Optimal Control of the Mean Field Equilibrium for a Pedestrian Tourists’ Flow Model

Fabio Bagagiolo (), Silvia Faggian, Rosario Maggistro () and Raffaele Pesenti ()
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Fabio Bagagiolo: Università di Trento
Rosario Maggistro: Università Ca’ Foscari Venezia
Raffaele Pesenti: Università Ca’ Foscari Venezia

Networks and Spatial Economics, 2022, vol. 22, issue 2, No 3, 243-266

Abstract: Abstract Art heritage cities are popular tourist destinations but for many of them overcrowding is becoming an issue. In this paper, we address the problem of modeling and analytically studying the flow of tourists along the narrow alleys of the historic center of a heritage city. We initially present a mean field game model, where both continuous and switching decisional variables are introduced to respectively describe the position of a tourist and the point of interest that he/she may visit. We prove the existence of a mean field equilibrium. A mean field equilibrium is Nash-type equilibrium in the case of infinitely many players. Then, we study an optimization problem for an external controller who aims to induce a suitable mean field equilibrium.

Keywords: Tourist flow optimal control; Mean field games; Switching variables; Dynamics on networks (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11067-019-09475-4

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