Departure Time Choice Models in Urban Transportation Systems Based on Mean Field Games

References

• Adlakha S, Johari R (2013) Mean field equilibrium in dynamic games with strategic complementarities. Oper. Res. 61(4):971–989.Link, Google Scholar
• Akamatsu T, Wada K, Iryo T, Hayashi S (2018) Departure time choice equilibrium and optimal transport problems. Munich Personal RePEc Archive Paper 90361, University Library of Munich, Germany.Google Scholar
• Akamatsu T, Wada K, Iryo T, Hayashi S (2020) A new look at departure time choice equilibrium models with heterogeneous users. Preprint, submitted September 23, https://arxiv.org/abs/2009.11037.Google Scholar
• Alisoltani N, Leclercq L, Zargayouna M (2021) Can dynamic ride-sharing reduce traffic congestion? Transportation Res. Part B Methodological 145:212–246.Crossref, Google Scholar
• Alisoltani N, Zargayouna M, Leclercq L (2020a) A multi-agent system for real-time ride sharing in congested networks. Agents Multi-agent System: Tech. Appl (Springer), 333–342.Crossref, Google Scholar
• Alisoltani N, Zargayouna M, Leclercq L (2020b) Real-time autonomous taxi service: An agent-based simulation. Agents Multi-agent System: Tech. Appl (Springer), 199–207.Crossref, Google Scholar
• Alisoltani N, Leclercq L, Zargayouna M, Krug J 2019 Optimal fleet management for real-time ride-sharing service considering network congestion. 98th Annual Meeting Transportation Res. Board (Washington, DC).Google Scholar
• Ameli M (2019) Heuristic methods for calculating dynamic traffic assignment. Unpublished PhD thesis, the French Institute of Science and Technology for Transport, Development and Networks and Université de Lyon, Paris, France.Google Scholar
• Ameli M, Alisoltani N, Leclercq L (2021) Lyon North realistic trip data set during the morning peak. Accessed March 5, 2021, https://research-data.ifsttar.fr/dataset.xhtml?persistentId=doi:10.25578/HWN8KE.Google Scholar
• Ameli M, Lebacque JP, Leclercq L (2018) Day-to-day multimodal dynamic traffic assignment: Impacts of the learning process in case of non-unique solutions. DTA 2018 7th Internat. Sympos. Dynamic Traffic Assignment.Google Scholar
• Ameli M, Lebacque JP, Leclercq L (2020a) Cross-comparison of convergence algorithms to solve trip-based dynamic traffic assignment problems. Comput. Aided Civil Infrastructure Engrg. 35(3):219–240.Crossref, Google Scholar
• Ameli M, Lebacque JP, Leclercq L (2020b) Improving traffic network performance with road banning strategy: A simulation approach comparing user equilibrium and system optimum. Simulation Model. Practice Theory 99:101995.Crossref, Google Scholar
• Ameli M, Lebacque JP, Leclercq L (2020c) Simulation-based dynamic traffic assignment: Meta-heuristic solution methods with parallel computing. Comput. Aided Civil Infrastructure Engrg. 35(10):1047–1062.Crossref, Google Scholar
• Ameli M, Lebacque JP, Leclercq L (2021) Computational methods for calculating multimodal multiclass traffic network equilibrium: Simulation benchmark on a large-scale test case. J. Adv. Transportation 2021:8815653.Crossref, Google Scholar
• Ameli M, Faradonbeh MSS, Lebacque JP, Abouee-Mehrizi H, Leclercq L (2021) Mean field games framework to departure time choice equilibrium in urban traffic networks. TRB 2021 Transportation Res. Board 100th Annual Meeting.Google Scholar
• Arnott R (2013) A bathtub model of downtown traffic congestion. J. Urban Econom. 76:110–121.Crossref, Google Scholar
• Arnott R, Buli J (2018) Solving for equilibrium in the basic bathtub model. Transportation Res. Part B Methodological 109(C):150–175.Crossref, Google Scholar
• Arnott R, Kokoza A, Naji M (2016) Equilibrium traffic dynamics in a bathtub model: A special case. Econom. Transportation 7:38–52.Crossref, Google Scholar
• Ata B, Peng X (2018) An equilibrium analysis of a multiclass queue with endogenous abandonments in heavy traffic. Oper. Res. 66(1):163–183.Link, Google Scholar
• Aurell A, Djehiche B (2019) Modeling tagged pedestrian motion: A mean-field type game approach. Transportation Res. Part B Methodological 121:168–183.Crossref, Google Scholar
