Bicycle is one of the main factors that affects the traffic safety and capacity on pedestrian-bicycle mixed traffic sections. It is important for implementing the warning of bicycle safety and improving the active safety to identify the cyclists’ intention in the mixed traffic environments under the condition of the “Internet of Things”. The phase-field coupling theory has been developed in this paper to comprehensively analyse the generation, spring up, increase, transfer, regression and reduction method of the traffic phase. The adaptive genetic algorithm based on the information entropy has been used to extract feature vectors of different types of cyclists for intention identification from the reduced pedestrian-bicycle traffic phase, and the theory of evidence has been provided here to build the identification model. The experimental verification shows that the extraction method of cyclists’ intention feature vector and identification model are scientific and reasonable. The theoretical basis can be applied to establishing the pedestrian-bicycle interactive security system.


    Access

    Download


    Export, share and cite



    Title :

    Cyclist’s Intention Identification on Pedestrian-Bicycle Mixed Sections Based on Phase-Field Coupling Theory


    Contributors:
    Haibo Wang (author) / Haiqing Si (author) / Xiaoyuan Wang (author)


    Publication date :

    2019




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




    Design of bicycle facilities from a cyclist's point of view

    Ljungberg, C. | British Library Conference Proceedings | 1990


    Does Pedalling on a Recumbent Bicycle Influence the Cyclist's Steering Behaviour?

    Boon, K.M. / Klap, P. / van Lanen, J.A. et al. | Tema Archive | 2014


    Cyclist’s glove

    ZHANG MEIYING | European Patent Office | 2016

    Free access

    Cyclist's side warning light

    GRIBBIN AIDAN WILLIAM | European Patent Office | 2016

    Free access