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

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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
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