• Bao Y, Verhoef E, Koster P (2020) Leaving the tub: The nature and dynamics of hypercongestion in a bathtub model with a restricted downstream exit. Technical report, Tinbergen Institute Discussion Paper 20-003/VIII, Amsterdam.Google Scholar
• Ben-Akiva M, Bierlaire M (2003) Discrete choice models with applications to departure time and route choice. Hall RW, ed. Handbook of Transportation Science. Internat. Ser. Oper. Res. Management Sci., vol. 56 (Springer, Boston, MA), 7–37.Crossref, Google Scholar
• Billingsley P (2012) Probability and Measure, Wiley Series in Probability and Statistics (Wiley).Google Scholar
• Billingsley P (2013) Convergence of Probability Measures (John Wiley & Sons).Google Scholar
• Bortolomiol S, Lurkin V, Bierlaire M (2019) A disaggregate choice-based approach to find ε-equilibria of oligopolistic markets. Technical report, Transport and Mobility Laboratory, Ecole Polytechnique Fédérale de Lausanne, Lausanne.Google Scholar
• Caines PE, Huang M, Malhamé RP (2017) Mean field games. Basar T, Zaccour G, eds. Handbook of Dynamic Game Theory (Springer, Cham).Google Scholar
• Cardaliaguet P (2013) Notes on mean field games. Technical report, Université Paris-Dauphine, Paris, France.Google Scholar
• Cardaliaguet P (2018) A short course on mean field games. Unpublished lecture notes.Google Scholar
• Carmona R, Delarue F (2018) Probabilistic Theory of Mean Field Games with Applications I-II (Springer).Crossref, Google Scholar
• Chevalier G, Le Ny J, Malhamé R (2015) A micro-macro traffic model based on mean-field games. 2015 Amer. Control Conf. (IEEE), 1983–1988.Google Scholar
• Cominetti R, Correa J, Larré O (2015) Dynamic equilibria in fluid queueing networks. Oper. Res. 63(1):21–34.Link, Google Scholar
• Dafermos SSC (1968) Traffic Assignment and Resource Allocation in Transportation Networks (The Johns Hopkins University).Google Scholar
• Daganzo CF (1985) The uniqueness of a time-dependent equilibrium distribution of arrivals at a single bottleneck. Transportation Sci. 19(1):29–37.Link, Google Scholar
• Daganzo CF, Lehe LJ (2015) Distance-dependent congestion pricing for downtown zones. Transportation Res. Part B Methodological 75:89–99.Crossref, Google Scholar
• Daly A, Bar-Gera H (2021) Exploration of maximum-to-minimum shifts in generic methods for departure time choice models. Transportation Res. Rec. 2675(10):907–915.Crossref, Google Scholar
• Degond P, Liu JG, Ringhofer C (2014) Large-scale dynamics of mean-field games driven by local Nash equilibria. J. Nonlinear Sci. 24(1):93–115.Crossref, Google Scholar
• Djehiche B, Tcheukam A, Tembine H (2016) Mean-field-type games in engineering. Preprint, submitted May 11, https://arxiv.org/abs/1605.03281.Google Scholar
• Doan K, Ukkusuri S, Han L (2011) On the existence of pricing strategies in the discrete time heterogeneous single bottleneck model. Procedia Soc. Behav. Sci. 17(9):269–291.Crossref, Google Scholar
• Fosgerau M (2015) Congestion in the bathtub. Econom. Transportation 4(4):241–255.Crossref, Google Scholar
• Friesz TL, Han K (2019) The mathematical foundations of dynamic user equilibrium. Transportation Res. Part B Methodological 126:309–328.Crossref, Google Scholar
• Friesz TL, Bernstein D, Mehta NJ, Tobin RL, Ganjalizadeh S (1994) Day-to-day dynamic network disequilibria and idealized traveler information systems. Oper. Res. 42(6):1120–1136.Link, Google Scholar
• Friesz TL, Bernstein D, Smith TE, Tobin RL, Wie BW (1993) A variational inequality formulation of the dynamic network user equilibrium problem. Oper. Res. 41(1):179–191.Link, Google Scholar
• Guo RY, Yang H, Huang HJ (2018) Are we really solving the dynamic traffic equilibrium problem with a departure time choice? Transportation Sci. 52(3):603–620.Link, Google Scholar
• Guo RY, Yang H, Huang HJ, Li X (2018) Day-to-day departure time choice under bounded rationality in the bottleneck model. Transportation Res. Part B Methodological 117(B):832–849.Crossref, Google Scholar
• Hendrickson C, Kocur G (1981) Schedule delay and departure time decisions in a deterministic model. Transportation Sci. 15(1):62–77.Link, Google Scholar
• Huang K, Di X, Du Q, Chen X (2019) A game-theoretic framework for autonomous vehicles velocity control: Bridging microscopic differential games and macroscopic mean field games. Preprint, submitted March 14, https://arxiv.org/abs/1903.06053.Google Scholar
