Original scientific paper
https://doi.org/10.7307/ptt.v31i3.2927
Cyclist’s Intention Identification on Pedestrian-Bicycle Mixed Sections Based on Phase-Field Coupling Theory
Haibo Wang
; College Civil Aviation and Flight, Nanjing University of Aeronautics and Astronautics
Haiqing Si
; College Civil Aviation and Flight, Nanjing University of Aeronautics and Astronautics
Xiaoyuan Wang
; College of Electromechanical Engineering, Qingdao University of Science and Technology
Abstract
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.
Keywords
Hrčak ID:
221439
URI
Publication date:
7.6.2019.
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