A new method for GPS-based urban Vehicle Tracking using pareto frontier and fuzzy comprehensive judgment

Vehicle Tracking is an effective approach to urban traffic flow estimation. Based on the data of GIS and GPS, a Vehicle Tracking process continually judges, from a road network, the most reliable path between every two successively detected locations of a certain vehicle, and then links the paths to restore the real track. Conventional works focused mostly on the driving distance and selected the shortest path as the solution. However, as is in many situations, the shortest path is not necessarily the best choice. Instead, a path with the least time expense may be more reasonable. Therefore, a new hybrid real-time Vehicle Tracking method is proposed in this paper considering comprehensively two main time-costing factors, the total driving distance and the number of traversed crossroads, using the concept of Pareto Frontier and Fuzzy Theory. Analytical experiment in Shanghai yields promising results.