With the adjustment of holiday policy and the rapid growth of consumers’ demand for tourism, severe overcrowding in hot senic spots has become one of the main bottlenecks that perplex the development of many scenic spots in China. Based on the relevant literature and relevant data obtained from practical investigation, the factors that affect the path planning of hotspots are reasonably weighted by entropy method, and short-term prediction method is used to predict the passenger flow. Based on the improved A* path search algorithm and careful consideration in the various costs of different scenic spots in the scenic area, we can determine which scenic spot should come next, and finally get the optimal path. When tourists arrive at different scenic spots, they will make further progress according to the overall situation of the scenic area and update the optimal path. This paper takes Huangguoshu Tianxing Bridge scenic spot as an example to verify the improved A* path search algorithm. When taking Tianxing Bridge as the starting point, the optimal path is obtained by predicting the passenger flow of each scenic spot in the scenic area and comprehensively evaluating the influence of various factors, taking into account the total cost of each scenic spot. This paper considers the single way for tourists to visit—walking. In fact, for the problems of scattered scenic spots and considerable distance between them, sightseeing cars and shared bicycles would be arranged in the scenic spots. But by changing the value of traffic speed, the arrival time of each scenic spot can be calculated. The result has wide applicability, and the optimal path planning method has certain flexibility, which can be widely used in the route planning of other scenic spots.


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    Titel :

    Study on Route Optimization of Seasonal Hot Spots


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Wang, Wuhong (Herausgeber:in) / Chen, Yanyan (Herausgeber:in) / He, Zhengbing (Herausgeber:in) / Jiang, Xiaobei (Herausgeber:in) / Zhao, Haixia (Autor:in) / Tong, Ting (Autor:in) / You, Jiangping (Autor:in)


    Erscheinungsdatum :

    2021-12-14


    Format / Umfang :

    17 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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