00000caa a22000003i 4500 UP-1685594773862388620 Buklod 20210322153035.0 m | | ta 210318s2019 xx r |||| u|eng d (iLib)UPBAG-00039569048 STII-DOST BAG rda eng ARTICLE-2805 Teknomo, Kardi author. Ideal flow traffic analysis a case study on a campus road network by Kardi Teknomo, Roselle Wednesday Gardon, and Czarina Saloma. 2019. pages 51-62 illustrations, map (some color) 26 cm text rdacontent unmediated rdamedia volume rdacarrier Includes bibliographical references (pages 61-62) 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. (Author's abstract) Ideal flow analysis. Information and communications technology. Traffic analysis. Traffic assignment model. Saloma, Czarina author. Gardon, Roselle Wednesday author. The Philippine Journal of Science Vol. 148, no. 1, March 2019. Request full-text access via UPB University Library through https://forms.gle/KZjBv7aRtY6jiL5E9 (viewed 18 March 2021) FI UPBAG UPBAG-MAIN ARTICLE-2805 Analytics