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    Driving Behavior Motivation Model Research Based on Vehicle Trajectory Data

    Driving Behavior Motivation Model Research Based on Vehicle Trajectory Data


    Abstract The development of floating car technology provides a new method for studying driving behavior motivation. Massive vehicle trajectory data often contains rich potential semantic information such as traffic patterns and driving behavior habits. To overcome the nonstationarity of the spatial distribution of the original trajectory data, this paper designs a semantic mining method of traffic trajectory data to construct complex behavioral modeling of traffic trajectory data based on LDA latent semantic topic model, so that to depict the driving behavior interest patterns and explore the cognitive mechanism of driving behavior. Research results show that the driving motivation model constructed can estimate the probability of the potential driving motivation topic in each spatial grid, and then the driving trajectory will be transformed from random probability events into driving intention with intrinsic certainty.

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    Title :

    Driving Behavior Motivation Model Research Based on Vehicle Trajectory Data

    Contributors:
    Chen, Yun (author) / Jiang, Xin-hua (author) / Liao, Lyuchao (author) / Zou, Fu-min (author) / Zhang, Mei-run (author)
    Published in:

    Advances in Smart Vehicular Technology, Transportation, Communication and Applications ; 1 ; 36-44

    Smart Innovation, Systems and Technologies ; 86 , 1

    Publication date :

    2017-11-03

    Size :

    9 pages

    ISBN :

    978-3-319-70730-3 , 978-3-319-70729-7

    ISSN :

    2190-3018 , 2190-3026

    DOI :

    https://doi.org/10.1007/978-3-319-70730-3_5

    Type of media :

    Article/Chapter (Book)

    Type of material :

    Electronic Resource

    Language :

    English

    Keywords :

    Traffic trajectory , Driving behavior , Latent semantic analysis Engineering , Transportation Technology and Traffic Engineering , Computational Intelligence , Artificial Intelligence (incl. Robotics)

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