Research on Intelligent Guidance Optimal Path of Shared Car Charging in the IOT Environment

Yuefang Sun,Hao Wang,Zhaozhuang Guo,Chen Zhang,Kangkang Jin

doi:10.1155/2020/3714879

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.

Highlights

As a long-term problem, air pollution has not been fully improved, and automobile exhaust is an important cause of air pollution
With the support of Internet of Things (IOT) technology, it is of great significance to study the optimal path from shared cars to charging piles
Xiaolei [11] used the method of combining the Dijkstra algorithm with genetic algorithm to find the optimal path without the restriction of road network conditions. van der Zijpp and Catalano [12] proposed a shortest path optimization algorithm based on simulated annealing algorithm and genetic algorithm in 2009, which avoided the defect that a single algorithm was easy to fall into local optimum and improved the optimization efficiency

Summary

Introduction

As a long-term problem, air pollution has not been fully improved, and automobile exhaust is an important cause of air pollution. The rise of domestic shared electric vehicles, combined with the development of domestic and international urban parking guidance systems, has pointed out the development goals and directions for the study of the optimal path from shared electric cars to charging piles. Van der Zijpp and Catalano [12] proposed a shortest path optimization algorithm based on simulated annealing algorithm and genetic algorithm in 2009, which avoided the defect that a single algorithm was easy to fall into local optimum and improved the optimization efficiency. The above researches on parking guidance system and urban route guidance based on IOT have certain limitations, and there are few researches on the path planning of guiding shared cars to charging piles at home and abroad, because of the complexity of urban traffic network, the uncertain situation of vehicles in road network, the real time of vehicles, and roads situation. When we use real-time updated traffic data to search the path, higher requirements are put forward for the optimal path selection

IOT Technology

Question-Making and Analysis

Research Scheme of Optimal Path in Urban Network

Research on Optimal Induction Path Based on PSO Algorithm