Localized speed prediction with the use of spatial simultaneous autoregressive models
Axhausen, Kay W.
- Conference Paper
Rights / licenseIn Copyright - Non-Commercial Use Permitted
This paper examines how to employ spatial regression modelling as a direct demand modelling approach to provide localized speed estimates in a large scale network. In particular, four different spatial simultaneous autoregressive (SAR) models are estimated and compared to an ordinary linear regression in order to highlight and evaluate their capability of explaining transport related phenomena and resolving issues that arise from the underlying spatial dependence. A particular focus is given on the identification, the construction, and the selection of the spatial weighting matrices. We conclude that the spatial autocorrelation (SAC) model outperforms the other SAR models, resolving spatial dependence issues, and thus is the proposed one for speed prediction purposes. Show more
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Book titleTRB 94th Annual Meeting Compendium of Papers
PublisherNational Academy of Sciences
Organisational unit03521 - Axhausen, Kay W. / Axhausen, Kay W.
02226 - NSL - Netzwerk Stadt und Landschaft / NSL - Network City and Landscape
02655 - Netzwerk Stadt und Landschaft D-ARCH
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