Road situation modeling and parallel algorithm implementation with FCD based on principle curves

This paper is to model the road situation with Floating Car Data (FCD) based on principle curves. The relationship of the time and the passing velocity through a road segment is presented by the Principle Curves (PCs) which can reflect urban traffic situation. And the rules of road situation are built by PCs. Moreover, a parallel algorithm is proposed to build the models because of massive GPS data and the large road net. The task scheduling policy of the algorithm can assign tasks of different size to processors with different speed such that all subtasks complete at the same time in theory. The experimental results indicate that the increasing multiple of the speedup is about equal to the increasing multiple of the processors, and that the efficiency of each processor is about 93% in the heterogeneous computing platform with the algorithm