Virtual Reality Simulation and Perception of Traffic Congestion Scenes

Urban traffic congestion causes huge economic losses and many social problems, such as, environmental pollution, energy consumption and longer commuting time. Accurate simulation and perception of traffic congestion scenes can help to analyze and solve the problems of traffic congestion. This paper presents a data-driven traffic congestion simulation method, which, by fitting the function relationship between traffic performance index (TPI) and the flow value of simulation input, simulates stable traffic scenes of the specified TPI. Three different virtual reality ways are applied to perceive the results of the simulation. The digital sand table is used to achieve the ”God's perspective” perception of overall congestion scenes; the virtual driving system realizes drivers' ”first-perspective” perception of traffic congestion scenes; a Myo-based virtual flight system is presented to roam and perceive congestion scenes from a ”free perspective”. The simulation and perception of traffic congestion scenes, serving as tool support, make contributions to the popularization education of traffic congestion, design evaluation of signal timing and driving behavior analysis. Experiments on various traffic scenes are conducted to verify the validity of the proposed method.