A low-frequency GPS track road network matching method based on multi-dimensional data fusion analysis comprises the steps that firstly, a candidate point set of each GPS track point is calculated, the matching degree of adjacent candidate points is considered from multiple dimensions such as space, time and environment, multi-dimensional data fusion analysis is conducted, and the final matching degree is formed; then, a global static voting matrix is constructed and compressed, low-correlation-degree abnormal track points are removed, meanwhile, factors such as signal timing are comprehensively considered, and a dynamically-optimized local weighted voting matrix is generated; and finally, path generation and candidate point voting are carried out, the candidate path with the highest voting value is selected as a final matching path, and road network matching of the GPS track is completed. The method is suitable for an urban road network, considers the space-time relationship and environmental influence of adjacent track points, carries out multi-dimensional data fusion analysis, eliminates low-correlation abnormal points, and improves the accuracy of road network matching. Meanwhile, dynamic factors such as signal timing and the like are considered, and the road network matching precision is further improved.