The LRMS Linear Referencing Profile — Technical Evaluation

Abstract

Executive Summary he Linear Referencing Profile (LRP) is part of the Location Referencing Message Specification (LRMS), a partial solution to interoperability problems in location expression and exchange (LX) in Intelligent Transportation Systems (ITS). This report is an evaluation of the LRP, carried out by the This document assumes that the reader is familiar with the background to interoperability problems in ITS, and the LRMS effort. The following points clarify the scope of this research: • Linear Referencing is most popular in GIST (Geographic Information Systems for Transportation), however, we treat the LRP as a generic ITS location messaging profile, not constraining our test approach to GIST scenarios. • We do not assume that the original expression of position is accurate; we examine the error in the process by which a linear reference is derived from 2-dimensional coordinates, and the error in measuring a linear offset using a Distance Measuring Instrument (DMI). • The LRP relies on indices for road sections and intersection nodes, that are common between users. If users communicate with respect to the same database, there is no interoperability problem; if the databases are different, then the task of assigning common identifiers is expensive, and some errors are inevitably introduced in this step. However our testing assumes away this problem, and we do not attempt to model or to estimate such error. We expend considerable manual effort to develop an accurate table of correspondences for a small sample of data, and we caution that in practical implementation, creating this table with requisite accuracy, and overcoming the inherent semantic conflicts (single vs dual line freeways, traffic circles, etc) will be a potential problem. Testing is built around three sets of experiments. The first involves field surveys using differential Global Positional Systems (GPS) and a Distance Measuring Instrument (DMI). In the preliminaries, we observe various characteristics of DMI readings under normal traffic conditions, and in remote test areas, to estimate the accuracy of the instrument and to quantify its limitations. Then a small sample of roads is selected; we drive those roads, and compare our readings to length calculations and coordinates from digital maps. One of those maps is an engineering scale product; measurements off the map are almost identical to our observations, both in terms of road lengths (±12m) and coordinates (±2m). Other maps disagree by 60–130m in length, and some coordinates are substantially in error (±200m). These numbers …

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