Improved Identification and Calculation of Horizontal Curves with Geographic Information System Road Layers

Abstract

Horizontal curve data are collected or calculated by transportation agencies for different purposes because there is always a demand to generate new curve data either to improve the data quality or to extend the data coverage. There are different approaches and technologies for curve data collection. The selection of methods takes into consideration accuracy, cost, and available sources. There is, consequently, a wide interest in extracting curve information from available road network data of the geographic information system (GIS). When the cost of GIS data extraction is much lower than the cost of other approaches, it is significant to improve the accuracy of GIS curve identification and calculation. This paper analyzes errors related to existing GIS curve calculation methods and introduces a new method to identify and to calculate horizontal curves with improved accuracy. The new method uses regression analysis of road vertex direction–location profiles to calculate curve radii. A freeway segment on Interstate 80 in Nevada, including the eastbound and westbound directions, was selected to evaluate the accuracy of the new method. The evaluation compared the curve calculation results and the accurate curve information from project contract plans. The evaluation results proved the effect of the new procedure on improving the accuracy of horizontal curve identification and estimation. The new method can be implemented as a GIS tool to scan GIS road networks automatically and create horizontal curve data layers. This new method can also be used to generate curve data from GPS survey data.