Author(s)

Xingyu Wang ¹, Yuqing Gao ¹, Jiajia Zhou ¹, Hao Wu ¹

Affiliation(s)

¹ School of Management Science and Engineering, Anhui University of Finance & Economics, Bengbu, Anhui, 233030, China

Corresponding Author

Hao Wu

ABSTRACT

Unmanned autonomous vehicles play an important role in the future transportation field. It has changed the control mode of traditional cars from the source, and improved the safety and efficiency of the transportation system by means of science and technology. The optimal path of driverless vehicles is the focus of path planning, and selecting a correct algorithm is also the key. Ant colony algorithm is selected to improve the algorithm on the original basis, and change the pheromone update mode and search strategy. According to the combination of actual road conditions, the shortest path is not necessarily the best path. This improvement can better deal with emergencies in road conditions.

KEYWORDS

Driverless vehicle, optimal path, ant colony algorithm

CITE THIS PAPER

Xingyu Wang, Yuqing Gao, Jiajia Zhou, Hao Wu, Mini-Review of Unmanned Vehicle Route Planning Based on Ant Colony Algorithm. Automation and Machine Learning (2023) Vol. 4: 42-46. DOI: http://dx.doi.org/10.23977/autml.2023.040206.

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