Browse > Article
http://dx.doi.org/10.5369/JSST.2019.28.3.157

Realization of Object Detection Algorithm and Eight-channel LiDAR sensor for Autonomous Vehicles  

Kim, Ju-Young (Sensor Research Team, Gyeongbuk Institute of IT Convergence Industry Technology)
Woo, Seong Tak (Sensor Research Team, Gyeongbuk Institute of IT Convergence Industry Technology)
Yoo, Jong-Ho (Sensor Research Team, Gyeongbuk Institute of IT Convergence Industry Technology)
Park, Young-Bin (Sensor Research Team, Gyeongbuk Institute of IT Convergence Industry Technology)
Lee, Joong-Hee (Sensor Research Team, Gyeongbuk Institute of IT Convergence Industry Technology)
Cho, Hyun-Chang (IT Convergence Components Research Center)
Choi, Hyun-Yong (IT Convergence Components Research Center)
Publication Information
Journal of Sensor Science and Technology / v.28, no.3, 2019 , pp. 157-163 More about this Journal
Abstract
The LiDAR sensor, which is widely regarded as one of the most important sensors, has recently undergone active commercialization owing to the significant growth in the production of ADAS and autonomous vehicle components. The LiDAR sensor technology involves radiating a laser beam at a particular angle and acquiring a three-dimensional image by measuring the lapsed time of the laser beam that has returned after being reflected. The LiDAR sensor has been incorporated and utilized in various devices such as drones and robots. This study focuses on object detection and recognition by employing sensor fusion. Object detection and recognition can be executed as a single function by incorporating sensors capable of recognition, such as image sensors, optical sensors, and propagation sensors. However, a single sensor has limitations with respect to object detection and recognition, and such limitations can be overcome by employing multiple sensors. In this paper, the performance of an eight-channel scanning LiDAR was evaluated and an object detection algorithm based on it was implemented. Furthermore, object detection characteristics during daytime and nighttime in a real road environment were verified. Obtained experimental results corroborate that an excellent detection performance of 92.87% can be achieved.
Keywords
LiDAR sensor; Object detection; Advanced driving assistance system; Autonomous vehicle; Euro new car assessment program;
Citations & Related Records
연도 인용수 순위
  • Reference
1 http://leddartech.com/(retrieved on Sep. 15, 2017).
2 http://www.advancedscientificconcepts.com/(retrieved on Mar. 20, 2019).
3 U. Hogmann, F. Senger, F. Soerensen, V. Stenchly, B. Jensen, and J. Janes , "Biaxial resonant 7mm-MEMS mirror for automotive LIDAR application", IEEE 2012 Int. Conf. on Optical MEMS and Nanophotonics, Banff, Canada, 2012.
4 T. Fersch, R. Weigel, and A. Koelpin, "A CDMA Modulation Technique for Automotive Time-of-Flight LiDAR Systems", IEEE Sensors J., Vol. 17, No. 11, pp. 3507-3516, 2017.   DOI
5 R. Thakur, "Scanning LIDAR in Advanced Driver Assistance Systems and Beyond: Building a road map for next-generation LIDAR technology", IEEE Consum. Electron. Mag., Vol. 5, No. 3, pp. 48-54, 2016.   DOI
6 J. Han, D. Kim, M. Lee, and M. Sunwoo, "Enhanced Road Boundary and Obstacle Detection Using a Downward-Looking LIDAR Sensor", IEEE Trans. Veh. Technol., Vol. 61, No. 3, pp. 971-985, 2012.   DOI
7 J. Choi, V. Va, N. Gonzalez-Prelcic, R. Daniels, C. R. Bhat, and R. W. Heath, "Millimeter-Wave Vehicular Communication to Support Massive Automotive Sensing", IEEE Commun. Mag., Vol. 54, No. 12, pp. 160-167, 2016.   DOI
8 J. Sun, E. Timurdogan, A. Yaacobi, E. S. Hosseini, and M. R. Watts, "Large-scale nanophotonic phased array", Nature, Vol. 493, No. 7431, pp. 195-199, 2013.   DOI
9 https://www.continental-corporation.com/(retrieved on Jun. 5, 2018).
10 http://www.hamamatsu.com/(retrieved on Mar. 12, 2019).
11 J. Sun, E. Timurdogan, A. Yaacobi, Z. Su, E. S. Hosseini, D. B. Cole, and M. R. Watts, "Large-scale silicon photonic circuits for optical phased arrays", IEEE J. Sel. Top. Quantum Electron., Vol. 20, No. 4, pp. 1-15, 2014.
12 C. V. Poulton, M. J. Byrd, M. Raval, Z. Su, N. Li, E. Timurdogan, D. Coolbaugh, D. Vermeulen, and M. R. Watts, "Large-scale silicon nitiride nanophotonic phased arrays at infrared and visible wavelengths", Opt. Lett., Vol. 42, No. 1, pp. 21-24, 2017.   DOI
13 http://www.osram.com/ (retrieved on Mar. 9, 2018).
14 X. Zhang, S. J. Koppal, R. Zhang, L. Zhou, E. Butler, and H. Xie "Wide-angle structured light with a scanning MEMS mirror in liguid", Opt. Express, Vol. 24, No. 4, pp. 3479-3487, 2016.   DOI
15 K. E. Petersen, "Silicon torsional scanning mirror", IBM J. Res. Dev., Vol. 24, No. 5, pp. 631-637, 1980.   DOI
16 A. Kasturi, V. Milanovic, B. H. Atwood, and J. Yang, "UAV-Borne LiDAR with MEMS Mirror-Based Scanning Capability", Proc. of SPIE, Vol. 9832, pp. 98320M(1)-98320M(10), 2016.
17 X. Lee and C. Wang, "Optical design for uniform scanning in MEMS-based 3D imaging lidar," Appl. Opt., Vol. 54, No. 9, pp. 2219-2223, 2015.   DOI
18 L. Ye, G. Zhang, and Z. You, "Large-aperture kHz operating frequency Ti-alloy based optical micro scanning mirror for LiDAR application", Micromachines, Vol. 8, No. 4, pp. 120-133, 2017.   DOI
19 S. T. Woo, Y. B. Park, J. H. Lee, C. S. Han, S. D. Na, and J. Y. Kim, "Angle Sensor Module for Vehicle Steering Device Based on Multi-Track Impulse Ring", Sensors, Vol. 19, No. 526, pp. 1-13, 2019.   DOI
20 L. Ye, G. Zhang, and Z. You, "5 V compatible two-axis PZT driven MEMS scanning mirror with mechanical leverage structure for miniature LiDAR Application", Sensors, Vol. 17, No. 3, pp. 521-534, 2017.   DOI
21 D. N. Hutchison, J. Sun, J. K. Doylend., R. Kumar, J. Heck, W. Kim, C. T. Phare, A. Feshali, and H. Rong, "High-resolution aliasing-free optical beam steering", Optica, Vol. 3, No. 8, pp. 887-890, 2016.   DOI