The classic transport model consists of four sub-models: trip generation, trip distribution, modal split and traffic assignment. The current article in particular focuses on trip distribution. In this paper a statistical approach is introduced to deal with spatial autocorrelation among errors in a regression model based on commuter data. A gravity model is applied to estimate traffic flows by using regression techniques. Unlike time-series in cross-section analysis the measures of autocorrelation must take into consideration different contiguities among units. In a first step - illustrated by a simple cross-sectional example - a theoretical framework is developed, allowing the estimation of spatial weight matrices adapted from a Moran coefficient as a measure of spatial correlation. These weight matrices establish a basis for estimating a spatial autocorrelation coefficient and, moreover, reflect the various effects of different neighbourhood matrices. Finally, the same approach is applied by using commuter flow data. Here, contrary to simple cross-sectional analysis the contiguity matrix must take into account vectors. It is shown, that in travel flow data as well as in cross-sectional data spatial autocorrelation can be found. Accounting for this phenomenon by an appropriate spatially autocorrelated structure of the error terms leads to significant improvements of the transport flow model.


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    Title :

    Neuere oekonometrische Methoden in der Verkehrswissenschaft


    Additional title:

    Advanced econometric methods for traffic science


    Contributors:
    Stock, W. (author)

    Published in:

    Publication date :

    2004


    Size :

    25 Seiten



    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    German




    Neuere ökonometrische Methoden in der Verkehrswissenschaft

    Stock, Wilfried | Online Contents | 2004



    Verkehrswissenschaft

    Napp-Zinn, Anton Felix | SLUB | 1968


    Beiträge zur Verkehrswissenschaft

    Technische Universität Berlin, Institut für Verkehrsplanung und Verkehrswegebau | SLUB | 1978