A Rear-End Collision Avoidance Scheme for Intelligent Transportation System

Chen Chen; Hongyun Liu; Hongyu Xiang; Meilian Li; Qingqi Pei; Shengda Wang

doi:10.1051/matecconf/20168102001

All issues

Volume 81 (2016)

MATEC Web Conf., 81 (2016) 02001

References

Open Access

Issue		MATEC Web Conf. Volume 81, 2016 2016 5^th 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

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) [Google Scholar]
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] [Google Scholar]
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] [Google Scholar]
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] [Google Scholar]
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] [Google Scholar]
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] [Google Scholar]
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) [Google Scholar]
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] [Google Scholar]
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] [Google Scholar]
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] [Google Scholar]
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] [Google Scholar]
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] [Google Scholar]
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] [Google Scholar]
P. Seiler, B. Song, and J. K. Hedrick, “Development of a collision avoidance system”, Development, 4, pp. 17–22, 1998 [Google Scholar]
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] [Google Scholar]
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] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.

[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) [Google Scholar]

[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] [Google Scholar]

[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] [Google Scholar]

[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] [Google Scholar]

[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] [Google Scholar]

[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] [Google Scholar]

[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) [Google Scholar]

[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] [Google Scholar]

[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] [Google Scholar]

[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] [Google Scholar]

[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] [Google Scholar]

[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] [Google Scholar]

[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] [Google Scholar]

[14] P. Seiler, B. Song, and J. K. Hedrick, “Development of a collision avoidance system”, Development, 4, pp. 17–22, 1998 [Google Scholar]

[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] [Google Scholar]

[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] [Google Scholar]