Multiday User Equilibrium with Strategic Commuters
Published Online:20 Dec 2024https://doi.org/10.1287/trsc.2023.0488
References
- (2022) Departure time choice models in urban transportation systems based on mean field games. Transportation Sci. 56(6):1483–1504.Link, Google Scholar
- (2019) Modeling tagged pedestrian motion: A mean-field type game approach. Transportation Res. Part B Methodological 121:168–183.Crossref, Google Scholar
- Beckmann M, McGuire CB, Winsten CB (1956) Studies in the Economics of Transportation (Yale University Press, New Haven, CT). Google Scholar
- (2018) Mean field control and mean field game models with several populations. Preprint, submitted October 1, https://arxiv.org/abs/1810.00783.Google Scholar
- (2010) Stability and attraction domains of traffic equilibria in a day-to-day dynamical system formulation. Transportation Res. Part B Methodological 44(1):90–107.Crossref, Google Scholar
- Bureau of Public Roads (1964) Traffic Assignment Manual for Application with a Large, High Speed Computer (U.S. Department of Commerce, Bureau of Public Roads, Office of Planning, Urban Planning Division, Washington, DC).Google Scholar
- (2021) Solving n-player dynamic routing games with congestion: A mean field approach. Preprint, submitted October 22, https://arxiv.org/abs/2110.11943.Google Scholar
- (2013) Day-to-day dynamic models for intelligent transportation systems design and appraisal. Transportation Res. Part C Emerging Tech. 29:117–130.Crossref, Google Scholar
- (1995) Dynamic processes and equilibrium in transportation networks: Toward a unifying theory. Transportation Sci. 29(4):305–329.Link, Google Scholar
- (2017) Stochastic user equilibrium in the presence of inertia. Transportation Res. Procedia 22:13–24.Crossref, Google Scholar
- (2019) Stochastic user equilibrium in the presence of state dependence. EURO J. Transportation Logist. 8(5):535–559.Crossref, Google Scholar
- (2016) Optimal deployment of charging lanes for electric vehicles in transportation networks. Transportation Res. Part B Methodological 91:344–365.Crossref, Google Scholar
- (2015) Multi-population mean field games systems with Neumann boundary conditions. J. Math. Pures Appl. 103(5):1294–1315.Crossref, Google Scholar
- Cui K, Koeppl H (2021) Approximately solving mean field games via entropy-regularized deep reinforcement learning. Banerjee A, Fukumizu K, eds. Proc. 24th Internat. Conf. Artificial Intelligence Statist., Proceedings of Machine Learning Research, vol. 130 (PMLR, Cambridge, MA), 1909–1917.Google Scholar
- (1977) On stochastic models of traffic assignment. Transportation Sci. 11(3):253–274.Link, Google Scholar
- (2018) A mixed-behaviour equilibrium model under predictive and static advanced traveller information systems (ATIS) and state-dependent route choice. Transportation Res. Part C Emerging Tech. 86:549–562.Crossref, Google Scholar
- (2013) Boundedly rational user equilibria (BRUE): Mathematical formulation and solution sets. Procedia Soc. Behav. Sci. 80:231–248.Crossref, Google Scholar
- Elie R, Pérolat J, Laurière M, Geist M, Pietquin O (2020) On the convergence of model-free learning in mean field games. Bessiere C, ed. Proc. 34th AAAI Conf. Artificial Intelligence, vol. 34, no. 5 (AAAI Press, Palo Alto, CA), 7143–7150.Google Scholar
- (2013) The derivation of ergodic mean field game equations for several populations of players. Dynam. Games Appl. 3:523–536.Crossref, Google Scholar
- Fudenberg D, Levine DK (1998) The Theory of Learning in Games, vol. 2 (MIT Press, Cambridge, MA)Google Scholar
- (2010) Discrete time, finite state space mean field games. J. Math. Pures Appl. 93(3):308–328.Crossref, Google Scholar
- (2013) A discrete rational adjustment process of link flows in traffic networks. Transportation Res. Part C Emerging Tech. 34:121–137.Crossref, Google Scholar
- (2018a) Are we really solving the dynamic traffic equilibrium problem with a departure time choice? Transportation Sci. 52(3):603–620.Link, Google Scholar
- (2018b) Day-to-day departure time choice under bounded rationality in the bottleneck model. Transportation Res. Part B Methodological 117:832–849.Crossref, Google Scholar
- (2015) Link-based day-to-day network traffic dynamics and equilibria. Transportation Res. Part B Methodological 71:248–260.Crossref, Google Scholar
- (2012) On a link-based day-to-day traffic assignment model. Transportation Res. Part B Methodological 46(1):72–84.Crossref, Google Scholar
- (2013) A partial differential equation formulation of Vickrey’s bottleneck model, part I: Methodology and theoretical analysis. Transportation Res. Part B Methodological 49:55–74.Crossref, Google Scholar
- (2022) The emergence of stochastic user equilibria in day-to-day traffic models. Transportation Res. Part B Methodological 158:102–112.Crossref, Google Scholar
- (2010) A link-based day-to-day traffic assignment model. Transportation Res. Part B Methodological 44(4):597–608.Crossref, Google Scholar
- (2006) Large population stochastic dynamic games: Closed-loop McKean-Vlasov systems and the Nash certainty equivalence principle. Comm. Inform. Systems 6(3):221–252.Crossref, Google Scholar
- (2021) Dynamic driving and routing games for autonomous vehicles on networks: A mean field game approach. Transportation Res. Part C Emerging Tech. 128:103189.Crossref, Google Scholar
