Detecting spatial and temporal route information of GPS traces

This paper aims at detecting route information of GPS traces to represent spatial and temporal information of trips. A Bayesian belief network model is used to calculate the probability of a road matching a GPS log point. The algorithm incorporates road network topology, distance from trace nodes to road segments, the angle between two lines, direction difference, accuracy of measured GPS log point, and position of roads. GPS data collected in the Eindhoven region, The Netherlands, is used to examine the performance of this algorithm. Results based on a small sample show that the algorithm has a good performance in both processing efficiency and prediction accuracy of correctly identified instances. Prediction accuracy using a small sample is 87.02 %.