Abstract

Traffic simulation has become an efficient tool, with the assistance of computer visualizing techniques, to solve traffic issues such as traffic congestion, network design, and similar problems. Properly controlling simulated traffic flow and modeling each vehicle’s irregular behaviors are key issues in the traffic simulation field. In this paper, we introduce real vehicle trajectories as a data-driven factor in simulated traffic situations to drive behaviors of other simulated vehicles. First, we train a driving model for each simulated vehicle using real traffic data that have a unique control strategy. Then, we fuse real trajectories driven vehicles with simulated trajectories driven vehicles to interact, guided by our learned traffic model, to accurately depict the reality of traffic flows. Compared with existing methods, traffic flows simulated using this method are more realistic and can preserve irregular characteristics of the real traffic flows.

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