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Efficient Access Control to Parking Space for Different Customer Segments

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Digital Business and Intelligent Systems (Baltic DB&IS 2022)

Abstract

In urban areas, the number of parking spaces is limited and takes up valuable space that is also needed for other purposes. Demand-driven and systematic utilisation of parking spaces can help to gain the most out of available space. We propose a probability-based approach to control access to off-street parking lots. Our approach takes into account distinct offerings for different customer segments. Registered customers, who pay a monthly fee and have a guarantee of a free parking space at all times, and public customers, who pay according to their parking time. The latter is more profitable and needs to be maximized. We test our approach in a case study with a historic dataset and compare our results with the original control of access. Over two months, we could release on critical periods approximately 22% more parking spaces for public customers.

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References

  1. Manville, M., Shoup, D.: Parking, People, and Cities. J. Urban Plann. Dev. 131(4), 233–245 (2005). https://doi.org/10.1061/(ASCE)0733-9488(2005)131:4(233)

    Article  Google Scholar 

  2. van Ommeren, J., Wentink, D., Dekkers, J.: The real price of parking policy. J. Urban Econ. 70, 25–31 (2011). https://doi.org/10.1016/j.jue.2011.02.001

    Article  Google Scholar 

  3. Cai, Y., Chen, J., Zhang, C., Wang, B.: A parking space allocation method to make a shared parking strategy for appertaining parking lots of public buildings. Sustainability 11, 120 (2019). https://doi.org/10.3390/su11010120

    Article  Google Scholar 

  4. MOBIX Homepage. https://mobix.ai/2021/10/07/the-iaa-mobility-2021-mobix-deep-parking-showcase/. Accessed 23 Feb 2022

  5. Buehler, R., Pucher, J., Gerike, R., Götschi, T.: Reducing car dependence in the heart of Europe: lessons from Germany, Austria, and Switzerland. Transp. Rev. 37, 4–25 (2017). https://doi.org/10.1080/01441647.2016.1177799

    Article  Google Scholar 

  6. The Buffalo News Homepage. Buffalo’s zoning code steps into the 21st century. https://buffalonews.com/news/local/buffalos-zoning-code-steps-into-the-21st-century/article_a8b81e45-f6f3-526e-99fe-dde988ef9c78.html. Accessed 23 Feb 2022

  7. Arjona, J., Linares, M.P., Casanovas, J.: A deep learning approach to real-time parking availability prediction for smart cities. In: Hoballah, I. (ed.) Proceedings of the Second International Conference on Data Science, E-Learning and Information Systems - DATA 2019, Dubai, United Arab Emirates, 02.12.2019–05.12.2019, pp. 1–7. ACM Press, New York, New York, USA (2019). https://doi.org/10.1145/3368691.3368707

  8. Badii, C., Nesi, P., Paoli, I.: Predicting available parking slots on critical and regular services by exploiting a range of open data. IEEE Access 6, 1–12 (2018). https://doi.org/10.1109/ACCESS.2018.2864157

    Article  Google Scholar 

  9. Abdeen, M.A.R., Nemer, I.A., Sheltami, T.R.: A balanced algorithm for in-city parking allocation: a case study of Al Madinah City. Sensors. 21, 3148 (2021). https://doi.org/10.3390/s21093148

  10. Tian, Q., Yang, L., Wang, C., Huang, H.-J.: Dynamic pricing for reservation-based parking system: a revenue management method. Transp. Policy 71, 36–44 (2018). https://doi.org/10.1016/j.tranpol.2018.07.007

    Article  Google Scholar 

  11. Caicedo, F., Blazquez, C., Miranda, P.: Prediction of parking space availability in real time. Expert Syst. Appl. 39, 1–9 (2012). https://doi.org/10.1016/j.eswa.2012.01.091

    Article  Google Scholar 

  12. Stolfi, D.H., Alba, E., Yao, X.: Can I park in the city center? Predicting car park occupancy rates in smart cities. J. Urban Technol. 27, 27–41 (2019). https://doi.org/10.1080/10630732.2019.1586223

    Article  Google Scholar 

  13. Vlahogianni, E.I., Kepaptsoglou, K., Tsetsos, V., Karlaftis, M.G.: A real-time parking prediction system for smart cities. J. Intell. Transp. Syst. 30, 192–204 (2016). https://doi.org/10.1080/15472450.2015.1037955

    Article  Google Scholar 

  14. Geng, Y., Cassandras, C.G.: New “smart parking” system based on resource allocation and reservations. IEEE Trans. Intell. Transport. Syst. 30, 192–204 (2013). https://doi.org/10.1109/TITS.2013.2252428

    Article  Google Scholar 

  15. Wu, E.H.-K., Sahoo, J., Liu, C.-Y., Jin, M.-H., Lin, S.-H.: Agile urban parking recommendation service for intelligent vehicular guiding system. IEEE Intell. Transport. 6, 35–49 (2014). https://doi.org/10.1109/MITS.2013.2268549

    Article  Google Scholar 

  16. Saharan, S., Kumar, N., Bawa, S.: An efficient smart parking pricing system for smart city environment: A machine-learning based approach. Future Gener. Comput. Syst. 106, 222–240 (2020). https://doi.org/10.1016/j.future.2020.01.031

  17. Guadix, J., Onieva, L., Muñuzuri, J., Cortés, P.: An overview of revenue management in service industries: an application to car parks. Serv. Indust. J. 31, 91–105 (2011). https://doi.org/10.1080/02642069.2010.491543

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Müller, T., Piller, G., Rothlauf, F. (2022). Efficient Access Control to Parking Space for Different Customer Segments. In: Ivanovic, M., Kirikova, M., Niedrite, L. (eds) Digital Business and Intelligent Systems. Baltic DB&IS 2022. Communications in Computer and Information Science, vol 1598. Springer, Cham. https://doi.org/10.1007/978-3-031-09850-5_2

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  • DOI: https://doi.org/10.1007/978-3-031-09850-5_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-09849-9

  • Online ISBN: 978-3-031-09850-5

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