Abstract

We propose a dynamic combined-mode traffic network model considering transfer behaviors. We assume that travelers can be classified into two classes: one class is pure-mode travelers who complete a trip by single transportation mode, and another is combined-mode travelers who cover a journey by car, bus, and so forth. The multimode point queue model is used to model the interaction of cars and buses on the network. We present an integrated variational inequality formulation to capture the complex traveler choice behaviors such as departure time choices, transfer point, and route choices. Finally, a numerical example is given to illustrate the effectiveness of the proposed heuristic algorithm and model.

Highlights

  • Many researchers have been devoted to static multimodal network models and algorithms

  • The previous models have assumed that a trip from origin to destination is completed by taking only one single mode

  • Fernandez [3] denoted a trip that occurs on one single mode as a “pure-mode” trip

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Summary

Introduction

Many researchers have been devoted to static multimodal network models and algorithms. E lower-level program models the static multimodal traffic equilibrium problem with combined mode. E multiple traveler behaviors (mode, route, transfer point choice, etc.) can be integrated into a general variational inequality formulation. Kim et al [6] used discrete choice modeling to develop equivalent mathematical programming formulations for the combined modal split and traffic assignment problem that explicitly considers mode and route similarities under congested networks. Liu et al [8] presented a combined modal split and traffic assignment model to evaluate the impacts of park-and-ride behavior on the network flows. The conceptual dynamic traffic network model with the combined mode is proposed in this paper. A dynamic traffic network model with combined mode under hierarchical structures can be formulated in an integrated way as a variational inequality problem. A numerical example is given to demonstrate the effectiveness of the proposed model and algorithm

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