@inproceedings{1710bd4988614bd4a19067abe96184fb,
title = "Point-of-Conflict Prediction for Pedestrian Path-Planning",
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. ",
keywords = "computer agent, path planning, pedestrian navigation, prediction",
author = "Trinh, {Thanh Trung} and Vu, {Dinh Minh} and Masaomi Kimura",
note = "Publisher Copyright: {\textcopyright} 2020 ACM.; 12th International Conference on Computer Modeling and Simulation, ICCMS 2020 and the 9th International Conference on Intelligent Computing and Applications. ICICA 2020 ; Conference date: 22-06-2020 Through 24-06-2020",
year = "2020",
month = jun,
day = "22",
doi = "10.1145/3408066.3408079",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "88--92",
booktitle = "Proceedings of ICCMS 2020 - 12th International Conference on Computer Modeling and Simulation and ICICA 2020 - 9th International Conference on Intelligent Computing and Applications",
}