Intelligent immersive high-speed train virtual driving behavior evaluation method and simulation system

Abstract

The invention provides an intelligent immersive high-speed train virtual driving behavior evaluation method and a simulation system. According to the method, a virtual driving scene module is established, and various driving training scenes composed of multiple intelligent agents are constructed; a high-speed train dynamics module is established, including various subsystems of the high-speed train such as engine, power train system, steering mechanism and body modules; a virtual driving scene simulation module is established; a high-speed train logic simulation module is established; a data helmet display and man-machine interaction module is established, the head tracking technology of a helmet type display is researched on the basis of the virtual reality technology, and motion of the high-speed train in a virtual environment is controlled and manipulated through a high-speed operation mechanism; finally, intelligent driving behavior researching and evaluation are realized on the basis of a time varying dynamic bayesian networks (TVDBN) dynamic learning learning model according to the virtual driving operation data accumulated in a user and simulation system interaction process.

Description

technical field [0001] The present invention relates to virtual reality technology, mechanical transmission technology, computer graphics, three-dimensional real-time rendering technology, computer interface technology, data communication technology, etc., and particularly relates to an immersive virtual driving behavior intelligent evaluation method and simulation system. Background technique [0002] The high-speed rail driving simulator constructs a driver-virtual scene interactive driving environment through manipulation simulation, dynamics simulation, visual simulation and other systems. In the virtual scene simulation, in order to truly simulate the road traffic environment, it is necessary to add moving objects such as vehicles to the scene. These moving objects simulate the corresponding behavior in the real world, and can perceive the environment in real time, and plan, make decisions and operate by themselves. Such autonomous, reactive, and capable objects that ca...

AI Technical Summary

Problems solved by technology

However, when the application environment changes over time and the agent system exhibits non-stationary characteristics, the decision control model constructed by the above modeling method is prone to distortion

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