Path planning of scenic spots based on improved A* algorithm
Abstract 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 evalua...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-01-01
|
| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-05386-6 |
| _version_ | 1819349705685991424 |
|---|---|
| author | Xingdong Wang Haowei Zhang Shuo Liu Jialu Wang Yuhua Wang Donghui Shangguan |
| author_facet | Xingdong Wang Haowei Zhang Shuo Liu Jialu Wang Yuhua Wang Donghui Shangguan |
| author_sort | Xingdong Wang |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-12-24T19:04:46Z |
| format | Article |
| id | doaj.art-e54a6fa478dd4ab58ef58052710054f4 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-12-24T19:04:46Z |
| publishDate | 2022-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-e54a6fa478dd4ab58ef58052710054f42022-12-21T16:43:08ZengNature PortfolioScientific Reports2045-23222022-01-011211710.1038/s41598-022-05386-6Path planning of scenic spots based on improved A* algorithmXingdong Wang0Haowei Zhang1Shuo Liu2Jialu Wang3Yuhua Wang4Donghui Shangguan5College of Information Science and Engineering, Henan University of TechnologyCollege of Information Science and Engineering, Henan University of TechnologyCollege of Information Science and Engineering, Henan University of TechnologySchool of Resources and Environmental Engineering, Anshun UniversityCollege of Information Science and Engineering, Henan University of TechnologyState Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy SciencesAbstract 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.https://doi.org/10.1038/s41598-022-05386-6 |
| spellingShingle | Xingdong Wang Haowei Zhang Shuo Liu Jialu Wang Yuhua Wang Donghui Shangguan Path planning of scenic spots based on improved A* algorithm Scientific Reports |
| 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 |
| url | https://doi.org/10.1038/s41598-022-05386-6 |
| work_keys_str_mv | AT xingdongwang pathplanningofscenicspotsbasedonimprovedaalgorithm AT haoweizhang pathplanningofscenicspotsbasedonimprovedaalgorithm AT shuoliu pathplanningofscenicspotsbasedonimprovedaalgorithm AT jialuwang pathplanningofscenicspotsbasedonimprovedaalgorithm AT yuhuawang pathplanningofscenicspotsbasedonimprovedaalgorithm AT donghuishangguan pathplanningofscenicspotsbasedonimprovedaalgorithm |