Efficient and fair system states in dynamic transportation networks

Abstract This paper sets out to model an efficient and fair transportation system accounting for both departure time choice and route choice of a general multi-OD network within a dynamic traffic assignment environment. Firstly, a bi-level optimization formulation is introduced based on the link-based traffic flow model. The upper level of the formulation minimizes the total system travel time, whereas the lower level captures traffic flow propagation and the user equilibrium constraints. Then the bi-level formulation is relaxed to a linear programming formulation that produces a lower bound of an efficient and fair system state. An efficient iterative algorithm is proposed to obtain the exact solution. It only requires solving one linear program in one iteration. Further, it is shown that the number of iterations is bounded, and the output traffic flow pattern is efficient and fair. Finally, two numerical cases (including a single OD network and a multi-OD network) are conducted to demonstrate the performance of the algorithm. The results consistently show that the departure rate pattern generated from the algorithm leads to an efficient and fair system state, and the algorithm converges within two iterations across all test scenarios.

[1]  Athanasios K. Ziliaskopoulos,et al.  A Linear Programming Model for the Single Destination System Optimum Dynamic Traffic Assignment Problem , 2000, Transp. Sci..

[2]  S. Lawphongpanich,et al.  Solving the Pareto-improving toll problem via manifold suboptimization , 2010 .

[3]  H. Simon,et al.  Bounded Rationality and Organizational Learning , 1991 .

[4]  Hai Yang,et al.  Pareto-improving congestion pricing and revenue refunding with multiple user classes , 2010 .

[5]  José R. Correa,et al.  Fast, Fair, and Efficient Flows in Networks , 2007, Oper. Res..

[6]  Tim Roughgarden,et al.  How bad is selfish routing? , 2002, JACM.

[7]  W. Y. Szeto,et al.  Elastic demand dynamic network user equilibrium: Formulation, existence and computation , 2013, 1304.5286.

[8]  Malachy Carey,et al.  Optimal Time-Varying Flows on Congested Networks , 1987, Oper. Res..

[9]  Guido Gentile,et al.  Solving a Dynamic User Equilibrium model based on splitting rates with Gradient Projection algorithms , 2016 .

[10]  Lanshan Han,et al.  Dynamic user equilibrium with a path based cell transmission model for general traffic networks , 2012 .

[11]  Jong-Shi Pang,et al.  Continuous-time dynamic system optimum for single-destination traffic networks with queue spillbacks , 2014 .

[12]  Satish V. Ukkusuri,et al.  Dynamic system optimal model for multi-OD traffic networks with an advanced spatial queuing model , 2015 .

[13]  J. Ho A Successive Linear Optimization Approach to the Dynamic Traffic Assignment Problem , 1980 .

[14]  Hai Yang,et al.  On the price of anarchy for non-atomic congestion games under asymmetric cost maps and elastic demands , 2008, Comput. Math. Appl..

[15]  A. Sumalee,et al.  Dynamic marginal cost, access control, and pollution charge: a comparison of bottleneck and whole link models , 2012 .

[16]  Terry L. Friesz,et al.  A Variational Inequality Formulation of the Dynamic Network User Equilibrium Problem , 1993, Oper. Res..

[17]  Roger L. Tobin,et al.  Uniqueness and computation of an arc-based dynamic network user equilibrium formulation , 2002 .

[18]  José R. Correa,et al.  Sloan School of Management Working Paper 4447-03 November 2003 Computational Complexity , Fairness , and the Price of Anarchy of the Maximum Latency Problem , 2003 .

[19]  Henry X. Liu,et al.  A Link-Node Discrete-Time Dynamic Second Best Toll Pricing Model with a Relaxation Solution Algorithm , 2009 .

[20]  Christos H. Papadimitriou,et al.  Worst-case equilibria , 1999 .

[21]  Lanshan Han,et al.  Complementarity formulations for the cell transmission model based dynamic user equilibrium with departure time choice, elastic demand and user heterogeneity , 2011 .

[22]  Andy H.F. Chow Properties of system optimal traffic assignment with departure time choice and its solution method , 2009 .

[23]  T. Friesz,et al.  A Computable Theory of Dynamic Congestion Pricing , 2007 .

[24]  W. Y. Szeto,et al.  A cell-based variational inequality formulation of the dynamic user optimal assignment problem , 2002 .

