Nearest Neighbour Route Classification in Travel Time Estimation Based onCellular Network Signalling.

Author(s)
Gundlegard, D. & Karlsson, J.M.
Year
Abstract

Travel time estimation based on cellular network signaling is a promisingtechnology for delivery of wide area travel times in real-time. The technology has received much attention recently, but few academic research reports has so far been published in the area, which makes it difficult to assess the potential of the technology. This paper aims to investigate the route classification task in a cellular travel time estimation context in detail. In order to estimate the magnitude of the problem a nearest neighborclassification algorithm is developed and evaluated using field measurements from the GSM network. A conclusion from the results is that the route classification problem is not trivial even in a highway environment, due to effects of multipath propagation and changing environment. In a highway environment the classification problem can be solved rather efficiently using e.g. a nearest neighbor classification method, keeping the effect on travel time accuracy low. However, in order to solve the route classification task in urban environments more research is required.

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Publication

Library number
C 46969 (In: C 46669 CD-ROM) /72 / ITRD E852490
Source

In: ITS in daily life : proceedings of the 16th World Congress on Intelligent Transport Systems (ITS), Stockholm, Sweden, September 21-25, 2009, 10 p.

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This publication is one of our other publications, and part of our extensive collection of road safety literature, that also includes the SWOV publications.