Incorporating Trip-Chaining Behavior into Network Equilibrium Analysis

The network equilibrium model is a useful tool for long-term transportation planning and is one promising alternative to the traditional four-step travel forecasting model. However, some issues with the model remain to be considered. For example, almost all variations of the model adhere to the traditional trip-based approach, in which trip chains made by users are treated as separate, independent entities in the analysis. This research aims to develop a simple, tractable model to overcome this problem. One proposed model is based on piston-type trip chaining, and another accommodates any other type of trip chaining and includes congestion phenomena. These proposed models have certain key features: they have been successfully formulated as convex minimization problems, so uniqueness and algorithm convergence are easily proved; traveler behavior is based on theoretically sound random utility models, which allows the benefit of transportation projects to be calculated such that it is consistent with travel demand forecasting; and optimal road pricing can be calculated even in large-scale networks. These models are examined with the use of simple network examples, with special attention paid to the effect of trip-chaining behavior at the level of second-best toll. In a simple two-destination network, the second-best toll of the trip-based model is lower than that of trip chain-based model, indicating one of the biases of the trip-based model.

[1]  Takuya Maruyama,et al.  ESTIMATION OF USER BENEFITS OF ROAD INVESTMENT CONSIDERING INDUCED TRAFFIC WITH COMBINED NETWORK EQUILIBRIUM MODE IN TOKYO AREA , 2002 .

[2]  Hillel Bar-Gera,et al.  Multiclass Combined Models for Urban Travel Forecasting , 2004 .

[3]  David Boyce,et al.  Is the sequential travel forecasting paradigm counterproductive , 2002 .

[4]  Yosef Sheffi,et al.  Urban Transportation Networks: Equilibrium Analysis With Mathematical Programming Methods , 1985 .

[5]  Moshe Ben-Akiva,et al.  PII: S0965-8564(99)00043-9 , 2000 .

[6]  H H P Van Zwam,et al.  Application of Disaggregate Models for a Regional Transportation Study in the Netherlands , 1983 .

[7]  Shing Chung Josh Wong,et al.  A combined distribution, hierarchical mode choice, and assignment network model with multiple user and mode classes , 2004 .

[8]  M. Florian,et al.  A Multi-Class Multi-Mode Variable Demand Network Equilibrium Model with Hierarchical Logit Structures , 2002 .

[9]  H. Pietrantonio.  URBAN TRAVEL DEMAND MODELING: FROM INDIVIDUAL CHOICES TO GENERAL EQUILIBRIUM , 1997 .

[10]  Yoram Shiftan,et al.  Practical Approach to Model Trip Chaining , 1998 .

[11]  Xiaoning Zhang,et al.  The optimal cordon-based network congestion pricing problem , 2004 .

[12]  C. B. Mcguire,et al.  Studies in the Economics of Transportation , 1958 .

[13]  Ennio Cascetta,et al.  Transportation Systems Engineering: Theory and Methods , 2001 .

[14]  Ryuichi Kitamura,et al.  Incorporating trip chaining into analysis of destination choice , 1984 .

[15]  M. Ben-Akiva,et al.  A THEORETICAL AND EMPIRICAL MODEL OF TRIP CHAINING BEHAVIOR , 1979 .

[16]  David E. Boyce,et al.  Origin-based algorithms for combined travel forecasting models , 2003 .

[17]  David E. Boyce,et al.  Validation of Multiclass Urban Travel Forecasting Models Combining Origin-Destination, Mode, and Route Choices , 2003 .

[18]  T. Abrahamsson,et al.  Formulation and Estimation of Combined Network Equilibrium Models with Applications to Stockholm , 1999, Transp. Sci..

[19]  Hai Yang,et al.  Transport bilevel programming problems: recent methodological advances , 2001 .

[20]  William H. K. Lam,et al.  An activity-based time-dependent traffic assignment model , 2001 .

[21]  Shing Chung Josh Wong,et al.  COMBINED DISTRIBUTION, HIERARCHICAL MODE CHOICE, AND ASSIGNMENT NETWORK MODEL WITH MULTIPLE USER AND MODE CLASSES. IN: URBAN AND REGIONAL TRANSPORTATION MODELING. ESSAYS IN HONOR OF DAVID BOYCE , 2004 .