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http://dx.doi.org/10.12815/kits.2012.11.5.125

Development of Vehicle and/or Obstacle Detection System using Heterogenous Sensors  

Jang, Jeong-Ah (한국전자통신연구원 자동차/조선 IT융합연구부)
Lee, Giroung (아주대학교 일반대학원 전자공학과)
Kwak, Dong-Yong (한국전자통신연구원 자동차/조선 IT융합연구부)
Publication Information
The Journal of The Korea Institute of Intelligent Transport Systems / v.11, no.5, 2012 , pp. 125-135 More about this Journal
Abstract
This paper proposes the new object detection system with two laser-scanners and a camera for classifying the objects and predicting the location of objects on road street. This detection system could be applied the new C-ITS service such as ADAS(Advanced Driver Assist System) or (semi-)automatic vehicle guidance services using object's types and precise position. This study describes the some examples in other countries and feasibility of object detection system based on a camera and two laser-scanners. This study has developed the heterogenous sensor's fusion method and shows the results of implementation at road environments. As a results, object detection system at roadside infrastructure is a useful method that aims at reliable classification and positioning of road objects, such as a vehicle, a pedestrian, and obstacles in a street. The algorithm of this paper is performed at ideal condition, so it need to implement at various condition such as light brightness and weather condition. This paper should help better object detection and development of new methods at improved C-ITS environment.
Keywords
laser-scanner; camera; object classification; object detection; C-ITS;
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  • Reference
1 H. Zhao, J. Cui and H. Zha, "Sensing an intersection using a network of laser scanners and video cameras", IEEE Intelligent Transportation Systems Magazine, vol. 1, no. 2, pp.31-37, 2009.
2 L. Alexander, P. Cheng, A. Gorjestani, A. Menon, B. Newstom, C. Shankwitz, and M. Donath, "The minnesota mobile intersection surveillance system", Proc. of IEEE Intelligent Transportation Systems Conference, pp.139-144, 2006.
3 L. A. Klein, "Sensor Technologies and Data Requirements for ITS", Artech House, 2001.
4 J. Cui, H. Zha, H. Zhao, and R. Shibasaki, "Multi-modal tracking of people using laser scanners and video camera", Image and vision computing, vol. 26, pp.240-252, 2008.   DOI   ScienceOn
5 장정아, 곽동용, 임동선, "자동차-IT서비스를 위한 인프라기반 이종센서의 융합기술연구", 2011년도 한국융합소프트웨어학회 추계학술발표대회 논문집, 제1권 1호, 2011.
6 E. Waltz and J. Llinas, "Multisensor data fusion norwood", MA: Artech House, 1990.
7 N. E. Faouzi, H. Leung, and A. Kurian, "Data fusion in intelligent transportation systems: progress and challenges- a survey", Information Fusion, vol. 12, pp.4-10, 2011.   DOI   ScienceOn
8 F. Ahlers, and Ch. Stimming, "Laserscanner based cooperative Pre-data-fusion", in Proc. IEEE in Intelligent Vehicles Symposium, pp.1187-1190, 2008.
9 M. Tsogas, N. Floudas, P. Lytrivis, A. Amditis, and A. Polychronopoulos, "Combined lane and road attributes extraction by fusion data from digital map, laser scanner and camera", Information Fusion, vol. 12, pp.28-36, 2011.   DOI   ScienceOn
10 M. Jokela, M. Kutila, J. Laitnen, F. Ahlers, N. Hautiere, and T. Schendzielorz, "Optical road monitoring of the future smart roads - preliminary results", World Academy of Science, Engineering and Technology, vol. 34, pp.52-57, 2007.
11 R. Labayrade, C. Royere, D. Gruyer, and D. Aubert, "Cooperative fusion for multi-obstacles detection with use of stereovision and laser scanner", Autonomous Robots, vol. 19, pp.11-140, 2005.
12 N. Kaempchen and K. C. J. Dietmayer, "Fusion of laserscanner and video for advanced driver assistance systems", in Proc.11th World Congress on Intelligent Transportation Systems, Nagoya, Japan, 2004.
13 S. Wender and K. C. J. Dietmayer, "A feature level fusion approach for object classification", in Proc. IEEE Intelligent Vehicles Symposium, Istanbul, Turkey, 2007.
14 A. Soloviev, and M. M. Miller, "Navigation in difficult environments: Multi-sensor fusion techniques", RTO-EN-SET-116, Nato Otan Science and Technology Organization publication, 2011.
15 C. h. Cuan, J. W. Gong, Y. D. Chen, and H. Y. Chen, "An application of data fusion combining laser scanner and vision in real-time driving environment recognition system", in Proc. 8th International Conference on Machine Learning and Cybernetics, Baoding, 12-15 July 2009.
16 H. Cramer, U. Scheunert, and G. Wanielik, "Multi sensor data fusion using a generalized feature model applied to different types of extended road objects," in Proc. 7th International Conference on Information Fusion. Stockholm, Schweden, June 2004.
17 A. Fod, A. Howard, and M.J. Mataric, "Laser-based people tracking", in Proc. IEEE Robotics, pp.3025-3029, 2003. J. Blanco, W. Burgard, R. Sanz, and J.L. Fernandez, "Fast face detection for mobile robots by integrating laser range data with vision", in Proc .IEEE Robotics, 2003.