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Path planning of scenic spots based on improved A* algorithm
Traditional scenic route planning only considers the shortest path, which ignores the information of scenic road conditions. As the most effective direct search method to solve the shortest path in static road network, A* algorithm can plan the optimal scenic route by comprehensively evaluating the...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8789847/ https://www.ncbi.nlm.nih.gov/pubmed/35079066 http://dx.doi.org/10.1038/s41598-022-05386-6 |
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author | Wang, Xingdong Zhang, Haowei Liu, Shuo Wang, Jialu Wang, Yuhua Shangguan, Donghui |
author_facet | Wang, Xingdong Zhang, Haowei Liu, Shuo Wang, Jialu Wang, Yuhua Shangguan, Donghui |
author_sort | Wang, Xingdong |
collection | PubMed |
description | Traditional scenic route planning only considers the shortest path, which ignores the information of scenic road conditions. As the most effective direct search method to solve the shortest path in static road network, A* algorithm can plan the optimal scenic route by comprehensively evaluating the weights of each expanded node in the gridded scenic area. However, A* algorithm has the problem of traversing more nodes and ignoring the cost of road in the route planning. In order to bring better travel experience to the travelers, the above factors are taken into account. This paper presents a path planning method based on the improved A* algorithm. Firstly, the heuristic function of the A* algorithm is weighted by exponential decay to improve the calculation efficiency of the algorithm. Secondly, in order to increase the practicality of the A* algorithm, the impact factors that road conditions is introduced to the evaluation function. Finally, the feasibility of the improved A* algorithm is verified through simulation experiments. Experimental results show that the improved A* algorithm can effectively reduce the calculation time and road cost. |
format | Online Article Text |
id | pubmed-8789847 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-87898472022-01-27 Path planning of scenic spots based on improved A* algorithm Wang, Xingdong Zhang, Haowei Liu, Shuo Wang, Jialu Wang, Yuhua Shangguan, Donghui Sci Rep Article Traditional scenic route planning only considers the shortest path, which ignores the information of scenic road conditions. As the most effective direct search method to solve the shortest path in static road network, A* algorithm can plan the optimal scenic route by comprehensively evaluating the weights of each expanded node in the gridded scenic area. However, A* algorithm has the problem of traversing more nodes and ignoring the cost of road in the route planning. In order to bring better travel experience to the travelers, the above factors are taken into account. This paper presents a path planning method based on the improved A* algorithm. Firstly, the heuristic function of the A* algorithm is weighted by exponential decay to improve the calculation efficiency of the algorithm. Secondly, in order to increase the practicality of the A* algorithm, the impact factors that road conditions is introduced to the evaluation function. Finally, the feasibility of the improved A* algorithm is verified through simulation experiments. Experimental results show that the improved A* algorithm can effectively reduce the calculation time and road cost. Nature Publishing Group UK 2022-01-25 /pmc/articles/PMC8789847/ /pubmed/35079066 http://dx.doi.org/10.1038/s41598-022-05386-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Wang, Xingdong Zhang, Haowei Liu, Shuo Wang, Jialu Wang, Yuhua Shangguan, Donghui Path planning of scenic spots based on improved A* algorithm |
title | Path planning of scenic spots based on improved A* algorithm |
title_full | Path planning of scenic spots based on improved A* algorithm |
title_fullStr | Path planning of scenic spots based on improved A* algorithm |
title_full_unstemmed | Path planning of scenic spots based on improved A* algorithm |
title_short | Path planning of scenic spots based on improved A* algorithm |
title_sort | path planning of scenic spots based on improved a* algorithm |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8789847/ https://www.ncbi.nlm.nih.gov/pubmed/35079066 http://dx.doi.org/10.1038/s41598-022-05386-6 |
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