Point-of-Conflict Prediction for Pedestrian Path-Planning

Thanh Trung Trinh, Dinh Minh Vu, Masaomi Kimura

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A simulation model for pedestrian navigation often requires many problems to be addressed. An example is pedestrian path-planning in the case of a moving obstacle within the environment. To resolve the problem, it is necessary to model the prediction process of the pedestrian agent in order to specify a point-of-conflict area. In this paper, we propose an approach for our pedestrian agent to navigate in this situation. This process is accomplished by predicting a possible point-of-conflict with the obstacle and planning the path accordingly. Our implementation of this approach has demonstrated the capability of the agent to plan a more competent path as well as closer to the thinking process in human cognition.

Original languageEnglish
Title of host publicationProceedings of ICCMS 2020 - 12th International Conference on Computer Modeling and Simulation and ICICA 2020 - 9th International Conference on Intelligent Computing and Applications
PublisherAssociation for Computing Machinery
Pages88-92
Number of pages5
ISBN (Electronic)9781450377034
DOIs
Publication statusPublished - 2020 Jun 22
Event12th International Conference on Computer Modeling and Simulation, ICCMS 2020 and the 9th International Conference on Intelligent Computing and Applications. ICICA 2020 - Virtual, Online, Australia
Duration: 2020 Jun 222020 Jun 24

Publication series

NameACM International Conference Proceeding Series

Conference

Conference12th International Conference on Computer Modeling and Simulation, ICCMS 2020 and the 9th International Conference on Intelligent Computing and Applications. ICICA 2020
CountryAustralia
CityVirtual, Online
Period20/6/2220/6/24

Keywords

  • computer agent
  • path planning
  • pedestrian navigation
  • prediction

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

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