Multidimensional Scaling and Application in Traffic Jam Prediction

Abstract:

Many methods thus have been proposed to predict traffic conditions. However, it is difficult to accurately predict traffic jam, because it requires a wide range of knowledge such as statistics and informational technology. It is known that the probability of traffic jam can be evaluated by travel times of passing cars in a location of the motorway. In this paper, we restrict our attention to finding more efficient statistical methods through comparing models. For this reason, we used Multidimensional Scaling statistical methods to study the relationship between traffic conditions and travel time in different locations and times. This work aims at applying basic models to forecast traffic conditions.

• Periodical: Applied Mechanics and Materials (Volumes 291-294)
• Pages: 3060-3063
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.291-294.3060
• Online since: February 2013
• Authors: Bin Hui Wang, Lin Cai, Ming Liu
• Keywords: Boxplot, Multidimensional Scaling, Traffic Jam Prediction

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