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

Abstract

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.