Automobile rear end collision model on freeway

HOU Zhi-xiang; WU Yi-hu; LIU Zhen-wen; LI He-qing

Volume 4 Issue 4

Turn off MathJax

Article Contents

Article Navigation > Journal of Traffic and Transportation Engineering > 2004 > 4(4): 37-39

Next Previous

HOU Zhi-xiang, WU Yi-hu, LIU Zhen-wen, LI He-qing. Automobile rear end collision model on freeway[J]. Journal of Traffic and Transportation Engineering, 2004, 4(4): 37-39.

Citation:

HOU Zhi-xiang, WU Yi-hu, LIU Zhen-wen, LI He-qing. Automobile rear end collision model on freeway[J]. Journal of Traffic and Transportation Engineering, 2004, 4(4): 37-39.

HOU Zhi-xiang, WU Yi-hu, LIU Zhen-wen, LI He-qing. Automobile rear end collision model on freeway[J]. Journal of Traffic and Transportation Engineering, 2004, 4(4): 37-39.

Citation:

HOU Zhi-xiang, WU Yi-hu, LIU Zhen-wen, LI He-qing. Automobile rear end collision model on freeway[J]. Journal of Traffic and Transportation Engineering, 2004, 4(4): 37-39.

PDF( 144 KB)

Automobile rear end collision model on freeway

1.
School of Information Science and Engineering, Central South University, Changsha 410083, China
2.
School of Automobile and Mechanical Engineering, Changsha University of Science and Technology, Changsha 410076, China

More Information

Author Bio:
HOU Zhi-xiang(1971-), male, doctoral student, 86-731-5040119, houzhixiang2008@163.com
Received Date: 2004-05-30
Publish Date: 2004-12-25

Abstract

Abstract

A probability model of automobile rear end collision based on ANFIS(adaptive neural-fuzzy inference systems) was provided, the speed difference of automobiles, the speed of tracing automobile and the distance of automobiles were taken as inputs, and the probability of automobile rear end collision was taken as output. The probability of automobile rear end collision was calculated in different speed difference and distance of automobiles using the model. The probability model provides a new plan for analysing automobile rear end collision, and has directive role for decreasing automobile rear end collision on freeway.
- traffic safety,
- freeway,
- automobile rear end collision,
- ANFIS,
- prediction of automobile rear end collision

FullText(HTML)

References(6)

References

[1]	XIONG He-jin, LIUQing, YANG Jie. A study of back propagation neural networks model for car tracing cauda[J]. Journal of Wuhan Transportation University, 2002, 24(5): 25-28. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JTKJ200001007.htm
[2]	李作敏, 杜颖. 交通工程学[M]. 北京: 人民交通出版社, 1995.
[3]	ZHENG An-wen. The analysis of the motorway vehicle gap and designing the device of protective vehicle collision[J]. Journal ofWuhan University of Technology, 2002, 24(9): 62-65. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-WHGY200209018.htm
[4]	WANG Nian, REN Bin, HUANG Yong. The application of artificial neural networks in vehicle management[J]. Application of Electric Technology, 1998, 34(9): 11-12. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-DZJY809.002.htm
[5]	王永骥, 涂健. 神经元网络控制[M]. 北京: 机械工业出版社, 1999.
[6]	ZENG Qing-ning, LIU Qing, ZHOU De-xin. Nonlinear adaptive noise cancellation based on ANFIS[J]. Journal of China Communication, 2001, 18(12): 21-23. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-TXXB200112016.htm