Multi-source Information Fusion for Video Detection in Highway

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Modern Transportation

Modern Transportation is an international comprehensive professional academic journal of Ivy Publisher, concerning the development of transportation building and management. The main focus of the journal is the academic papers and comments of latest transportation engineering, system engineering and road engineering improvement in the fields of nature science, engineering technology, economy and science, report of latest research result, aiming a... [More] Modern Transportation is an international comprehensive professional academic journal of Ivy Publisher, concerning the development of transportation building and management. The main focus of the journal is the academic papers and comments of latest transportation engineering, system engineering and road engineering improvement in the fields of nature science, engineering technology, economy and science, report of latest research result, aiming at providing a good communication platform to transfer, share and discuss the theoretical and technical development for professionals, scholars and researchers in this field, reflecting the academic front level, promote academic change and seize the transportation technology theory, practice front line, research level and development direction.

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Paper Infomation

Multi-source Information Fusion for Video Detection in Highway

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Author: Jian Wan, Jinzhang Ji, Weifeng Wang, Li Zhang

Abstract: The accuracy and comprehensiveness of road traffic information detecting can be improved by multi-source information fusion. Firstly, this paper takes video detection technology used in multi-source information fusion process as the leading factor to meet the demand of traffic information detecting. Secondly, multi-level fusion with traffic video information on data level, feature level and decision level is studied based on data fusion theory. Lastly, the method multi-source information fusion process of highway which is used for traffic state recognizing and traffic flow detecting is analyzed. This research provides a new method for the design and application of highway and transportation information detecting.

Keywords: Multi-Source Information Fusion; Video Detection Technology; Traffic Characteristics

References:

[1] LIU Wei-ning, ZENG Heng, SUN Di-hua,et al. Video-based Discriminant Model of Traffic Congestion[J]. Application Research of Computers, 2010, 27(8):3006-3008.

[2] JIANG Xin-chun, LIU Xiao-ming. Analysis of Vehicle Behavioral Safety on Freeway Based on Video Detection[J]. Journal of Highway and Transportation Research and Development, 2010, 27(1):122-125.

[3] YANG Zhao-sheng, Feng Jin-qiao, ZHANG Lin. Kalman filtering based Traffic Information Fusion Method[J]. Journal of Jilin University (Engineering and Technology Edition), 2007, 37(5):1039-1042.

[4] David L.Hall,James Llinas. Handbook of Multisensor Data Fusion[M]. Beijing: Publishing House of electronics industry, 2008.

[5] YANG Zhao-sheng,WANG Shuang,MA Dao-song. Review of Basic Traftic Data Fusion Methods[J]. Journal of Highway and Transportation Research and Development, 2006, 23(3):111-116.

[6] GONG Da-li. Study on the Key Technology of Urban Traffic Intelligent Monitoring System[D].Xi’an: Chang'an University,2009.

[7] GUO Lin.Traffic Information Collection based on Information Fusion[D].Hefei: University of Science and Technology of China, 2007.

[8] WENG Jian-cheng, ZHAO Xiao-juan, RONG Jian. Urban Expressway Automatic Incident Detection Algorithm Based on D-S Theory[J]. Journal of Highway and Transportation Research and Development. 2011, 28(12):112-116.

[9] Lim, S, Lee, C. Data fusion algorithm improves travel time predictions[J]. 2011, 5(4):302-309.

[10] LI Cun-jun,YANG Ru-gui,JIN Fan. Data-Fusion Prediction of Traffic Information Based on Artificial Neural Network[J]. Systems Engineering. 2004, 22(3):80-85.

[11] YANG Zhao-sheng, YANG Qing-fang, FENG Jin-qiao. Fuzzy-combination Algorithm for Traffic Incident Identification[J]. Journal of Highway and Transportation Research and Development, 2003, 20(4): 92-94.

[12] Yingjie Xia, Zhoumin Ye , Yiwen Fang, et al. Parallelized extraction of traffic state estimation rules based on bootstrapping rough set[C]. //Fuzzy Systems and Knowledge Discovery (FSKD), 2012 9th International Conference .Sichuan. 2012:1532-1536.