Highway cost allocation: An application of the theory of nonatomic games
The purpose of all highway cost allocation procedures is to divide in a fair and rational manner the cost building or rehabilitating highway facilities among the highway's users. This article proposes a solution approach to the highway cost allocation problem based on game theory. In this approach, every passage made on the road is viewed as a player in a game that has a large number of insignificant players. For this reason, it can be assumed to be a nonatomic game. Of all highway costs, pavement costs are the most difficult to allocate on the basis of relative damage caused by the user of a highway. A distinctive feature of the analysis conducted in this article is the consideration of a nonlinear programming model that optimizes the total cost of pavement as the characteristic function of the game. The distribution of pavement construction costs proposed by the Federal Highway Administration is essentially a numerical procedure for obtaining value. A solution to the nonatomic game is presented based on a set of axioms that result in allocations that are desirable for its properties. The solution obtained by the proposed approach is compared to existing highway cost allocation methodologies.
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Volume (Year): 29 (1995)
Issue (Month): 3 (May)
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- Small, Kenneth A & Winston, Clifford, 1988. "Optimal Highway Durability," American Economic Review, American Economic Association, vol. 78(3), pages 560-69, June.
- Hendrickson, Chris & Kane, Anthony, 1983. "Cost allocation by uniform traffic removal-- Theoretical discussion and example highway cost applications," Transportation Research Part B: Methodological, Elsevier, vol. 17(4), pages 265-274, August.
- S. H. Tijs & T. S. H. Driessen, 1986. "Game Theory and Cost Allocation Problems," Management Science, INFORMS, vol. 32(8), pages 1015-1028, August.
- Tijs, S.H. & Driessen, T.S.H., 1986. "Game theory and cost allocation problems," Other publications TiSEM 376c24c5-c95d-4d29-96b6-4, Tilburg University, School of Economics and Management.
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