Ideal Flow Traffic Analysis: A Case Study on a Campus Road Network

Kardi Teknomo1, Roselle Wednesday Gardon2*, and Czarina Saloma3

1Department of Information Systems and Computer Science,
Ateneo de Manila University, Quezon City 1108 Philippines
2School of Computing and Information Technologies,
Asia Pacific College, Makati City 1232 Philippines
3Department of Sociology and Anthropology,
Ateneo de Manila University, Quezon City 1108 Philippines

*Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.



Traditional traffic assignment models often use historical travel demand, such as the costly origin-destination flow distribution and actual flow distribution, as inputs in determining the most efficient distribution of flow on a road network. In this paper, the authors examine the ideal flow network (IFN) model, a novel and alternative traffic assignment model. The IFN model is compared with a traditional traffic assignment model using a generic model comparison method. The application of the method is presented using a campus road network as a case study to examine the importance of understanding the road network structure – by making a comparison between the results of a traditional traffic assignment model and the IFN model to gain nuanced insights into the distribution of the traffic flow. The authors suggest that – while both models can yield almost the same result – the IFN model has the advantage of using a stochastic matrix, which is more readily available than demand data. The IFN model is likewise more geared toward evaluating the ideas of solving the traffic problem through simulation modeling, which – as a form of social engineering – is easier to stabilize into traffic management.


Traffic congestion has always been a perennial problem, especially on important roads such as those located in densely populated metropolitan areas. The problem of congestion is not easy to handle, and varied solutions have been suggested and implemented to address the challenge. These solutions necessitate the creation of, or the improvement of, existing traffic assignment models. Traditional traffic assignment models make use of historical travel demand data, specifically from the costly origin-destination (OD) survey. This is a difficulty for low-income societies, especially those with limited OD data or minimal budget for data collection. It is beneficial, therefore, to view traffic assignment from both sides of supply (road infrastructure) and demand rather than merely from the demand side. This is the uniqueness and novelty of the Ideal Flow Network (IFN) model (Teknomo 2017, Teknomo & Gardon 2017). The IFN models the ideal flow matrix with which one can measure the efficiency of the current traffic flow. In other words, one can use the flow matrix generated by the model as a guide to how the current traffic flow should be managed. . . . . read more



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