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Localización: Hogar / Tecnología / Planificación de ruta de puntos escénicos basados en un algoritmo mejorado*

Planificación de ruta de puntos escénicos basados en un algoritmo mejorado*

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Con el desarrollo de la economía social, el nivel de vida de las personas ha mejorado significativamente, y el turismo se ha convertido en una de las formas más entusiastas para las personas en su tiempo libre.Para los turistas, el terreno de las manchas escénicas a menudo es resistente, por lo que es esencial mantener suficiente energía para visitarlos. At the same time, for scenic spots, an efficient tour path can also reduce the congestion of scenic spots and improve the resource utilization of scenic spots, which is conducive to the sustainable and healthy development of scenic spots1.Por lo tanto, la planificación razonable de la ruta del recorrido es muy importante para la experiencia de los turistas..

For the optimal path solving problem, researchers have proposed many classical algorithms including dijestra algorithm, Flow Direction algorithm2, etc. Dijkstra algorithm was proposed in 1959, and the algorithm is suitable for static networks, that is, when the weight in the network is fixed and there is no negative weight3.En la mejora del algoritmo, Zhang et al. proposed a path planning method based on dijkstra, which can save driving time and oil consumption4.Rosita et al. used vector normalization technology combined with dijkstra algorithm to achieve the optimal distribution path of products5.Sabri et al. used the combination of dijkstra algorithm and ant colony algorithm to find the safest escape path in high-rise buildings6. Ant colony algorithm was proposed by Italian scientist Dorigo according to the foraging process of animals, and the algorithm was originally used to solve the traveling salesman problem7.Después de eso, muchos investigadores mejoraron el algoritmo, por ejemplo, Zhou et al.. optimized the intelligent logistics distribution path based on the improved ant colony algorithm, which was better to improve the dynamic optimization performance of the algorithm8.Yu et al. combined a special genetic operator in the ant colony algorithm, which not only avoids the local search limitations of the ant colony algorithm, but also enhances the global optimal searching ability of the ant colony algorithm9.Además, hay muchos algoritmos y mejoras para resolver el problema de ruta más corto, como Miao et al..propuso un algoritmo mejorado de colonia de hormigas adaptativas. While improving the real-time and security of robot path planning, balance the convergence and global search ability of ant colony algorithm, and transform the path planning problem into a multi-objective optimization problem by introducing multi-objective performance index, so as to realize the global comprehensive optimization of robot path planning10.Hsieh et al. proposed a route planning algorithm which combines the two-way fast-exploring random tree algorithm and greedy algorithm to generate various route planning schemes for ice navigation, and evaluated and selected a relatively optimal route with a lower risk scheme through a risk index11.Rakita et al. proposed a new sampling-based path planning method, which quickly finds solutions to high-dimensional path planning problems by minimizing the number of collision check samples12.Pan et al. used the improved floyd algorithm to design the optimal delivery path for take-out food, so that the travel time of the vehicle after optimization was shortened and the time efficiency was improved, but the algorithm did not consider the impact of road conditions13.Wu et al. combined normal distributed random numbers with genetic algorithms, and considered traveling least costs and the traveling highest experience index to construct the optimal tourism path14.Aunque los algoritmos se han mejorado para sus respectivos problemas, algunas de sus deficiencias inherentes son difíciles de erradicar.Como el método de búsqueda directa más efectivo para resolver la ruta más corta en la red de carreteras estáticas, un algoritmo* se ha mejorado innumerables.Wang et al.Introdujo el factor de giro en el algoritmo A* para resolver el problema de la ruta más corta. At the same time, they proposed a dynamic path planning method based on the A* algorithm, which can effectively search the shortest path and avoid collision15.Liu et al. Proposed an improved A* algorithm to solve the combination of normal channel and berthing channel16.Uttendorf et al. combined the fuzzy inference system with the A* algorithm to generate a path map for automatically guided vehicles17.Das et al. proposed an online path planning method based on an improved real-time A* algorithm, which plans the optimal path by avoiding obstructions and minimizing time, energy, and distance as the cost18.Shin et al. proposed an improved A* algorithm using Automatic Identification System (AIS) and weather data, and it finds the optimal paths by minimizing the estimated time of arrival generated by machine learning through 16-way node exploration19.Alani et al. proposed a new technique that consists of a hybridizing of A* algorithm and ant colony optimization, and the new technology can more accurately find the best parking path20.Pradhan et al. and Pardines both proposed to implement shopping guide path recommendations based on consumers' shopping lists, but they did not consider the problem of supermarket space modeling21,22.Ma et al. proposed a navigation path planning method for articulated underground scrapers based on improved A* algorithm to improve search efficiency23.Rahul et al. solved the problem of robotic path planning using a combination of A* algorithm and Fuzzy Inference, which finds the shortest path and generates the result in a finite time24.

En el estudio de planificación de ruta anterior, hay muchos métodos de Dijkstra y algoritmos de inteligencia de enjambre.Aunque los algoritmos se han mejorado para sus propios problemas, la ineficiencia del algoritmo Dijkstra en sí y el problema del algoritmo de colonia de hormigas que es sensible a los parámetros del algoritmo es difícil de resolver.Además, la mejora de un algoritmo* todavía tiene el problema de ignorar el costo de la carretera.Para proporcionar una mejor planificación de ruta escénica para los pasajeros, este documento presenta un método de planificación de ruta basado en un algoritmo mejorado*.Al ponderar exponencialmente la función heurística del algoritmo A*, la eficiencia de cálculo del algoritmo se mejora, y el algoritmo A* se mejora utilizando la información de la condición de la carretera de los puntos escénicos como índice de evaluación, lo que hace que el algoritmo sea más aplicable alPlanificación de ruta spot spot real.

Path planning of scenic spots based on improved A* algorithm