Public vehicles and personal navigation assistants have become increasingly equipped with single-frequency global positioning system (GPS) receivers or loggers. These commonly used terminals offer an inexpensive way for acquiring large volumes of GPS traces, which contain information pertaining to road position and traffic rules. Using this new type of spatial data resource, we propose a novel approach for generating high-quality routable road maps. In this approach, a simplified road network graph model uses circular boundaries to separate all GPS traces into road intersections and road segments and builds road networks that maintain their identical geometric topologies through the entry/exit points at the original boundaries. One difficulty inherent to this type of approach is how to best determine the appropriate spatial coverage for road intersections. Conflict points among GPS traces that have large intersection angles usually occur within the physical areas of road intersections, particularly those involving left turns. Therefore, we determined a proper circle boundary for individual road intersections by conducting a spatial analysis of such feature points. This approach was implemented using Python and PostgreSQL/PostGIS and was tested in Huaibei City, China. Based on a comparison with human-interpreted results, the automatically generated routable road map was demonstrated to be of high quality and displayed detailed road networks with turning at various at-grade intersections, interchanges and U-turns.