Research on intelligent city parking guidance method based on ant colony algorithm
by Feng Gao; Aifeng Chen
International Journal of Innovative Computing and Applications (IJICA), Vol. 13, No. 1, 2022

Abstract: In order to get the most satisfactory parking space at the fastest speed, an intelligent urban parking guidance method based on ant colony algorithm is proposed. The main factors affecting the selection of parking spaces in parking lots are analysed, including walking distance, driving distance, walking time, driving time and so on. Each factor is set as multiple attributes of berth, and the optimal berth selection model of smart city is established. Ant colony algorithm is used to solve the model, obtain the optimal parking space, and realise intelligent guidance of intelligent city parking. The simulation results show that the proposed method is feasible and effective.

Online publication date: Thu, 10-Mar-2022

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