This paper bring forward a variational Bayes trajectory prediction algorithm based on Gaussian mixture trajectory model. It is assumed that the movement patterns of moving target can be statistically modeled by a common Gaussian mixture model, and this algorithm contains three main steps: 1.Data preprocessing. 2. Ttajectory model training. 3. Trajectory prediction. Meanwhile, this paper analysed the error of this algorithm, according to the real-world data set, the simulation result indicates that: Compared with EM prediction algorithm under the same parameter setting, the trajectory prediction accuracy of VB prediction algorithm is increased by 87.3% on average.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Trajectory Prediction Algorithm Based on Variational Bayes


    Contributors:
    Ma, Xiaolong (author) / Liu, Gang (author) / He, Bing (author) / Zhang, Kaijie (author) / Zhang, Xianyang (author) / Zhao, Xin (author)


    Publication date :

    2018-08-01


    Size :

    219933 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Variational-Bayes Optical Flow

    Chantas, G. | British Library Online Contents | 2014


    Vehicle Trajectory Prediction Using Intention-based Conditional Variational Autoencoder

    Feng, Xidong / Cen, Zhepeng / Hu, Jianming et al. | IEEE | 2019


    Prediction of Road Congestion Level Based on Bayes Algorithm

    Xiao, Shou Bai | Trans Tech Publications | 2014



    Frenet-Based Algorithm for Trajectory Prediction

    Avanzini, G. | Online Contents | 2004