A neural network approach to target classification for active safety system using microwave radar

Expert Systems with Applications

Volumn 37, Issue 3, 2010, Pages 2340-2346

  Park, Seongkeun ^a   Pil Hwang, Jae ^a   Kim, Euntai ^a   Lee, Heejin ^b   Gi Jung, Ho ^c  

^a Yonsei University   (South Korea)

^b Hankyong National University   (South Korea)

^c MANDO Corporation   (South Korea)

Author keywords

Active safety system; Belief update; Multilayer perceptron neural network; Probabilistic classification; Target classification

Indexed keywords

ACTIVE SAFETY SYSTEM; BELIEF UPDATE; MULTILAYER PERCEPTRON NEURAL NETWORK; PROBABILISTIC CLASSIFICATION; TARGET CLASSIFICATION;

ELECTRIC LOADS; MICROWAVES; MULTILAYERS; NEURAL NETWORKS; RADAR; SECURITY SYSTEMS; SENSORS; STRUCTURES (BUILT OBJECTS);

TARGETS;

EID: 70449521179     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2009.07.070     Document Type: Article

References (18)

1. Bifulco, G. N., Simonelli, F., & Di Pace, R. (2008). Experiments toward an human-like Adaptive Cruise Control. In Intelligent vehicles symposium (pp. 919-924).
2. Chan C.Y. Trends in crash detection and occupant restraint technology. IEEE Proceedings 95 2 (2007) 388-396
3. Duda R., Hart P., and Stork D. Pattern classification (2001), Addison Wesley
4. Fuerstenberg, K. & Dietmayer, K. (2004). Object tracking and classification for multiple active safety and comfort applications using a multilayer laser scanner. In IEEE intelligence vehicle symposium (pp. 802-807). Parma, Italy.
5. Fuerstenberg, K., & Willhoeft, V. (2001). Object tracking and classification using laserscanners - Pedestrian recognition in urban environment. In Intelligence transportation systems conference (pp. 451-453). Oakland, USA.
6. Gandhi T., and Trivedi M.M. Pedestrian protection systems: Issues, survey, and challenges. IEEE Tranactions on Intelligence Transportation Systems 8 3 (2007) 413-430
7. Hagan M.T., Demuth H.B., and Beale H. Neural network design (1995), PWS Publishing Company, USA
8. Ioannou P.A., and Stefanovic M. Evaluation of ACC vehicles in mixed traffic: Lane change effects and sensitivity analysis. IEEE Transactions on Intelligence Transportation Systems 6 1 (2005) 79-89
9. Knott E.F., Shaeffer J.F., and Tuley M.T. Radar cross section (1993), Artech House, Boston
10. Krips, M., Velten, J., Kummert, A., & Teuner, A. (2004). AdTM tracking for blind spot collision avoidance. In Intelligent vehicles symposium, 2004 IEEE 14-17 (pp. 544-548).
11. Maclachlan, R., & Mertz, C. (2006). Tracking of moving objects from a moving vehicle using a scanning laser rangefinder. In Intelligence transportation systems conference (pp. 301-306), Toronto, Canada.
12. Manual of MA-COM MASRAU0025., 2005.
13. Nguwi, Y.-Y., & Kouzani, A. Z. (2006). A study on automatic recognition of road signs. In 2006 IEEE conference on cybernetics and intelligent systems (pp. 1-6).
14. Thrun S., Bugard W., and Fox D. Probabilistic robotics (2005), MIT Press, Cambridge, MA
15. US Patent 6859148. (2005). Blind spot warning system for an automotive vehicle. US Patent Issued on February 22, 2005.
16. Wang, W., Zhang, W., & Bubb, H. (2007). Car-following safety algorithms based on adaptive cruise control strategies. In Intelligent systems and informatics, 2007. SISY 2007. Fifth international symposium (pp.135-140).
17. Watanabe, K., Umezawa, Y., & Abe, K. (1994). Advanced passive safety system via prediction and sensor fusion. In Vehicle navigation and information systems conference (pp. 435-440).
18. Yoon C., Lee H., Kim E., and Park M. Real-time road sign detection using fuzzy-boosting. IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences E91-A 11 (2008) 3346-3355