Traffic Object Detection in Virtual Environments
Bo-Yi Lin, Chih-Sheng Huang, Jia‐Ming Lin, Pin-Hsuan Liu, Kuan-Ting Lai · 2023
As Virtual Reality (VR) technology becomes more advanced, VR can create scenes that closely resemble the real world. Therefore, automotive industry has started to use VR environments as test bed for autonomous driving algorithms. However, to the best of our knowledge, there is no systematic evaluation for the performance of real-world object detectors in VR worlds. To solve this issue, we used Unreal Engine to construct a virtual environment simulating real street view and AirSim plugin to generate bounding box ground truths. We employed the state-of-the-art object detectors YOLOv7 and YOLOv8 to detect common traffic objects. Our experiments can reveal the strengths and weakness of each detector.