• Huang Y, Xiong J, Sumalee A, Zheng N, Lam W, He Z, Zhong R (2020) A dynamic user equilibrium model for multi-region macroscopic fundamental diagram systems with time-varying delays. Transportation Res. Part B Methodological 131:1–25.Crossref, Google Scholar
• Iryo T (2019) Instability of departure time choice problem: A case with replicator dynamics. Transportation Res. Part B Methodological 126:353–364.Crossref, Google Scholar
• Ji Y, Luo J, Geroliminis N (2014) Empirical observations of congestion propagation and dynamic partitioning with probe data for large-scale systems. Transportation Res. Rec. 2422(1):1–11.Crossref, Google Scholar
• Jin WL (2020a) Generalized bathtub model of network trip flows. Transportation Res. Part B Methodological 136:138–157.Crossref, Google Scholar
• Jin WL (2020b) Stable day-to-day dynamics for departure time choice. Transportation Sci. 54(1):42–61.Link, Google Scholar
• Krug J, Burianne A, Leclercq L (2019) Reconstituting demand patterns of the city of Lyon by using multiple GIS data sources. Technical report, University of Lyon, Transport and Traffic Engineering Laboratory, Postgraduate School of Transport and Civil Engineering, France.Google Scholar
• Lacker D (2018) Mean field games and interacting particle systems, preprint.Google Scholar
• Lamotte R (2018) Congestion and departure time choice equilibrium in urban road networks. Technical report, EPFL.Google Scholar
• Lamotte R, Geroliminis N (2016) The morning commute in urban areas: Insights from theory and simulation. 2016 TRB Annual Meeting Online (Transportation Research Board).Google Scholar
• Lamotte R, Geroliminis N (2018) The morning commute in urban areas with heterogeneous trip lengths. Transportation Res. Part B Methodological 117(B):794–810.Crossref, Google Scholar
• Lamotte R, Geroliminis N (2021) Monotonicity in the trip scheduling problem. Transportation Res. Part B Methodological 146:14–25.Crossref, Google Scholar
• Lamotte R, Murashkin M, Kouvelas A, Geroliminis N (2018) Dynamic modeling of trip completion rate in urban areas with MFD representations. 2018 TRB Annual Meeting Online, 18–06192 (Transportation Research Board).Google Scholar
• Lasry JM, Lions PL (2006) Jeux à champ moyen. I–le cas stationnaire. Comptes Rendus de l'Académie des Sciences Paris 343(9):619–625.Google Scholar
• Lasry JM, Lions PL (2007) Mean field games. Japanese J. Math. 2(1):229–260.Crossref, Google Scholar
• Leclercq L, Sénécat A, Mariotte G (2017) Dynamic macroscopic simulation of on-street parking search: A trip-based approach. Transportation Res. Part B Methodological 101:268–282.Crossref, Google Scholar
• Li ZC, Huang HJ, Yang H (2020) Fifty years of the bottleneck model: A bibliometric review and future research directions. Transportation Res. Part B Methodological 139:311–342.Crossref, Google Scholar
• Lindsey R (2004) Existence, uniqueness, and trip cost function properties of user equilibrium in the bottleneck model with multiple user classes. Transportation Sci. 38(3):293–314.Link, Google Scholar
• Lindsey R, De Palma A, Silva HE (2019) Equilibrium in a dynamic model of congestion with large and small users. Transportation Res. Part B Methodological 124:82–107.Crossref, Google Scholar
• Liu Y, Kang C, Gao S, Xiao Y, Tian Y (2012) Understanding intra-urban trip patterns from taxi trajectory data. J. Geographical Systems 14(4):463–483.Crossref, Google Scholar
• Mahmassani HS, Chang GL (1987) On boundedly rational user equilibrium in transportation systems. Transportation Sci. 21(2):89–99.Link, Google Scholar
• Mahmassani HS, Chang GL (1985) Dynamic aspects of departure time choice behavior in a commuting system: Theoretical framework and experimental analysis. Transportation Res. Rec. (1037):88–101.Google Scholar
• Mahmassani HS, Herman R (1984) Dynamic user equilibrium departure time and route choice on idealized traffic arterials. Transportation Sci. 18(4):362–384.Link, Google Scholar
• Mariotte G, Leclercq L, Laval JA (2017) Macroscopic urban dynamics: Analytical and numerical comparisons of existing models. Transportation Res. Part B Methodological 101:245–267.Crossref, Google Scholar
