Affiliation:
1. School of Liberal Arts and Sciences, North China Institute of Aerospace Engineering, Langfang, Hebei, China
2. Engineering Computing and Simulation Innovation Lab, North China University of Science and Technology, Tangshan, Hebei, China
Abstract
In recent years, with the improvement of Internet of Things (IOT) technology, a “shared” service concept has appeared in people’s life. In the limited available resources, it is of great value to study the optimal path of charging pile selection for shared cars. With the help of Internet of Things technology and through analyzing the collected data, this paper introduces three path optimization methods, the Dijkstra algorithm, heuristic algorithm A∗, and improved particle swarm optimization (PSO) algorithm; establishes relevant convergence conditions; and takes the actual path cost as the criterion to judge the optimal path. In addition, this paper studies the optimal path from the shared car to the charging pile. Through the simulation experiment, the results show that compared with the traditional optimal path algorithm, the improved particle swarm optimization algorithm has strong parallelism and better search effect for optimal path selection in the case of large number of traffic path nodes and complex paths, which fully reflects the performance advantage of the algorithm.
Funder
Research Project of Langfang Science and Technology Bureau
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Information Systems
Cited by
3 articles.
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