吉林大学学报(工学版) ›› 2018, Vol. 48 ›› Issue (1): 330-335.doi: 10.13229/j.cnki.jdxbgxb20170373

• Orginal Article • Previous Articles     Next Articles

Instantaneous velocity extraction method on NGSLM data

LIU Dong-liang1, 2, WANG Qiu-shuang3   

  1. 1.School of Information Science and Technology, Northeast Normal University,Changchun 130021,China;
    2. Editorial Department of Journal of Jilin University(Information Science Edition),Changchun 130012,China;
    3.College of Computer Science and Technology,Jilin University,Changchun 130012,China
  • Received:2017-04-15 Online:2018-02-26 Published:2018-02-26

RICH HTML

0   

PDF (PC)

335

Abstract: Conventional traffic information acquisition technologies, such as virtual coil and WSN, have small information acquisition range that can not meet the requirement of wide range coordinate traffic. It can take the advantage of wide-area coverage of remote sensing image and meet the need of mass traffic information acquisition if the image information parameters is applied to set up the instantaneous velocity model of vehicle. In this paper, to solve the problem of wide-area traffic information acquisition, a instantaneous velocity model of the vehicle is set up based on the Back Propagation (BP) network and Next Generation Simulation (NGSIM) data by analyzing and determining the input parameters. The effectiveness of the model is validated using the data of similar period. This model differs from the general traffic information acquisition method, that it takes the advantage of wide-area coverage of remote sensing image, providing an effective way to acquire wide-area traffic information.

Key words: information processing technology, wide-area traffic information, vehicles instantaneous velocity, BP neural network

CLC Number: 

