Traffic congestion problem is one of the major problems that face many transportation decision makers for urban areas. The problem has many impacts on social, economical and development aspects of urban areas. Hence the solution to this problem is not straight forward. It requires a lot of effort, expertise, time and cost that sometime are not available. Most of the existing transportation planning software, specially the most advanced ones, requires personnel with lots practical transportation planning experience and with high level of education and training. In this paper we propose a comprehensive framework for an Intelligent Decision Support System (IDSS) for Traffic Congestion Management System that utilizes a state of the art transportation network equilibrium modeling and providing an easy to use GIS-based interaction environment. The developed IDSS reduces the dependability on the expertise and level of education of the transportation planners, transportation engineers, or any transportation decision makers.
Single class travel forecasting models assume that all travelers are similar in their travel-decision characteristics, such as their money-value of the time and their sensitivity to travel times in choosing their origin, destination and mode of travel, etc. To obtain more realistic models, travelers are often divided into classes, either by socio-economic attributes (e.g., income level, car availability, etc.) or by the purpose (e.g., home-based-work, non-home-based-work, home-based-shopping, etc.) of their travel, assuming that travel-decision characteristics are the same within each class, but differ among classes. However, the development of this concept of multiple classes increases the mathematical complexity of travel forecasting models. All the existing multiclass combined models consider the trip generation step of transportation planning process is exogenous to the combined prediction process. In this paper we enhance the Simultaneous Transportation Equilibrium Model (STEM) that developed by Safwat and Magnanti in 1988, and explicitly combined trip generation step, to be a multiclass model in terms of socio-economic group, trip purpose, pure and combined transportation modes, as well as departure time, all interacting over a physically unique multimodal network. The developed Multiclass Simultaneous Transportation Equilibrium Model (MSTEM) is formulated as a Variational Inequality problem and a diagonalization algorithm is proposed to solve it. Copyright Springer Science+Business Media, LLC 2007Simultaneous transportation equilibrium models, Multiclass combined models, Multimodal network, Variational inequality, Diagonalization algorithm, Departure time,
The approach used in practice to predict short-run transport equilibria involves a sequential process, often with four stages: trip generation, trip distribution, modal split, and traffic assignment. This approach has an inherent weakness—its prediction need not be internally consistent. This deficiency has motivated attempts to predict all four stages simultaneously. The (conventional) sequential and simultaneous models are compared by calibrating and applying both models to the urban transportation network of Riyadh, Saudi Arabia. The main finding is that the simultaneous model produces better traffic flow predictions than the prediction of the conventional sequential model. These predictions are much better for the heavy volume links that are the most important links in the prediction process.
Between 1990 and 1997 intraregional trade was very low among the member countries of the United Nations Economic and Social Commission for Western Asia (ESCWA). Their export share fell from 10.9% to 8.6% of their total world exports, and their import share rose from 9.1% to 10.4% of their total world imports. Among the main reasons were complicated, costly, and time-consuming border controls and customs formalities. To overcome these obstacles and to promote greater economic integration among its members, ESCWA developed an integrated transport system in the Arab Mashreq (ITSAM). ITSAM comprises three basic components: an integrated (multimodal) transport network, an associated information system, and a methodological framework for issue analysis and policy formulation. The present research focuses on the development of an international freight simultaneous transportation equilibrium model (IFSTEM) to predict equilibrium freight flow patterns (times and costs) that can describe the behaviors of exporters and importers of different commodities over an international multimodal network covering ESCWA member countries. IFSTEM is considered a central component of the ITSAM methodological framework. The application of IFSTEM to the prototype shows that the model satisfies the behavioral aspects of the freight system, and its solution procedure is computationally tractable. This should encourage the full implementation of IFSTEM (after its calibration process) as a policy analysis tool and a decision-support system for transport policy makers in the region. The approach can easily be extended and applied to other regions of the world.
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