Progress made in researching autonomous vehicle systems based on BeiDou navigation

Abstract

The evolution of smart transport systems has made autonomous vehicles a central focus for research. The BeiDou navigation system's highly accurate location data is vital for environmental detection, autonomous vehicle decision-making, and navigation. This research aims to develop and actualize a system for autonomous vehicles to plan routes and evade obstacles, utilizing the BeiDou satellite navigational framework. Consequently, this document introduces an algorithm for planning paths and avoiding obstacles that integrate BeiDou navigation data, capable of adjusting to intricate traffic conditions and enhancing the safety and efficiency of autonomous vehicles. Verification of the suggested algorithm was conducted on the environment simulation platform within the ROS operating system, revealing the algorithm's capability to create the ideal path and successfully evade dynamic obstacles. The practical vehicle testing verifies the algorithm's practicality and steadiness in traffic situations. Ultimately, the document encapsulates the study's findings and outlines prospective research avenues, encompassing the acquisition of both image and depth information, along with conducting image recognition and car tracking.