• Mariotte G, Leclercq L, Batista S, Krug J, Paipuri M (2020) Calibration and validation of multi-reservoir MFD models: A case study in Lyon. Transportation Res. Part B Methodological 136:62–86.Crossref, Google Scholar
• Nagel K, Wagner P, Woesler R (2003) Still flowing: Approaches to traffic flow and traffic jam modeling. Oper. Res. 51(5):681–710.Link, Google Scholar
• Noor MA (1988) General variational inequalities. Appl. Math. Lett. 1(2):119–122.Crossref, Google Scholar
• Perakis G, Roels G (2006) An analytical model for traffic delays and the dynamic user equilibrium problem. Oper. Res. 54(6):1151–1171.Link, Google Scholar
• Protter MH, Morrey CB Jr (2012) Intermediate Calculus (Springer Science & Business Media).Google Scholar
• Ramadurai G, Ukkusuri SV, Zhao J, Pang JS (2010) Linear complementarity formulation for single bottleneck model with heterogeneous commuters. Transportation Res. Part B Methodological 44(2):193–214.Crossref, Google Scholar
• Ran B, Boyce DE, LeBlanc LJ (1993) A new class of instantaneous dynamic user-optimal traffic assignment models. Oper. Res. 41(1):192–202.Link, Google Scholar
• Salhab R, Le Ny J, Malhamé RP (2018) A mean field route choice game model. 2018 IEEE Conf. Decision Control (IEEE), 1005–1010.Google Scholar
• Sandholm WH (2015) Population games and deterministic evolutionary dynamics. Peyton YH, Zamir S, eds. Handbook of Game Theory with Economic Applications, vol. 4 (Elsevier, Oxford, UK), 703–778.Google Scholar
• Sbayti H, Lu CC, Mahmassani H (2007) Efficient implementation of method of successive averages in simulation-based dynamic traffic assignment models for large-scale network applications. Transportation Res. Rec. 2029(1):22–30.Crossref, Google Scholar
• Sheffi Y (1985) Urban Transportation Networks, vol. 6 (Prentice-Hall, Englewood Cliffs, NJ).Google Scholar
• Smith MJ (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
• Sun X, Han X, Bao JZ, Jiang R, Jia B, Yan X, Zhang B, Wang WX, Gao ZY (2017) Decision dynamics of departure times: Experiments and modeling. Physica A 483:74–82.Crossref, Google Scholar
• Takayama Y, Kuwahara M (2017) Bottleneck congestion and residential location of heterogeneous commuters. J. Urban Econom. 100:65–79.Crossref, Google Scholar
• Tanaka T, Nekouei E, Pedram AR, Johansson KH (2020) Linearly solvable mean-field traffic routing games. IEEE Trans. Automatic Control 66(2):880–887.Crossref, Google Scholar
• Thomas T, Tutert S (2013) An empirical model for trip distribution of commuters in the Netherlands: Transferability in time and space reconsidered. J. Transport Geography 26:158–165.Crossref, Google Scholar
• Tsekeris T, Geroliminis N (2013) City size, network structure and traffic congestion. J. Urban Econom. 76(C):1–14.Crossref, Google Scholar
• Vickrey W (1969) Congestion theory and transport investment. Amer. Econom. Rev. 59(2):251–260.Google Scholar
• Vickrey W (1991) Congestion in Manhattan in relation to marginal cost pricing. Memo, Columbia University. Notational Glossary.Google Scholar
• Vickrey W (1994) Types of congestion pricing models. Memo, Columbia University. Notational Glossary.Google Scholar
• Vickrey W (2019) Types of congestion pricing models. Econom. Transportation 20:100140.Crossref, Google Scholar
• Vickrey W (2020) Congestion in midtown Manhattan in relation to marginal cost pricing. Econom. Transportation 21:100152.Crossref, Google Scholar
• Wang Y, Szeto W, Han K, Friesz TL (2018) Dynamic traffic assignment: A review of the methodological advances for environmentally sustainable road transportation applications. Transportation Res. Part B Methodological 111:370–394.Crossref, Google Scholar
• Wardrop JG (1952) Road paper. Some theoretical aspects of road traffic research. Proc. Institute Civil Engineers 1(3):325–362.Crossref, Google Scholar
• Yang F (2005) An Evolutionary Game Theory Approach to the Day-to-Day Traffic Dynamics (The University of Wisconsin-Madison).Google Scholar
• Zhong R, Sumalee A, Friesz TL, Lam WH (2011) Dynamic user equilibrium with side constraints for a traffic network: Theoretical development and numerical solution algorithm. Transportation Res. Part B Methodological 45(7):1035–1061.Crossref, Google Scholar