Open Access
Issue
MATEC Web Conf.
Volume 81, 2016
2016 5th International Conference on Transportation and Traffic Engineering (ICTTE 2016)
Article Number 02001
Number of page(s) 6
Section Transportation Security
DOI https://doi.org/10.1051/matecconf/20168102001
Published online 25 October 2016
  1. S. H. Kim, P. S. Moon, W. S. Jang, K. S. Kim, S. C. Lee, WooM., et al., “An experimental investigation of a CW/CA system for automobiles”, SAE Technical Paper, (1999)
  2. S. Moon, I. Moon, and K. Yi, “Design, tuning, and evaluation of a full-range adaptive cruise control system with collision avoidance,” Control Engineering Practice, 17, pp. 442–455, (2009) [CrossRef]
  3. A. Ferrara and C. Vecchio, “Second order sliding mode control of vehicles with distributed collision avoidance capabilities,” Mechatronics, vol. 19, pp. 471–477, (2009) [CrossRef]
  4. J. van den Berg, D. Wilkie, S. J. Guy, M. Niethammer, and D. Manocha, “LQG-obstacles: Feedback control with collision avoidance for mobile robots with motion and sensing uncertainty,” in Robotics and Automation (ICRA), 2012 IEEE International Conference on, pp. 346–353, (2012) [CrossRef]
  5. Y. J. Mon and C. M. Lin, “Supervisory recurrent fuzzy neural network control for vehicle collision avoidance system design”, Neural Computing and Applications, 21, pp. 2163–2169, (2012) [CrossRef]
  6. N. B. Hui, V. Mahendar, and D. K. Pratihar, “Time-optimal, collision-free navigation of a car-like mobile robot using neuro-fuzzy approaches,” Fuzzy Sets and Systems, 157, pp. 2171–2204, (2006) [CrossRef]
  7. H. S. Hwang, Y. H. Joo, H. K. Kim, and K. B. Woo, “Identification of fuzzy control rules utilizing genetic algorithms and its application to mobile robots,” Algorithms and Architectures for Real-Time Control (Korea, 1992), pp. 249–254, (2014)
  8. A. Jalali, F. Piltan, A. Gavahian, and M. Jalali, “Model-free adaptive fuzzy sliding mode controller optimized by particle swarm for robot manipulator,“ International Journal of Information Engineering and Electronic Business (IJIEEB), 5, p. 68, (2013) [CrossRef]
  9. D. K. Pratihar, K. Deb, and A. Ghosh, “A genetic-fuzzy approach for mobile robot navigation among moving obstacles”, International Journal of Approximate Reasoning, 20, pp. 145–172, (1999) [CrossRef]
  10. F. Betin, A. Sivert, A. Yazidi, and G. A. Capolino, “Determination of scaling factors for fuzzy logic control using the sliding-mode approach: Application to control of a DC machine drive,” Industrial Electronics, IEEE Transactions on, 54, pp. 296–309, (2007) [CrossRef]
  11. S. Kang, I. Yoo, M. Shin, and S. Seo, “Accurate inter-vehicle distance measurement based on monocular camera and line laser”, IEICE Electronics Express, 11, pp. 20130932–20130932, (2014) [CrossRef]
  12. L. Cheng, B. E. Henty, D. D. Stancil, F. Bai, and P. Mudalige, “Mobile vehicle-to-vehicle narrow-band channel measurement and characterization of the 5.9 GHz dedicated short range communication (DSRC) frequency band,” Selected Areas in Communications, IEEE Journal on, 25, pp. 1501–1516, (2007) [CrossRef]
  13. M. Rohani, D. Gingras, V. Vigneron, and D. Gruyer, “A new decentralized Bayesian approach for cooperative vehicle localization based on fusion of GPS and inter-vehicle distance measurements,” in Connected Vehicles and Expo (ICCVE), 2013 International Conference on, pp. 473–479, (2013) [CrossRef]
  14. P. Seiler, B. Song, and J. K. Hedrick, “Development of a collision avoidance system”, Development, 4, pp. 17–22, 1998
  15. W. Zhang, O. Tsimhoni, M. Sivak, and M. J. Flannagan, “Road safety in China: analysis of current challenges”, Journal of safety research, 41, pp. 25–30, (2010) [CrossRef]
  16. L. Fan and E. M. Joo, “Design for auto-tuning PID controller based on genetic algorithms,” in Industrial Electronics and Applications, 2009. ICIEA 2009. 4th IEEE Conference on, pp. 1924–1928, (2009) [CrossRef]