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.


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    Title :

    Multidimensional Scaling and Application in Traffic Jam Prediction



    Published in:

    Applied Mechanics and Materials ; 291-294 ; 3060-3063


    Publication date :

    2013-02-13


    Size :

    4 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English







    A Visual Workspace for Hybrid Multidimensional Scaling Algorithms

    Ross, G. / Chalmers, M. / Institute of Electrical and Electronics Engineers | British Library Conference Proceedings | 2003