Optimal combinations of selected tactics for public-transport transfer synchronization

Handling efficiently and effectively real-time vehicle control is of major concern of public transport (PT) operators. One related problem is on how to reduce the uncertainty of simultaneous arrivals of two or more vehicles at a transfer point. Improper or lack of certain control actions leads to have missed transfers, one of the undesirable features of the PT service. Missed transfers result in increase of passenger waiting and travel times, and of passenger frustration. This work focuses on reducing the uncertainty of missed transfers by the use of control tactics in real-time operation. The developed model improves the PT service performance by optimally increasing the number of direct transfers and reducing the total passenger travel time. This model consists of two policies built upon a combination of two tactics: holding and skip-stop/segment, where a segment is a group of stops. The implementation of the concept is performed in two steps: optimization and simulation. The optimization searches for the best combination of operational tactics. The simulation serves as a validation of the optimal results under a stochastic framework. A case in Auckland, New Zealand is used. The results show that by applying the holding-skip stop, and holding-skip segment tactics the number of direct transfers are increased by about 100% and 150%, and the total passenger travel time is reduced by 2.14% and 4.1%, respectively, compared with the no-tactic scenario. The holding-skip segment tactic results with 47% more direct transfers than the holding-skip stop tactic for short headway operation.

[1]  R. Adam Molnar Bus Arrivals and Bunching , 2008 .

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

[3]  G. F. Newell Control of Pairing of Vehicles on a Public Transportation Route, Two Vehicles, One Control Point , 1974 .

[4]  Maged Dessouky,et al.  REAL-TIME CONTROL OF BUSES FOR SCHEDULE COORDINATION AT A TERMINAL , 2003 .

[5]  Felipe Delgado,et al.  Holding for Transfers , 2013 .

[6]  Zhiyuan Liu,et al.  Bus stop-skipping scheme with random travel time , 2013 .

[7]  Steve Callas,et al.  DETERMINANTS OF BUS DWELL TIME , 2004 .

[8]  John N. Hooker,et al.  Operations Research Methods in Constraint Programming , 2006, Handbook of Constraint Programming.

[9]  Mark A. Turnquist,et al.  EVALUATING POTENTIAL EFFECTIVENESS OF HEADWAY CONTROL STRATEGIES FOR TRANSIT SYSTEMS , 1980 .

[10]  Jean-Marc Rousseau,et al.  Real-Time Scheduling on a Transit Bus Route , 1992 .

[11]  Ted Eschenbach,et al.  Spiderplots versus Tornado Diagrams for Sensitivity Analysis , 1992 .

[12]  A. Barnett On Controlling Randomness in Transit Operations , 1974 .

[13]  Carlos F. Daganzo,et al.  A headway-based approach to eliminate bus bunching: Systematic analysis and comparisons , 2009 .

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

[15]  Mark D. Hickman,et al.  The Real–Time Stop–Skipping Problem , 2005, J. Intell. Transp. Syst..

[16]  Avishai Ceder,et al.  Transfer Synchronization of Public Transport Networks , 2013 .

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

[18]  Mark A. Turnquist,et al.  THE EFFECTS OF NETWORK STRUCTURE ON RELIABILITY OF TRANSIT SERVICE , 1980 .

[19]  Avishai Ceder,et al.  Improving Bus Passenger Transfers on Road Segments through Online Operational Tactics , 2007 .

[20]  Avishai Ceder,et al.  Public Transit Network Connectivity , 2010 .

[21]  Avishai Ceder,et al.  Optimal coordination of public transit vehicles using operational tactics examined by simulation , 2008 .

[22]  Nigel H. M. Wilson,et al.  Modeling real-time control strategies in public transit operations , 1999 .