Hyperpaths in Network Based on Transit Schedules

The concept of a hyperpath was introduced for handling passenger strategies in route choice behavior for public transit, especially in a frequency-based transit service environment. This model for handling route choice behavior has been widely used for planning transit services, and hyperpaths are now applied in areas beyond public transit. A hyperpath representing more specific passenger behaviors on a network based on transit schedules is proposed. A link-based time-expanded (LBTE) network for transit schedules is introduced; in the network each link represents a scheduled vehicle trip (or trip segment) with departure time and travel time (or arrival time) between two consecutive stops. The proposed LBTE network reduces the effort to build a network based on transit schedules because the network is expanded with scheduled links. A link-based representation of a hypergraph with existing hyperpath model properties that is directly integrated with the LBTE network is also proposed. Transit passenger behavior was incorporated for transfers in the link-based hyperpath. The efficiency of the proposed hyperpath model was demonstrated. The proposed models were applied on a test network and a real transit network represented by the general specification of Google's transit feed.

[1]  Daniele Pretolani,et al.  Finding the K shortest hyperpaths using reoptimization , 2006, Oper. Res. Lett..

[2]  Daniele Pretolani,et al.  Finding the K shortest hyperpaths , 2005, Comput. Oper. Res..

[3]  Umberto Crisalli,et al.  A Doubly Dynamic Schedule-based Assignment Model for Transit Networks , 2001, Transp. Sci..

[4]  Giovanni Storchi,et al.  Shortest viable path algorithm in multimodal networks , 2001 .

[5]  Giorgio Gallo,et al.  Directed Hypergraphs and Applications , 1993, Discret. Appl. Math..

[6]  Federico Malucelli,et al.  A Modeling Framework for Passenger Assignment on a Transport Network with Timetables , 1998, Transp. Sci..

[7]  C. O. Tong,et al.  A computer model for finding the time-dependent minimum path in a transit system with fixed schedules , 1984 .

[8]  Michel Gendreau,et al.  Implicit Enumeration of Hyperpaths in a Logit Model for Transit Networks , 1992, Transp. Sci..

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

[10]  Susan Buck-Morss,et al.  Exchange , 1919, The Indian medical gazette.

[11]  Patrice Marcotte,et al.  Hyperpath Formulations of Traffic Assignment Problems , 1998 .

[12]  Achille Fonzone,et al.  SCHEDULE-BASED HYPERPATH APPROACHES TO TRANSIT ASSIGNMENT: THE IMPACT OF IMPERFECT INFORMATION , 2010 .

[13]  Shing Chung Josh Wong,et al.  A dynamic schedule-based model for congested transit networks , 2004 .

[14]  S. Pallottino,et al.  Hyperpaths and shortest hyperpaths , 1989 .

[15]  Siriphong Lawphongpanich,et al.  Schedule-based transit assignment model with travel strategies and capacity constraints , 2008 .

[16]  Otto Anker Nielsen,et al.  Optimisation of timetable-based, stochastic transit assignment models based on MSA , 2006, Ann. Oper. Res..

[17]  Michael G.H. Bell.  Hyperstar: A multi-path Astar algorithm for risk averse vehicle navigation , 2009 .

[18]  Otto Anker Nielsen,et al.  Large-scale schedule-based transit assignment – further optimization of the solution algorithms , 2009 .

[19]  Athanasios K. Ziliaskopoulos,et al.  An intermodal optimum path algorithm for multimodal networks with dynamic arc travel times and switching delays , 2000, Eur. J. Oper. Res..

[20]  R. M. Oliver,et al.  Flows in transportation networks , 1972 .