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Research on the Behavioral Dynamics Motion Planning Method of the Human-Vehicle Social Force Model

The interactive motion planning between unmanned vehicles and pedestrians in urban road environments is the key to realizing the autonomous motion of unmanned vehicles in hybrid traffic scenarios. The problem of human-vehicle interaction motion planning modeling at complex intersections is studied f...

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Detalles Bibliográficos
Autores principales: Han, Gaining, Wu, Zongsheng, Zhang, Wei, Wang, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9635974/
https://www.ncbi.nlm.nih.gov/pubmed/36337268
http://dx.doi.org/10.1155/2022/3154532
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author Han, Gaining
Wu, Zongsheng
Zhang, Wei
Wang, Wei
author_facet Han, Gaining
Wu, Zongsheng
Zhang, Wei
Wang, Wei
author_sort Han, Gaining
collection PubMed
description The interactive motion planning between unmanned vehicles and pedestrians in urban road environments is the key to realizing the autonomous motion of unmanned vehicles in hybrid traffic scenarios. The problem of human-vehicle interaction motion planning modeling at complex intersections is studied for an unmanned vehicle in this article. First, the motion planning of pedestrians and the unmanned vehicles is established according to the social force model and the behavioral dynamics model. Then, the autonomous vehicle is added to the crowd, and the human-vehicle interaction force is established. The virtual force is added to the social force model and the behavioral dynamics model, respectively, and the improved social force model and the behavioral dynamics model are used for the motion planning of pedestrians and unmanned vehicles. In this way, the established model solves the problems of simple pedestrian interaction motion planning in the social force model and single-body motion planning in the behavioral dynamics and thus provides a strong support for multibody motion planning. Finally, through the interactive motion planning trajectory of pedestrians and unmanned vehicles in different scenes, the vehicle and pedestrian motion planning trajectory can effectively avoid overlapping or crossing, so as to avoid the collision, which verifies the effectiveness and feasibility of the proposed model.
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spelling pubmed-96359742022-11-05 Research on the Behavioral Dynamics Motion Planning Method of the Human-Vehicle Social Force Model Han, Gaining Wu, Zongsheng Zhang, Wei Wang, Wei Comput Intell Neurosci Research Article The interactive motion planning between unmanned vehicles and pedestrians in urban road environments is the key to realizing the autonomous motion of unmanned vehicles in hybrid traffic scenarios. The problem of human-vehicle interaction motion planning modeling at complex intersections is studied for an unmanned vehicle in this article. First, the motion planning of pedestrians and the unmanned vehicles is established according to the social force model and the behavioral dynamics model. Then, the autonomous vehicle is added to the crowd, and the human-vehicle interaction force is established. The virtual force is added to the social force model and the behavioral dynamics model, respectively, and the improved social force model and the behavioral dynamics model are used for the motion planning of pedestrians and unmanned vehicles. In this way, the established model solves the problems of simple pedestrian interaction motion planning in the social force model and single-body motion planning in the behavioral dynamics and thus provides a strong support for multibody motion planning. Finally, through the interactive motion planning trajectory of pedestrians and unmanned vehicles in different scenes, the vehicle and pedestrian motion planning trajectory can effectively avoid overlapping or crossing, so as to avoid the collision, which verifies the effectiveness and feasibility of the proposed model. Hindawi 2022-10-28 /pmc/articles/PMC9635974/ /pubmed/36337268 http://dx.doi.org/10.1155/2022/3154532 Text en Copyright © 2022 Gaining Han et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Han, Gaining
Wu, Zongsheng
Zhang, Wei
Wang, Wei
Research on the Behavioral Dynamics Motion Planning Method of the Human-Vehicle Social Force Model
title Research on the Behavioral Dynamics Motion Planning Method of the Human-Vehicle Social Force Model
title_full Research on the Behavioral Dynamics Motion Planning Method of the Human-Vehicle Social Force Model
title_fullStr Research on the Behavioral Dynamics Motion Planning Method of the Human-Vehicle Social Force Model
title_full_unstemmed Research on the Behavioral Dynamics Motion Planning Method of the Human-Vehicle Social Force Model
title_short Research on the Behavioral Dynamics Motion Planning Method of the Human-Vehicle Social Force Model
title_sort research on the behavioral dynamics motion planning method of the human-vehicle social force model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9635974/
https://www.ncbi.nlm.nih.gov/pubmed/36337268
http://dx.doi.org/10.1155/2022/3154532
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