Horizontal curvature estimation of tram tracks using OpenStreetMap

Abstract

For analysing, understanding and predicting the track/train-dynamics in order to develop comfortable and sustainable vehicles a sufficient description of the track course and conditions are key requirements. Not only the track irregularities but also the horizontal curvature affects the vehicle dynamics strongly. Nearly all cities owning light rail systems have gradually established the light rail traffic. By reasons of building density, road transportation infrastructure, and progress of the overall urban planning, the light rail infrastructure was constrained to the pre-existing environment. Thus, the track course is mainly optimized for efficient space use but not for best possible vehicle dynamics. To be able to analyse the track layout of tram networks at a bigger scale, an appropriate methodology that allows acquiring track course data is needed, which is the main objective of this paper. For this purpose, an open data approach was developed by the authors utilizing OpenStreetMap (OSM) to derive the horizontal track curvature based on geodata. This groundbreaking approach improves the state of the art since professional geodetic measurements of light rail tracks are generally rarely publicly available, cost-intensive and their preprocessing can potentially be time consuming. The outcome is a simple, robust, and fast approach that was validated using already existing reference track data which was available to the authors. Additionally, an error estimation of the methodology was carried out. Using a quadratic error function, the median standard deviation of the curvature can be determined and used to rate the exactness of the estimated curvature depending on its magnitude. In this approach, the curvature estimations exactness is generally high for small curve radii and decreases for bigger radii. Therefore it can be concluded that the field of application is especially promising for light rail infrastructure. But also for mainline tracks the new method can be used as a rough estimate, if no curvature data is at hand.