Map Matching Algorithms for Intelligent Transport Systems

Map Matching Algorithms for Intelligent Transport Systems

Mohammed A. Quddus (Loughborough University, UK)
DOI: 10.4018/978-1-4666-2038-4.ch040
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Abstract

Map matching algorithms integrate positioning data with spatial road network data to support the navigation modules of intelligent transport systems requiring location and navigation data. Research on the development of map matching algorithms has significantly advanced over the last few years. This article looks at different methods that have been adopted in map matching algorithms and highlights future trends in map matching and navigation research.
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Methodologies Used In Map Matching Algorithms

The general purpose of a map matching algorithm is to identify the correct road segment on which the vehicle is travelling and to determine the vehicle location on that segment. The parameters used to select a precise road segment are mainly based on the proximity between the position fix and the road, the degree of correlation between the vehicle trajectory derived from the position fixes and the road centreline, and the topology of the road network. Orthogonal projection of the position fix onto the selected road segment is normally used to calculate the vehicle location on the segment. Figure 1 shows a general map matching process (see Quddus, 2006 for details) which takes inputs from an integrated GPS/DR such as easting (E), northing (N), speed (v), and heading (θ) and the error variances associated with them. The map matching process also takes inputs from a spatial digital road network database. The outputs of the algorithm are the correct link on which the vehicle is travelling and the location of the vehicle () and the error variances associated with them.

Figure 1.

A map matching algorithm

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