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Aurell, Alexander
Publications (3 of 3) Show all publications
Aurell, A. & Djehiche, B. (2019). Modeling tagged pedestrian motion: A mean-field type game approach. Transportation Research Part B: Methodological, 121, 168-183
Open this publication in new window or tab >>Modeling tagged pedestrian motion: A mean-field type game approach
2019 (English)In: Transportation Research Part B: Methodological, ISSN 0191-2615, E-ISSN 1879-2367, Vol. 121, p. 168-183Article in journal (Refereed) Published
Abstract [en]

This paper suggests a model for the motion of tagged pedestrians: Pedestrians moving towards a specified targeted destination, which they are forced to reach. It aims to be a decision-making tool for the positioning of fire fighters, security personnel and other services in a pedestrian environment. Taking interaction with the surrounding crowd into account leads to a differential nonzero-sum game model where the tagged pedestrians compete with the surrounding crowd of ordinary pedestrians. When deciding how to act, pedestrians consider crowd distribution-dependent effects, like congestion and crowd aversion. Including such effects in the parameters of the game, makes it a mean-field type game. The equilibrium control is characterized, and special cases are discussed. Behavior in the model is studied by numerical simulations.

Place, publisher, year, edition, pages
Elsevier, 2019
Backward-forward stochastic differential equations, Congestion, Crowd aversion, Evacuation planning, Mean-field type games, Pedestrian dynamics
National Category
Transport Systems and Logistics
urn:nbn:se:kth:diva-246491 (URN)10.1016/j.trb.2019.01.011 (DOI)2-s2.0-85060867885 (Scopus ID)

QC 20190319

Available from: 2019-03-19 Created: 2019-03-19 Last updated: 2019-03-19Bibliographically approved
Aurell, A. (2018). Mean-Field Type Games between Two Players Driven by Backward Stochastic Differential Equations. Games, 9(5)
Open this publication in new window or tab >>Mean-Field Type Games between Two Players Driven by Backward Stochastic Differential Equations
2018 (English)In: Games, ISSN 2073-4336, E-ISSN 2073-4336, Vol. 9, no 5Article in journal (Refereed) Published
Abstract [en]

In this paper, mean-field type games between two players with backward stochastic dynamics are defined and studied. They make up a class of non-zero-sum, non-cooperating, differential games where the players’ state dynamics solve backward stochastic differential equations (BSDE) that depend on the marginal distributions of player states. Players try to minimize their individual cost functionals, also depending on the marginal state distributions. Under some regularity conditions, we derive necessary and sufficient conditions for existence of Nash equilibria. Player behavior is illustrated by numerical examples, and is compared to a centrally planned solution where the social cost, the sum of playercosts, is minimized. The inefficiency of a Nash equilibrium, compared to socially optimal behavior, is quantified by the so-called price of anarchy. Numerical simulations of the price of anarchy indicate how the improvement in social cost achievable by a central planner depends on problem parameters.

Backward stochastic differential equations; Cooperative game; Linear-quadratic stochastic control; Mean-field type game; Non-zero-sum differential game; Price of anarchy; Social cost
National Category
Probability Theory and Statistics Other Mathematics
urn:nbn:se:kth:diva-248531 (URN)10.3390/g9040088 (DOI)2-s2.0-85056271574 (Scopus ID)

QC 20190514

Available from: 2019-04-09 Created: 2019-04-09 Last updated: 2019-05-20Bibliographically approved
Aurell, A. & Djehiche, B. (2018). Mean-field type modeling of nonlocal crowd aversion in pedestrian crowd dynamics. SIAM Journal of Control and Optimization, 56(1), 434-455
Open this publication in new window or tab >>Mean-field type modeling of nonlocal crowd aversion in pedestrian crowd dynamics
2018 (English)In: SIAM Journal of Control and Optimization, ISSN 0363-0129, E-ISSN 1095-7138, Vol. 56, no 1, p. 434-455Article in journal (Refereed) Published
Abstract [en]

We extend the class of pedestrian crowd models introduced by Lachapelle and Wolfram [Transp. Res. B: Methodol., 45 (2011), pp. 1572–1589] to allow for nonlocal crowd aversion and arbitrarily but finitely many interacting crowds. The new crowd aversion feature grants pedestrians a “personal space” where crowding is undesirable. We derive the model from a particle picture and treat it as a mean-field type game. Solutions to the mean-field type game are characterized via a Pontryagin-type maximum principle. The behavior of pedestrians acting under nonlocal crowd aversion is illustrated by a numerical simulation.

Place, publisher, year, edition, pages
Society for Industrial and Applied Mathematics Publications, 2018
Crowd aversion, Crowd dynamics, Interacting populations, Mean-field approximation, Mean-field type game, Optimal control
National Category
urn:nbn:se:kth:diva-224585 (URN)10.1137/17M1119196 (DOI)000426744900020 ()2-s2.0-85043490666 (Scopus ID)
Swedish Research Council, 2016-04086

QC 20180320

Available from: 2018-03-20 Created: 2018-03-20 Last updated: 2018-03-26Bibliographically approved

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