Simple Map-Matching Algorithm Applied to Intelligent Winter Maintenance Vehicle Data

Abstract

Intelligent winter maintenance vehicles are equipped with automatic vehicle location (AVL) technology, including differential Global Positioning System (DGPS) receivers and various additional sensors that collect equipment status and material use data. DGPS data points are associated with the nearest roadway centerline by calculating minimum perpendicular distances between each roadway centerline representation and the DGPS data points. Highly accurate roadway centerline maps and DGPS measurements are not always available. Thus, spatial mismatches may occur at converging and diverging roadways, divided highways, and intersections. Decision makers use winter maintenance performance measures to evaluate achievement of goals and objectives and to improve winter maintenance operations in public agencies. These performance measures are sensitive to spatial mismatches, which need to be resolved before calculations are done. This paper presents a simple map-matching algorithm that resolves spatial ambiguities by determining the correct roadway centerline on which the vehicle is traveling. The algorithm computes shortest paths between snapped DGPS data points using network topology and turn restrictions. A path is considered viable, and locations for the snapped DGPS data points correct, if similarity exists between values of calculated and recorded vehicle speeds. If a path is not feasible, DGPS points are snapped to alternative roadway centerlines contained within their buffers, shortest paths are recalculated, and speeds are again compared. Examples are presented to illustrate the implementation and effectiveness of the algorithm.