Abstract
In artificial society simulation, each artificial population needs road path planning in the process of travel. However, because of the large amounts of populations in artificial society, road path planning will cost lots computational resources and time, thus this process has terrible efficiency to the performance of the simulation system. In order to solve this problem, this article firstly makes use of CPU to generate the artificial populations, travel logs, and construct the road network models; then computes the shortest road path between each two environments and load the results in RAM for prepare; lastly, sends the ID and its start point and destination of the population who need road path querying to GPU at current simulation time in the simulation process, and then takes advantages of GPU to query the road path and return the results back. In this way, we can obviously reduce the time costs in the process of road path querying and enormously improve the performance of the whole simulation system.
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