Determining the Desired Amount of Parking Using Game Theory
Publication: Journal of Urban Planning and Development
Volume 132, Issue 1
Abstract
The problem of seeking an optimal parking policy is formulated here as a Stackelberg game between the government and the travelers. The government wishes to encourage transit ridership while keeping a strong urban center; unlike most existing tools that assist in determining parking policies, the proposed game includes an explicit quantitative formulation of the governmental objective. Each traveler wishes to gain a maximum utility from his choice of destination and transportation mode, and the choice distribution of all travelers is obtained by Logit model. A fundamental difference exists between Game Theory practice and common assumptions used in transportation modeling regarding the relationship between a single traveler’s utility and the choice distribution of all travelers. This difference is tackled here through the definition of the player that represents the travelers and its objective function. A simple version of the game is tested in 24 imaginary scenarios of transportation and urban conditions.
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References
Chen, O. J., and Ben-Akiva, M. E. (1998). “Game-theoretic formulations of interaction between dynamic traffic control and dynamic traffic assignment.” Transportation Research Record 1617, Transportation Research Record, Washington, D.C., 179–188.
Fisk, C. S. (1984). “Game Theory and transportation systems modeling.” Transp. Res., Part B: Methodol., 18(4/5), 301–313.
Hamerslag, R., Fricker, J. D., and Van Beek, P. (1995). “Parking restrictions in employment centers: Implications for public transport and land use.” Transportation Research Record 1449, Transportation Research Record, Washington, D.C., 76–82.
Higgins, T. J. (1989). “Parking management and traffic migration in six cities: Implications for local policy.” Transportation Research Record 1232, Transportation Research Record, Washington, D.C., 60–67.
Hollander, Y., Prashker, J. N., and Mahalel, D. (2003). “Determining the desired amount of parking using game theory.” Research Rep., Technion–Israel Institute of Technology, Israel (in Hebrew).
Kerrigan, M., and Bull, D. (1998). Measuring accessibility—A public transport accessibility index, London Borough of Hammersmith and Fulham, U.K.
Marshall, S., and Banister, D. (1997). “Travel reduction strategies: Intentions and outcomes.” Policy, Planning and Sustainability, Proc., Seminar C at the 25th European Transport Forum Annual Meeting, Brunel Univ., London, P413, 91–108.
Martens, M. J., and Griethuysen, S. V. (1999). The ABC location policy in The Netherlands, TNO-Inro, Delft, The Netherlands.
Polak, J. (1988). “The analysis of central area parking management policies.” Transport & Planning, Proc., Seminar A at the 16th European Transport Forum Summer Annual Meeting, London, P303, 81–93.
Still, B. D., and Simmonds, D. (2000). “Parking restraint and urban vitality.” Transport Rev., 20(3), 291–316.
Topp, H. H. (1993). “Parking policies to reduce car traffic in German cities.” Transport Rev., 13(1), 83–95.
Verroen, E. J., and Jansen, G. R. M. (1991). Location planning for companies and public facilities, a promising policy to reduce car use, Traffic and Transportation Unit at the Netherlands Organization for Applied Scientific Research, The Netherlands.
Young, W., Thompson, R. G., and Taylor, M. A. P. (1991). “A review of urban car parking models.” Transport Rev., 11(1), 63–84.
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© 2006 ASCE.
History
Received: Jun 4, 2004
Accepted: Dec 1, 2004
Published online: Mar 1, 2006
Published in print: Mar 2006
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