  • TN911.73
[1] 徐文聪. 基于视频的交通数据采集技术研究[D]. 山东大学机电与信息工程学院, 2012.
Xu Wen-cong.Research on the techniques of vision-based traffic data collection[D].Jinan:College of Mediatronics and Information Engineerig,Shandong University, 2012.
[2] Yin M, Zhang H, Meng H, et al.An HMM-based algorithm for vehicle detection in congested traffic situations[C]∥Intelligent Transportation Systems Conference,Seattle,WA,USA,2007: 736-741.
[3] Zhu Z, Xu G Y, Yang B, et al.VISATRAM: a real-time vision system for automatic traffic monitoring[J]. Image and Vision Computing, 2000, 18(10): 781-794.
[4] 李子青. 人脸识别技术应用和市场分析[J].中国安防,2007(8):49-53.
Li Zi-qing .Face recognition technology and market analysis[J]. Security & Protection,2007(8):42-46.
[5] Tan T N, Sullivan G D, Baker K D.Model-based localisation and recognition of road vehicles[J]. International Journal of Computer Vision, 1998, 27(1): 5-25.
[6] Tai J C, Tseng S T, Lin C P, et al.Real-time image tracking for automatic traffic monitoring and enforcement applications[J]. Image and Vision Computing, 2004, 22(6): 485-501.
[7] Jin S, Wang D H, Xu C, et al.Short-term traffic safety forecasting using Gaussian mixture model and Kalman filter[J]. Journal of Zhejiang University (Science A), 2013, 14(4): 231-243.
[8] Bajwa R, Rajagopal R, Varaiya P, et al.In-pavement wireless sensor network for vehicle classification[C]∥10th International Conference on Information Processing in Sensor Networks (IPSN),Chicago,IL,USA,2011: 85-96.
[9] 王祺,李力,胡坚明,等.不同车头间距下交通流的速度分布[J].清华大学学报: 自然科学版,2011,51(3):23-26.
Wang Qi, Li Li, Hu Jian-ming, et al.Traffic velocity distributions for different spacings[J]. Journal of Tsinghua University(Science and Technology), 2011, 51(3): 309-312.
[10] Leitloff J, Hinz S, Stilla U.Inferring traffic activity from optical satellite images[J]. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 2007, 36(3/W49B): 89-93.
[11] 索明亮. 卫星图像中运动车辆探测和速度提取研究 [D].北京: 北京交通大学城市交通复杂系统理论与技术教育部重点实验室,2011.
Suo Ming-liang.Research on moving vehicle detection and velocity extraction from satellite image[D].Beijing: MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology,Beijing Jiaotong University,2011.
[12] 张素兰. 基于卫星遥感影像的交通状态判别研究 [D].北京: 北京交通大学交通运输规划与管理学院,2010.
Zhang Su-lan.Research on traffic state estimation from satellite remote sensing images [D].Beijing: College of Transportation Planning and Management,Beijing Jiaotong University,2010.
[13] 王殿海. 交通流理论[M]. 北京: 人民交通出版社, 2002:52.
[14] Bonzani I, Mussone L.From the discrete kinetic theory of vehicular traffic flow to computing the velocity distribution at equilibrium[J]. Mathematical and Computer Modelling, 2009, 49(3): 610-616.
[15] Bando M, Hasebe K, Nakayama A, et al.Dynamical model of traffic congestion and numerical simulation[J]. Physical Review E, 1995, 51: 1035-1042.
[16] 李孝安, 张晓缋. 神经网络与神经计算机导论 [M]. 西安: 西安电子工业出版社, 1994.
[17] Wang J, Yang J, Wu W.Convergence of cyclic and almost-cyclic learning with momentum for feedforward neural networks[J].IEEE Transactions on Neural Networks,2011, 22(8): 1297-1306.
[1] YING Huan,LIU Song-hua,TANG Bo-wen,HAN Li-fang,ZHOU Liang. Efficient deterministic replay technique based on adaptive release strategy [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1917-1924.
[2] LIU Zhong-min,WANG Yang,LI Zhan-ming,HU Wen-jin. Image segmentation algorithm based on SLIC and fast nearest neighbor region merging [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1931-1937.
[3] SHAN Ze-biao,LIU Xiao-song,SHI Hong-wei,WANG Chun-yang,SHI Yao-wu. DOA tracking algorithm using dynamic compressed sensing [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1938-1944.
[4] YAO Hai-yang, WANG Hai-yan, ZHANG Zhi-chen, SHEN Xiao-hong. Reverse-joint signal detection model with double Duffing oscillator [J]. 吉林大学学报(工学版), 2018, 48(4): 1282-1290.
[5] QUAN Wei, HAO Xiao-ming, SUN Ya-dong, BAI Bao-hua, WANG Yu-ting. Development of individual objective lens for head-mounted projective display based on optical system of actual human eye [J]. 吉林大学学报(工学版), 2018, 48(4): 1291-1297.
[6] CHEN Mian-shu, SU Yue, SANG Ai-jun, LI Pei-peng. Image classification methods based on space vector model [J]. 吉林大学学报(工学版), 2018, 48(3): 943-951.
[7] CHEN Tao, CUI Yue-han, GUO Li-min. Improved algorithm of multiple signal classification for single snapshot [J]. 吉林大学学报(工学版), 2018, 48(3): 952-956.
[8] MENG Guang-wei, LI Rong-jia, WANG Xin, ZHOU Li-ming, GU Shuai. Analysis of intensity factors of interface crack in piezoelectric bimaterials [J]. 吉林大学学报(工学版), 2018, 48(2): 500-506.
[9] LIN Jin-hua, WANG Yan-jie, SUN Hong-hai. Improved feature-adaptive subdivision for Catmull-Clark surface model [J]. 吉林大学学报(工学版), 2018, 48(2): 625-632.
[10] WANG Ke, LIU Fu, KANG Bing, HUO Tong-tong, ZHOU Qiu-zhan. Bionic hypocenter localization method inspired by sand scorpion in locating preys [J]. 吉林大学学报(工学版), 2018, 48(2): 633-639.
[11] YU Hua-nan, DU Yao, GUO Shu-xu. High-precision synchronous phasor measurement based on compressed sensing [J]. 吉林大学学报(工学版), 2018, 48(1): 312-318.
[12] WANG Fang-shi, WANG Jian, LI Bing, WANG Bo. Deep attribute learning based traffic sign detection [J]. 吉林大学学报(工学版), 2018, 48(1): 319-329.
[13] TANG Kun, SHI Rong-hua. Detection of wireless sensor network failure area based on butterfly effect signal [J]. 吉林大学学报(工学版), 2017, 47(6): 1939-1948.
[14] LI Juan, MENG Ke-xin, LI Yue, LIU Hui-li. Seismic signal noise suppression based on similarity matched Wiener filtering [J]. 吉林大学学报(工学版), 2017, 47(6): 1964-1968.
[15] YANG Chao-yu, LI Ce, LIANG Yin-cheng, YANG Feng. Blurred object detection based on improved particle filter in coal mine underground surveilance [J]. 吉林大学学报(工学版), 2017, 47(6): 1976-1985.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
[1] JIAO Yu-ling, XU Liang-cheng, WANG Zhan-zhong, ZHANG Peng. Balance experiment and analysis of double U-shaped assembly line based on directed network[J]. 吉林大学学报(工学版), 2018, 48(2): 454 -459 .
Copyright © Journal of Jilin University(Engineering and Technology Edition), All Rights Reserved.
Tel: +86-431-85095297　Fax: +86-431-85094074　E-mail: xbgxb@jlu.edu.cn
Powered by Beijing Magtech Co. Ltd