Path planning of scenic spots based on improved A* algorithm

被引:0
|
作者
Xingdong Wang
Haowei Zhang
Shuo Liu
Jialu Wang
Yuhua Wang
Donghui Shangguan
机构
[1] Henan University of Technology,College of Information Science and Engineering
[2] Anshun University,School of Resources and Environmental Engineering
[3] Chinese Academy Sciences,State Key Laboratory of Cryospheric Science, Northwest Institute of Eco
来源
关键词
D O I
暂无
中图分类号
学科分类号
摘要
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.
引用
收藏
相关论文
共 50 条
  • [1] Path planning of scenic spots based on improved A* algorithm
    Wang, Xingdong
    Zhang, Haowei
    Liu, Shuo
    Wang, Jialu
    Wang, Yuhua
    Shangguan, Donghui
    SCIENTIFIC REPORTS, 2022, 12 (01)
  • [2] An Improved Ant Colony Algorithm for Path Planning in One Scenic Area With Many Spots
    Zhang, Wenbo
    Gong, Xiaopeng
    Han, Guangjie
    Zhao, Yuntao
    IEEE ACCESS, 2017, 5 : 13260 - 13269
  • [3] Path Planning Based on Improved Hybrid A* Algorithm
    Tang, Bijun
    Hirota, Kaoru
    Wu, Xiangdong
    Dai, Yaping
    Jia, Zhiyang
    JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS, 2021, 25 (01) : 64 - 72
  • [4] Robot Path Planning Based on Improved A* Algorithm
    Peng, Jiansheng
    Huang, Yiyong
    Luo, Guan
    CYBERNETICS AND INFORMATION TECHNOLOGIES, 2015, 15 (02) : 171 - 180
  • [5] Cruise shore excursion planning based on accessibility of scenic spots
    Sun, Xiaodong
    Xu, Meihua
    Lau, Yui-yip
    Kanrak, Maneerat
    Ng, Adolf K. Y.
    RESEARCH IN TRANSPORTATION BUSINESS AND MANAGEMENT, 2023, 49
  • [6] ARA☆+: Improved path planning algorithm based on ARA☆
    Li, Bo
    Gong, Jianwei
    Jiang, Yan
    Nasry, Hany
    Xiong, Guangming
    2012 IEEE/WIC/ACM INTERNATIONAL CONFERENCE ON WEB INTELLIGENCE AND INTELLIGENT AGENT TECHNOLOGY (WI-IAT 2012), VOL 2, 2012, : 361 - 365
  • [7] An improved path planning algorithm based on fuel consumption
    Tianbo Liu
    Jindong Zhang
    The Journal of Supercomputing, 2022, 78 : 12973 - 13003
  • [8] A Path Planning Algorithm for Robots Based on Improved QPSO
    Tao, Chongyang
    Yang, Jihua
    Zhao, Hang
    INTERNATIONAL CONFERENCE ON COMPUTATIONAL AND INFORMATION SCIENCES (ICCIS 2014), 2014, : 548 - 554
  • [9] The Path Planning of Mobile Robots Based on an Improved A* Algorithm
    Chang, Lu
    Shan, Liang
    Li, Jun
    Dai, Yuewei
    PROCEEDINGS OF THE 2019 IEEE 16TH INTERNATIONAL CONFERENCE ON NETWORKING, SENSING AND CONTROL (ICNSC 2019), 2019, : 257 - 262
  • [10] An improved path planning algorithm based on fuel consumption
    Liu, Tianbo
    Zhang, Jindong
    JOURNAL OF SUPERCOMPUTING, 2022, 78 (11): : 12973 - 13003