[25]  W. Y. Szeto,et al.  Bounded Rationality in Dynamic Traffic Assignment , 2015 .

[26]  S. Travis Waller,et al.  A Combinatorial user optimal dynamic traffic assignment algorithm , 2006, Ann. Oper. Res..

[27]  W. Y. Szeto,et al.  An Intersection-Movement-Based Dynamic User Optimal Route Choice Problem , 2013, Oper. Res..

[28]  B Wie,et al.  DYNAMIC SYSTEM OPTIMAL TRAFFIC ASSIGNMENT ON CONGESTED MULTIDESTINATION NETWORKS , 1990 .

[29]  Rolf H. Möhring,et al.  System-optimal Routing of Traffic Flows with User Constraints in Networks with Congestion System-optimal Routing of Traffic Flows with User Constraints in Networks with Congestion , 2022 .

[30]  Clermont Dupuis,et al.  An Efficient Method for Computing Traffic Equilibria in Networks with Asymmetric Transportation Costs , 1984, Transp. Sci..

[31]  T. Friesz,et al.  Dynamic Congestion and Tolls with Mobile Source Emission , 2012, 1208.4341.

[32]  Yu Nie A Cell-based Merchant-Nemhauser Model for the System Optimum Dynamic Traffic Assignment Problem , 2010 .

[33]  Satish V. Ukkusuri,et al.  Linear Programming Models for the User and System Optimal Dynamic Network Design Problem: Formulations, Comparisons and Extensions , 2008 .

[34]  Yafeng Yin,et al.  Nonnegative Pareto-Improving Tolls with Multiclass Network Equilibria , 2009 .

[35]  Satish V. Ukkusuri,et al.  A cell based dynamic system optimum model with non-holding back flows , 2013 .

[36]  Wei Shen,et al.  System optimal dynamic traffic assignment: Properties and solution procedures in the case of a many-to-one network , 2014 .

[37]  Wen-Long Jin,et al.  Continuous formulations and analytical properties of the link transmission model , 2014, 1405.7080.

[38]  Satish V. Ukkusuri,et al.  A linear programming formulation for autonomous intersection control within a dynamic traffic assignment and connected vehicle environment , 2015 .

[39]  Wei Shen,et al.  System-optimal dynamic traffic assignment with and without queue spillback: Its path-based formulation and solution via approximate path marginal cost , 2012 .

[40]  Malachy Carey,et al.  Externalities, Average and Marginal Costs, and Tolls on Congested Networks with Time-Varying Flows , 1993, Oper. Res..

[41]  W. Y. Szeto,et al.  A CELL-BASED SIMULTANEOUS ROUTE AND DEPARTURE TIME CHOICE MODEL WITH ELASTIC DEMAND , 2004 .

[42]  Hai Yang,et al.  The toll effect on price of anarchy when costs are nonlinear and asymmetric , 2008, Eur. J. Oper. Res..

[43]  Faculteit Ingenieurswetenschappen,et al.  The Link Transmission Model for Dynamic Network Loading , 2007 .

[44]  Bin Ran,et al.  for dynamic user equilibria with exact flow propagations , 2008 .

[45]  Athanasios K. Ziliaskopoulos,et al.  Foundations of Dynamic Traffic Assignment: The Past, the Present and the Future , 2001 .

[46]  George L. Nemhauser,et al.  Optimality Conditions for a Dynamic Traffic Assignment Model , 1978 .

[47]  Hani S. Mahmassani,et al.  System optimal and user equilibrium time-dependent traffic assignment in congested networks , 1995, Ann. Oper. Res..

[48]  Terry L. Friesz,et al.  Dynamic Network Traffic Assignment Considered as a Continuous Time Optimal Control Problem , 1989, Oper. Res..

[49]  W. Y. Szeto,et al.  Formulation, existence, and computation of boundedly rational dynamic user equilibrium with fixed or endogenous user tolerance , 2014, 1402.1211.

[50]  Mike Smith,et al.  A model for the dynamic system optimum traffic assignment problem , 1995 .

[51]  Deepak K. Merchant,et al.  A Model and an Algorithm for the Dynamic Traffic Assignment Problems , 1978 .

[52]  W. Y. Szeto,et al.  Emission Modeling and Pricing in Dynamic Traffic Networks , 2015 .

[53]  Henry X. Liu,et al.  Boundedly Rational User Equilibria (BRUE): Mathematical Formulation and Solution Sets , 2013 .