Abstract
According to the real-time laser radar is strong, wide detection depth, the advantages of little influence of the environment, put forward complex environment real-time vehicle detection method based on laser radar. Proposed method the HDL-64E-64 laser radar scanning complex traffic environment, perception by a laser radar system to get the lidar data, using 3D laser point cloud projection transform the lidar data to the body coordinate system, and establish the data grid structure. By gradient method for cutting the lattice structure of the lidar data, index figure obstacles markers in the cutting block. Box reduction method is used to detect the obstacles the shape, volume, speed, and coordinates, using cascade classifier detection accuracy control in the more than 0.9 mm. At last, by experimental verification, the proposed method has the advantages of low complexity and high efficiency.
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Acknowledgements
This work was supported by two funds: 1. City College of Wuhan University of Science and Technology, Teaching and Research Project: Research and Practice of Computer Network Course Group Practice Teaching System Reform Based on Cloud Computing (Project No: 2018CYZDJY007). 2. Innovation Entrepreneurship Project: Promote student employment plans with reform and practice teaching systems and innovation in science and technology competitions (Project No: 13).
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Li, B., Fang, L. (2020). Laser Radar Application in Vehicle Detection Under Traffic Environment. In: Jain, V., Patnaik, S., Popențiu Vlădicescu, F., Sethi, I. (eds) Recent Trends in Intelligent Computing, Communication and Devices. Advances in Intelligent Systems and Computing, vol 1006. Springer, Singapore. https://doi.org/10.1007/978-981-13-9406-5_126
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DOI: https://doi.org/10.1007/978-981-13-9406-5_126
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