Estimations of Parking Lot Capacity Using Simulations of Parking Demand as Flow of Requests for Services

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 844)


Paper presents a simulation model of a parking lot operation based on the object-oriented approach. The proposed model considers stochastic nature of demand for parking services: demand is described as a couple of stochastic variables – time interval between vehicles arrival to a parking lot and a parking duration. Using Python implementation of the model, the simulation experiment was carried out in order to define functional dependence between the probability of servicing the vehicle at the parking lot and numeric parameters of demand for parking services. On the grounds of the obtained simulation results, the formula for estimations of a parking lot optimal capacity was defined.


Parking lot capacity Regression analysis Python programming Computer simulations 


  1. 1.
    Urban Stormwater Management in the United States. Research report. National Research Council, p. 513 (2008)Google Scholar
  2. 2.
    Wolf, K.L.: Trees, parking and green law: strategies for sustainability. Research report. University of Washington, p. 73 (2004)Google Scholar
  3. 3.
    Lin, X., Yuan, P.: A dynamic parking charge optimal control model under perspective of commuters’ evolutionary game behavior. Phys. A 490, 1096–1110 (2018)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Duan, M., Chen, G., Cao, H., Zhou, H.: Game model for balanced use of parking lots. J. Southwest Jiaotong Univ. 52(4), 810–816 (2017)zbMATHGoogle Scholar
  5. 5.
    Van Der Waerden, P., Janssens, D., Da Silva, A.N.R.: The influence of parking facility characteristics on car drivers’ departure time decisions. Transp. Res. Procedia 25, 4062–4071 (2017)Google Scholar
  6. 6.
    Eran, B.-J.: Re-thinking a Lot: The Design and Culture of Parking, p. 184. The MIT Press, Cambridge (2015)Google Scholar
  7. 7.
    Stark, J.A.: Parking lots: where motorists become pedestrians. Research report. State University of New York at Albany, p. 51 (2012)Google Scholar
  8. 8.
    Porter, R.: Optimisation of car park designs. Research report. University of Bristol, p. 47 (2013)Google Scholar
  9. 9.
    Christopherson, K., Shoemaker, J.M., Simon, B., Zhang, A.: Transit-Oriented Development Parking Recommendations. Resilient Communities Project Report. University of Minnesota, p. 25 (2013)Google Scholar
  10. 10.
    Hudson, M., Raha, N.: A city-wide, capacity-constrained parking choice model. In: Proceedings of the 2010 European Transport Conference (2010)Google Scholar
  11. 11.
    Horbachov, P., Naumov, V., Kolii, O.: Badania procesów parkowania w centralnej części miasta Charkowa. Zeszyty Naukowo-Techniczne SITK RP, Oddział w Krakowie, vol. 1 (100), pp. 125–134 (2013)Google Scholar
  12. 12.
    Maršanić, R., Zenzerović, Z., Mrnjavac, E.: Planning model of optimal parking area capacity. Promet Traffic Transp. 22(6), 449–457 (2010)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Transport Systems DepartmentCracow University of TechnologyKrakowPoland

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