Safe Distance Detection Method of Unmanned Vehicle Based on Virtual Reality

Authors

  • Lingfang Wu College of Automobile and Transportation Engineering, Guilin University of Aerospace Technology, Guilin 541004, China

Abstract

Unmanned vehicles can enter and leave dangerous airspace for a long time and play a vitalrole in critical missions. They carry special equipment to accomplish specific tasks with high cost. They have great application prospects and strategic value, so it is essential to study their operational safety. This paper proposes a safe distance detection method based on virtual reality technology for driverless cars, and simulates the special effects of 3D graphics of driverless cars, 3D graphics of terrain and geomorphology, sound, and smoke from explosion by using virtual reality technology. Threshold segmentation and refinement methods are used to reduce the computation of obstacle recognition in the constructed virtual reality scene, and the
decision tree recognition method is used to identify obstacles.The location of obstacles is determined, and then the three-dimensional Euler space image is transformed into a two-dimensional Euler space image by constructing the ranging model. The detection of the safe distance of unmanned vehicles is achievedby using the monocular camera ranging model.The experimental results show that the detection method can clearly and effectively simulate a road environment and an explosion site environment, and can accurately and efficiently detect the safe distance of the unmanned vehicle in the conventional environment and in a complex electromagnetic environment, so as to enhance the safety of the unmanned vehicle.

Keywords: Virtual reality, Unmanned vehicle, Operation, Safetydistance, Detection, Obstacles

Cite As

L. Wu, "Safe Distance Detection Method of Unmanned Vehicle Based on Virtual Reality", Engineering
Intelligent Systems, vol. 29 no. 4, pp. 205-215, 2021.






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Published

2021-07-01

Issue

Vol. 29 No. 4 (2021): International Journal of Engineering Intelligent Systems

Section

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