Analysis of real-time control strategies in a corridor with multiple bus services

Control strategies have been widely used in the literature to counteract the effects of bus bunching in passenger‘s waiting times and its variability. These strategies have only been studied for the case of a single bus line in a corridor. However, in many real cases this assumption does not hold. Indeed, there are many transit corridors with multiple bus lines interacting, and this interaction affects the efficiency of the implemented control mechanism.

[1]  Ricardo Giesen,et al.  BRRT: adding an R for reliability , 2016 .

[2]  Aldo Cipriano,et al.  Comparison of dynamic control strategies for transit operations , 2013 .

[3]  Caroline S. Fisk,et al.  A Conceptual Framework for Optimal Transportation Systems Planning with Integrated Supply and Demand Models , 1986, Transp. Sci..

[4]  David Bernstein,et al.  The Holding Problem with Real - Time Information Available , 2001, Transp. Sci..

[5]  C. Fisk.  GAME THEORY AND TRANSPORTATION SYSTEMS MODELLING , 1984 .

[6]  Joseph N. Prashker,et al.  The applicability of non-cooperative game theory in transport analysis , 2006 .

[7]  Mark D. Hickman,et al.  An Analytic Stochastic Model for the Transit Vehicle Holding Problem , 2001, Transp. Sci..

[8]  Ricardo Giesen,et al.  How much can holding and/or limiting boarding improve transit performance? , 2012 .

[9]  Donald D. Eisenstein,et al.  A self-coördinating bus route to resist bus bunching , 2012 .

[10]  Qin Chen,et al.  Implementation of an iterative headway-based bus holding strategy with real-time information , 2013, Public Transp..

[11]  David H. Reiley,et al.  'The War for the Fare': How Driver Compensation Affects Bus System Performance , 2005 .

[12]  A Evans.  A THEORETICAL COMPARISON OF COMPETITION WITH OTHER ECONOMIC REGIMES FOR BUS SERVICES , 1987 .

[13]  José R. Correa,et al.  Common-Lines and Passenger Assignment in Congested Transit Networks , 2001, Transp. Sci..

[14]  Carlos F. Daganzo,et al.  Reducing bunching with bus-to-bus cooperation , 2011 .

[15]  Walter Ukovich,et al.  Two-Player Noncooperative Games over a Freight Transportation Network , 2004, Transp. Sci..

[16]  William H. K. Lam,et al.  THE GENERALIZED NASH EQUILIBRIUM MODEL FOR OLIGOPOLISTIC TRANSIT MARKET WITH ELASTIC DEMAND , 2005 .

[17]  Zi-You Gao,et al.  An equilibrium model for urban transit assignment based on game theory , 2007, Eur. J. Oper. Res..

[18]  Omar J. Ibarra-Rojas,et al.  Planning, operation, and control of bus transport systems: A literature review , 2015 .

[19]  Saeed Zolfaghari,et al.  A Model For Holding Strategy In Public Transit Systems With Real-Time Information , 2004 .

[20]  Ricardo Giesen,et al.  Real-Time Control of Buses in a Transit Corridor Based on Vehicle Holding and Boarding Limits , 2009 .

[21]  Liping Fu,et al.  Design and Implementation of Bus–Holding Control Strategies with Real-Time Information , 2002 .

[22]  Cristián E. Cortés,et al.  Hybrid predictive control for real-time optimization of public transport systems' operations based on evolutionary multi-objective optimization , 2010 .

[23]  Michael Florian,et al.  Optimal strategies: A new assignment model for transit networks , 1989 .

[24]  William Phillips,et al.  Quantifying the effects of driver non-compliance and communication system failure in the performance of real-time bus control strategies , 2015 .

[25]  James W. Friedman,et al.  Oligopoly and the theory of games , 1977 .

[26]  Lourdes Zubieta,et al.  A network equilibrium model for oligopolistic competition in city bus services 1 1 This work was par , 1998 .