optimal management of regenerative braking energy. Energy Convers. Manag. 75, 374–388 (2013). https://doi.org/10.1016/j.enconman.2013.06.039

    Article  Google Scholar 

  22. Scheepmaker, G., Goverde, R.M.P.: The interplay between energy-efficient train control and scheduled running time supplements. J. Rail Transp. Planning Manag. 5(4), 235–239 (2015). https://doi.org/10.1016/j.jrtpm.2015.10.003

    Article  Google Scholar 

  23. Wang, P., Goverde, R.M.P.: Multi-train trajectory optimization for energy-efficient timetabling. Eur. J. Oper. Res. 272(2), 621–635 (2019). https://doi.org/10.1016/j.ejor.2018.06.034

    Article  MathSciNet  MATH  Google Scholar 

  24. Romo, L., Turner, D., Ng, L.S.B.: Cutting traction power costs with wayside energy storage systems in rail transit systems. In: Proceedings of the 2005 Joint Rail Conference (JRC 2005), Pueblo(CO), USA (2005). https://doi.org/10.1109/RRCON.2005.186078

  25. Ghavihaa, N., Campilloa, J., Bohlinb, M., Dahlquista, E.: Review of application of energy storage devices in railway transportation. Energy Procedia 105, 4561–4568 (2017). https://doi.org/10.1016/j.egypro.2017.03.980

    Article  Google Scholar 

  26. Iannuzzi, D., Tricoli, P.: Speed-based state-of-charge tracking control for metro trains with onboard supercapacitors. IEEE Trans. Power Electron. 27(4), 2129–2140 (2012). https://doi.org/10.1109/TPEL.2011.2167633

    Article  Google Scholar 

  27. Song, R., Yuan, T., Yang, J., He, H.: Simulation of braking energy recovery for the metro vehicles based on the traction experiment system. Simulation 93(12), 1099–1112 (2017). https://doi.org/10.1177/0037549717726146

    Article  Google Scholar 

  28. Fallah, M., Asadi, M., Moghbeli, H., Dehnavi, G.R.: Energy management and control system of DC-DC converter with super-capacitor and battery for recovering of train kinetic energy. J. Renew. Sustain. Energy 10(1) (2018). https://doi.org/10.1063/1.5004619

  29. Cornic, D.: Efficient recovery of braking energy through a reversible DC substation. In: Proceedings of Electrical Systems for Aircraft, Railway and Ship Propulsion (ESARS 2010), Bologna, Italy (2010). https://doi.org/10.1109/ESARS.2010.5665264

  30. Ibaiondo, H., Romo, A.: Kinetic energy recovery on railway systems with feedback to the grid. In: Proceedings of the 14th International Power Electronics and Motion Control Conference (EPE-PEMC 2010), Ohrid, Macedonia (2010). https://doi.org/10.1109/EPEPEMC.2010.5606545

  31. Wikipedia: Frecciarossa1000. https://en.wikipedia.org/wiki/Frecciarossa_1000. Accessed February 2020

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Authors and Affiliations

  1. Department of Civil, Architectural and Environmental Engineering, Federico II University of Naples, 80125, Naples, Italy

    Marilisa Botte, Ilaria Tufano & Luca D’Acierno

Authors
  1. Marilisa Botte
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  2. Ilaria Tufano
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  3. Luca D’Acierno
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Corresponding author

Correspondence to Marilisa Botte .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Department of Electrical Engineering and Information Technology, University of Naples “Frederico II”, Naples, Italy

    Flora Amato

  3. Department of Political Science, University of Campania Luigi Vanvitelli, Caserta, Italy

    Francesco Moscato

  4. Faculty of Business Administration, Rissho University, Tokyo, Japan

    Tomoya Enokido

  5. Department of Advanced Sciences, Hosei University, Tokyo, Japan

    Makoto Takizawa

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Botte, M., Tufano, I., D’Acierno, L. (2020). Infrastructure Access Policies to Promote Sustainable Driving Behaviours in Railway Contexts. In: Barolli, L., Amato, F., Moscato, F., Enokido, T., Takizawa, M. (eds) Web, Artificial Intelligence and Network Applications. WAINA 2020. Advances in Intelligent Systems and Computing, vol 1150. Springer, Cham. https://doi.org/10.1007/978-3-030-44038-1_123

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