A heuristic path-estimating algorithm by using vector-based recognition

Floating Car Data (FCD) is an important material for a broad range of application such as traffic management and control, traffic conditions computation and so on. However, in the original data exists error, and the data must be handled by path-estimating and be related to the road. The traditional path-estimating algorithms mainly use two methods: the incremental method and the global method. Both of them have advantages and disadvantages of themselves: while the global map-matching algorithm produces better matching results, the incremental algorithm produces results of lower quality faster. All things considering the two traditional algorithms, this paper proposes a heuristic path-estimating algorithm by using vector-based recognition. Firstly, the algorithm uses the heuristic search method, and it makes use of geometric operation to form the restriction, and make the comparison between the vector formed with the vehicular GPS points and the special road network model to search and select the vehicular possible traveling routes. Secondly, it globally compares all the vehicular possible traveling routes, and then chooses the optimal one. The result of testing demonstrates the efficiency of the algorithm both at accuracy and computational speed when handling the large-scale data of GPS tracking data even under the complex road network conditions.