To plan the urban traffic path using the ant colony algorithm, the composition and functional division of the mobile robot are analyzed. The TSP (Traveling Salesman Problem) is used to deeply understand the traditional ant colony algorithm. Then, based on this, the improvement scheme of the traditional ant colony algorithm is analyzed. The results showed that the artificial potential field method and the A* algorithm improved the performance of the ant colony algorithm. At the initial stage of the search path, the blindness and randomness of the ant colony algorithm due to insufficient pheromone concentration in each path were solved. The local optimal path is avoided with the development of algorithm iteration. Therefore, the improved ant colony algorithm is superior to the traditional ant colony algorithm.
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1 September 2019
Research Article|
September 01 2019
Application of Hybrid Ant Colony Algorithm in Urban Traffic Path Planning Available to Purchase
* Corresponding author: Yu Zhou
Publisher: Emerald Publishing
Online ISSN: 2633-9838
Print ISSN: 0168-2601
© 2019 Open House International
2019
Licensed re-use rights only.
Open House International (2019) 44 (3): 96–99.
Citation
Zhou Y (2019), "Application of Hybrid Ant Colony Algorithm in Urban Traffic Path Planning". Open House International, Vol. 44 No. 3 pp. 96–99, doi: https://doi.org/10.1108/OHI-03-2019-B0025
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