Author Affiliations
1Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan, Hubei 430070, China2Hubei Collaborative Innovation Center for Automotive Components Technology, Wuhan University of Technology, Wuhan, Hubei 430070, China3Hubei Research Center for New Energy & Intelligent Connected Vehicle, Wuhan University of Technology, Wuhan, Hubei 430070, China;show less
Fig. 1. Flow chart of objection position detection algorithm
Fig. 2. Sector bins distribution and polar coordinate system
Fig. 3. Pseudo-code block diagram of ground segmentation algorithm
Fig. 4. Schematic diagram of point cloud projected by LiDAR
Fig. 5. Comparison of point clouds from different perspectives. (a) 3D view; (b) XOY plane view
Fig. 6. Object direction angle detection
Fig. 7. Coordinate system rotation process
Fig. 8. Pseudo code block diagram of direction and size detection algorithm
Fig. 9. Installation drawing of vehicle sensor
Fig. 10. Detection performance of the algorithm. (a) Velodyne VLP16; (b) LEISHEN C32151L; (c) ZVISION ML-30S
Fig. 11. Detection time of different LiDARs. (a) Velodyne VLP16; (b) LEISHEN C32151L; (c) ZVISION ML-30S
Performance parameters | Velodyne VLP16 | LEISHEN C32151L | ZVISION ML-30S |
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Number of lines | 16 | 32 | 140 | Measuring range /m | 100 | 150 | 30 | Measuring accuracy /cm | ±3 | ±2 | ±3 | Vertical angle range /(°) | 30 | 30 | 70 | Vertical angular resolution /(°) | 2 | 1 | 1 | Horizontal angle range /(°) | 360 | 360 | 150 | Horizontal angular resolution /(°) | 0.2 | 0.5 | 0.3 | Scanning frequency /Hz | 10 | 10 | 10 |
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Table 1. Performance parameters of LiDAR
LiDAR | Algorithm | TPA | FNA | TTPA | PPA |
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Velodyne VLP16 | MBR | 81.24 | 5.38 | 69.56 | 84.44 | TPE | 81.24 | 5.38 | 68.76 | 83.13 | RDME | 81.24 | 5.38 | 70.03 | 85.56 | LEISHEN C32151L | MBR | 81.80 | 6.84 | 70.83 | 86.93 | TPE | 81.80 | 6.84 | 71.34 | 87.28 | RDME | 81.80 | 6.84 | 74.23 | 90.91 | ZVISION ML-30S | MBR | 80.37 | 5.56 | 69.16 | 86.05 | TPE | 80.37 | 5.56 | 70.17 | 87.62 | RDME | 80.37 | 5.56 | 73.68 | 94.19 |
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Table 2. Algorithm effect evaluation table unit: %