The Parking Problem: A Game-Theoretic Solution

TL;DR

This paper introduces a game-theoretic approach to optimize multi-agent parking assignments, modeling cars as agents in a game to find Nash equilibrium solutions efficiently, demonstrated through a hospital parking case study.

Contribution

It presents a novel game-theoretic framework and a quadratic-time algorithm for multi-agent parking optimization, with practical implementation and testing.

Findings

Efficient quadratic-time algorithm for parking assignment

Successful application to hospital parking scenario

Evidence of improved parking allocation through game-theoretic method

Abstract

In this paper, we propose a game-theoretic solution to the parking problem, by exploiting a strategic-reasoning approach for multi-agent systems. Precisely, cars are modeled by agents interacting among them in a multi-player game setting, whose aim is to get a free slot parking-place satisfying their own constraints. The overall assignment is then given as a Nash equilibrium solution. We come up with an algorithm (and its implementation in a tool) that works in quadratic time. We give evidence of the benefits of our approach by running our tool on a large hospital parking space.