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Data Processing and Algorithm Analysis of Vehicle Path Planning Based on Wireless Sensor Network

机译:基于无线传感器网络的车辆路径规划数据处理与算法分析

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Optimizing the path planning to reduce the time and cost is an essential consideration in modern society, and existing research has mostly concentrated on static path planning and real-time data information in vehicle navigational applications. Using dynamic path planning to adjust and update the path information in time is a challenging approach to reduce road congestion and traffic accidents. In this paper, we present a data analysis algorithm that determines an efficient dynamic path for vehicle repair-scrap sites and navigates more flexibly to avoid obstacles, where the key idea is to design the sensor wireless network that helps to obtain data from different devices. Firstly, the data processing scheme for real-time data with regional cluster and node division can be obtained from different sensor devices through the wireless senor network. Secondly, the search space and the relevant road information are restricted to a strongly connected graph. The most important strategy for an optimal solution to find the shortest path is the search method. Finally, to validate the performance of our design and algorithm, we have conducted a simulation based on necessary traffic variables. The performance simulation results show that real-time dynamic path planning can be significantly optimized using our data processing scheme.
机译:优化路径规划以减少时间和成本是现代社会的重要考虑,并且现有研究主要集中在车辆导航应用中的静态路径规划和实时数据信息上。使用动态路径规划及时调整和更新路径信息是减少道路拥堵和交通事故的具有挑战性的方法。在本文中,我们提出了一种数据分析算法,该算法可以确定车辆维修报废站点的有效动态路径,并可以更灵活地导航以避开障碍物,其关键思想是设计有助于从不同设备获取数据的传感器无线网络。首先,可以通过无线传感器网络从不同的传感器设备获得具有区域集群和节点划分的实时数据的数据处理方案。其次,搜索空间和相关道路信息被限制在一个强连接图上。寻找最短路径的最佳解决方案的最重要策略是搜索方法。最后,为了验证我们的设计和算法的性能,我们基于必要的流量变量进行了仿真。性能仿真结果表明,使用我们的数据处理方案可以显着优化实时动态路径规划。

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