- (2024) The impact of road rationing on housing demand and sorting. J. Urban Econom. 140:103642.Crossref, Google Scholar
- (2005) Credit-based congestion pricing: A policy proposal and the public’s response. Transportation Res. Part A Policy Practice 39(7):671–690.Crossref, Google Scholar
- (2007) Mean field games. Japanese J. Math. 2(1):229–260.Crossref, Google Scholar
- (2021) Credit-based mobility management considering travelers’ budgeting behaviors under uncertainty. Transportation Sci. 55(2):297–314.Link, Google Scholar
- (2017) Interactive travel choices and traffic forecast in a doubly dynamical system with user inertia and information provision. Transportation Res. Part C Emerging Tech. 85:711–731.Crossref, Google Scholar
- (2010) Robust congestion pricing under boundedly rational user equilibrium. Transportation Res. Part B Methodological 44(1):15–28.Crossref, Google Scholar
- (1987) On boundedly rational user equilibrium in transportation systems. Transportation Sci. 21(2):89–99.Link, Google Scholar
- (2024) A game-theoretic framework for generic second-order traffic flow models using mean field games and adversarial inverse reinforcement learning. Transportation Sci. 58(6):1403–1426.Link, Google Scholar
- (1997) Projected dynamical systems in the formulation, stability analysis, and computation of fixed-demand traffic network equilibria. Transportation Sci. 31(2):147–158.Link, Google Scholar
- (1984) An efficient method for computing traffic equilibria in networks with asymmetric transportation costs. Transportation Sci. 18(2):185–202.Link, Google Scholar
- Perolat J, Perrin S, Elie R, Laurière M, Piliouras G, Geist M, Tuyls K, Pietquin O (2022) Scaling mean field games by online mirror descent. Sonenberg L, Stone P, Tumer K, Yolum P, eds. Proc. 21st Internat. Conf. Autonomous Agents Multiagent Systems, vol. 2 (International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC), 1028–1037.Google Scholar
- Perrin S, Pérolat J, Laurière M, Geist M, Elie R, Pietquin O (2020) Fictitious play for mean field games: Continuous time analysis and applications. Larochelle H, Ranzato M, Hadsell R, Balcan MF, Lin H, eds. Adv. Neural Inform. Processing Systems, vol. 33 (Curran Associates, Inc, Red Hook, NY), 13199–13213.Google Scholar
- (2023) Investigating day-to-day route choices based on multi-scenario laboratory experiments, part I: Route-dependent attraction and its modeling. Transportation Res. Part A Policy Practice 167:103553.Crossref, Google Scholar
- (2022) Multi-agent reinforcement learning for Markov routing games: A new modeling paradigm for dynamic traffic assignment. Transportation Res. Part C Emerging Tech. 137:103560.Crossref, Google Scholar
- (1984) The stability of a dynamic model of traffic assignment—An application of a method of Lyapunov. Transportation Sci. 18(3):245–252.Link, Google Scholar
- (2000) Modeling inertia and compliance mechanisms in route choice behavior under real-time information. Transportation Res. Rec. 1725(1):45–53.Crossref, Google Scholar
- (2018) A mean-field game method for decentralized charging coordination of a large population of plug-in electric vehicles. IEEE Systems J. 13(1):854–863.Crossref, Google Scholar
- (2020) The habit-driven life: Accounting for inertia in departure time choices for commuting trips. Transportation Res. Part A Policy Practice 133:272–289.Crossref, Google Scholar
- (2024a) Learning to generate synthetic human mobility data: A physics-regularized Gaussian process approach based on multiple kernel learning. Transportation Res. Part B Methodological 189:103064.Crossref, Google Scholar
- (2024b) Correcting missingness in passively-generated mobile data with multi-task Gaussian processes. Transportation Res. Part C Emerging Tech. 161:104523.Crossref, Google Scholar
- (1969) Congestion theory and transport investment. Amer. Econom. Rev. 59(2):251–260.Google Scholar
- (1952) Some theoretical aspects of road traffic research. Proc. Inst. Civil Engrg. 1(3):325–362.Crossref, Google Scholar
- (1999) Stability of the stochastic equilibrium assignment problem: A dynamical systems approach. Transportation Res. Part B Methodological 33(4):281–312.Crossref, Google Scholar
- (2015) Combined route choice and adaptive traffic control in a day-to-day dynamical system. Networks Spatial Econom. 15(3):697–717.Crossref, Google Scholar
- (2016) Physics of day-to-day network flow dynamics. Transportation Res. Part B Methodological 86:86–103.Crossref, Google Scholar
- Xie Q, Yang Z, Wang Z, Minca A (2021) Learning while playing in mean-field games: Convergence and optimality. Meila M, Zhang T, eds. Proc. 38th Internat. Conf. Machine Learn., Proceedings of Machine Learning Research, vol. 139 (PMLR, Cambridge, MA), 11436–11447.Google Scholar
- (2009) Day-to-day stationary link flow pattern. Transportation Res. Part B Methodological 43(1):119–126.Crossref, Google Scholar
- (2021) Day-to-day dynamics with advanced traveler information. Transportation Res. Part B Methodological 144:23–44.Crossref, Google Scholar
- (1996) On the local and global stability of a travel route choice adjustment process. Transportation Res. Part B Methodological 30(4):245–262.Crossref, Google Scholar
- (2015) Modeling route choice inertia in network equilibrium with heterogeneous prevailing choice sets. Transportation Res. Part C Emerging Tech. 57:42–54.Crossref, Google Scholar

