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Modelling demand in restricted parking zones

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  • Ibeas, Ángel
  • Cordera, Ruben
  • dell'Olio, Luigi
  • Moura, Jose Luis
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    Abstract

    Multiple linear regression (MLR) and geographically weighted regression (GWR) models are used for estimating parking demand in areas with paid short stay parking systems. These models have been applied to the city of Santander (Cantabria, Spain) to check their goodness of fit and their predictive ability. The results show the main advantages and disadvantages of using GWR models. The technique proved to be useful in this case study because it offered a better fit and made better predictions in a scenario showing a certain degree of spatial heterogeneity unexplained by any of the variables introduced into the global model. However, the GWR model also presented situations of local correlation although this was considered moderate given the results provided by the variance inflation factors and the local condition indexes.

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    Bibliographic Info

    Article provided by Elsevier in its journal Transportation Research Part A: Policy and Practice.

    Volume (Year): 45 (2011)
    Issue (Month): 6 (July)
    Pages: 485-498

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    Handle: RePEc:eee:transa:v:45:y:2011:i:6:p:485-498

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    Related research

    Keywords: Parking demand models Geographically weighted regression Parking policies;

    References

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    1. David C Wheeler, 2007. "Diagnostic tools and a remedial method for collinearity in geographically weighted regression," Environment and Planning A, Pion Ltd, London, vol. 39(10), pages 2464-2481, October.
    2. David Wheeler & Michael Tiefelsdorf, 2005. "Multicollinearity and correlation among local regression coefficients in geographically weighted regression," Journal of Geographical Systems, Springer, vol. 7(2), pages 161-187, 06.
    3. Shoup, Donald C., 1999. "The trouble with minimum parking requirements," Transportation Research Part A: Policy and Practice, Elsevier, vol. 33(7-8), pages 549-574.
    4. Hensher, David A. & King, Jenny, 2001. "Parking demand and responsiveness to supply, pricing and location in the Sydney central business district," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(3), pages 177-196, March.
    5. Marsden, Greg, 2006. "The evidence base for parking policies--a review," Transport Policy, Elsevier, vol. 13(6), pages 447-457, November.
    6. repec:ucp:bkecon:9781884829987 is not listed on IDEAS
    7. Bifulco, Gennaro Nicola, 1993. "A stochastic user equilibrium assignment model for the evaluation of parking policies," European Journal of Operational Research, Elsevier, vol. 71(2), pages 269-287, December.
    8. Goyal, S. K. & Gomes, L. F. A. M., 1984. "A model for allocating car parking spaces in universities," Transportation Research Part B: Methodological, Elsevier, vol. 18(3), pages 267-269, June.
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    Cited by:
    1. Simićević, Jelena & Vukanović, Smiljan & Milosavljević, Nada, 2013. "The effect of parking charges and time limit to car usage and parking behaviour," Transport Policy, Elsevier, vol. 30(C), pages 125-131.
    2. Arnott, Richard & Rowse, John, 2009. "Curbside Parking Time Limits," University of California Transportation Center, Working Papers qt21p8f8b2, University of California Transportation Center.

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