
Contents
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Previous Work on Parking Strategies Previous Work on Parking Strategies
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Modeling the Interaction of Parking Strategies Modeling the Interaction of Parking Strategies
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A Nash Equilibrium for a Simple Satisficing Strategy A Nash Equilibrium for a Simple Satisficing Strategy
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A Brief Sensitivity Analysis A Brief Sensitivity Analysis
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Alternative Measures of Performance Alternative Measures of Performance
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Other Ways to Park Other Ways to Park
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A Selection of Simple Parking Heuristics A Selection of Simple Parking Heuristics
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The Heuristics at Pure Nash Equilibria: Their Parameters, the Environments They Create, and Their Ecological Rationality The Heuristics at Pure Nash Equilibria: Their Parameters, the Environments They Create, and Their Ecological Rationality
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Finding Mixed Equilibria With an Evolutionary Algorithm Finding Mixed Equilibria With an Evolutionary Algorithm
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The Evolutionary Algorithm The Evolutionary Algorithm
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The Mixed Equilibria That Emerge The Mixed Equilibria That Emerge
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Explaining Heuristic Competitiveness via Environment Structure Explaining Heuristic Competitiveness via Environment Structure
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Conclusions: The Game of Parking Conclusions: The Game of Parking
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18 Car Parking as a Game Between Simple Heuristics
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Published:March 2012
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Abstract
Selecting a parking space is a sequential-search problem, with the pattern of spaces available to search determined by where others have parked. Earlier optimality models of parking ignored this game-theoretic aspect, unrealistically assuming random occurrences of spaces. This chapter instead simulates populations of cars: Agents (drivers) may accept any unoccupied space as they proceed down a dead-end street toward the destination; otherwise they take the first as they drive back out. Several simple decision heuristics are considered and Nash equilibria found with parameter values that are sensitive to conditions and performance criteria. An evolutionary algorithm is used to implement a competition between the heuristics. The winning heuristic exploits emergent environment structure: Because adjacent sites often fill sequentially, they empty at similar times, so spaces that drivers have recently encountered predict more spaces ahead. High car densities arising far from the destination also leads this heuristic to reject spaces until within a fixed distance of the destination.
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