A route navigation algorithm for pedestrian simulation based on grid potential field
Pedestrian simulation modeling has become an important means to study the dynamic characters of dense populations. In the continuous pedestrian simulation model for complex simulation scenario with obstacles, the pedestrian path planning algorithm is an indispensable component, which is used for the...
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2019-12-01
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Series: | Advances in Mechanical Engineering |
Online Access: | https://doi.org/10.1177/1687814019897831 |
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doaj-93435678dc8c4a1a9365b02eb8ea4bd72020-11-25T03:52:12ZengSAGE PublishingAdvances in Mechanical Engineering1687-81402019-12-011110.1177/1687814019897831A route navigation algorithm for pedestrian simulation based on grid potential fieldMinghua Li0Yun Wei1Yan Xu2Beijing Urban Construction Group Co., Ltd., Beijing, ChinaNational Engineering Laboratory for Green & Safe Construction Technology in Urban Rail Transit, Beijing, ChinaDepartment of Civil and Environmental Engineering, University of South Florida, Tampa, FL, USAPedestrian simulation modeling has become an important means to study the dynamic characters of dense populations. In the continuous pedestrian simulation model for complex simulation scenario with obstacles, the pedestrian path planning algorithm is an indispensable component, which is used for the calculation of pedestrian macro path and microscopic movement desired direction. However, there is less efficiency and poor robustness in the existing pedestrian path planning algorithm. To address this issue, we propose a new pedestrian path planning algorithm to solve these problems in this article. In our algorithm, we have two steps to determine pedestrian movement path, that is, the discrete potential fields are first generated by the flood fill algorithm and then the pedestrian desired speeds are determined along the negative gradient direction in the discrete potential field. Combined with the social force model, the proposed algorithm is applied in a corridor, a simple scene, and a complex scene, respectively, to verify its effectiveness and efficiency. The results demonstrate that the proposed pedestrian path planning algorithm in this article can greatly improve the computational efficiency of the continuous pedestrian simulation model, strengthen the robustness of application in complex scenes.https://doi.org/10.1177/1687814019897831 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Minghua Li Yun Wei Yan Xu |
spellingShingle |
Minghua Li Yun Wei Yan Xu A route navigation algorithm for pedestrian simulation based on grid potential field Advances in Mechanical Engineering |
author_facet |
Minghua Li Yun Wei Yan Xu |
author_sort |
Minghua Li |
title |
A route navigation algorithm for pedestrian simulation based on grid potential field |
title_short |
A route navigation algorithm for pedestrian simulation based on grid potential field |
title_full |
A route navigation algorithm for pedestrian simulation based on grid potential field |
title_fullStr |
A route navigation algorithm for pedestrian simulation based on grid potential field |
title_full_unstemmed |
A route navigation algorithm for pedestrian simulation based on grid potential field |
title_sort |
route navigation algorithm for pedestrian simulation based on grid potential field |
publisher |
SAGE Publishing |
series |
Advances in Mechanical Engineering |
issn |
1687-8140 |
publishDate |
2019-12-01 |
description |
Pedestrian simulation modeling has become an important means to study the dynamic characters of dense populations. In the continuous pedestrian simulation model for complex simulation scenario with obstacles, the pedestrian path planning algorithm is an indispensable component, which is used for the calculation of pedestrian macro path and microscopic movement desired direction. However, there is less efficiency and poor robustness in the existing pedestrian path planning algorithm. To address this issue, we propose a new pedestrian path planning algorithm to solve these problems in this article. In our algorithm, we have two steps to determine pedestrian movement path, that is, the discrete potential fields are first generated by the flood fill algorithm and then the pedestrian desired speeds are determined along the negative gradient direction in the discrete potential field. Combined with the social force model, the proposed algorithm is applied in a corridor, a simple scene, and a complex scene, respectively, to verify its effectiveness and efficiency. The results demonstrate that the proposed pedestrian path planning algorithm in this article can greatly improve the computational efficiency of the continuous pedestrian simulation model, strengthen the robustness of application in complex scenes. |
url |
https://doi.org/10.1177/1687814019897831 |
work_keys_str_mv |
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