Research on Computer Vision-Based Environment Perception and Decision-Making System for Autonomous Vehicles

This paper delves into the design and implementation of autonomous vehicle systems, with a focus on the overall architecture, hardware platforms, software design, and system integration. The autonomous driving system captures environmental information through high-precision sensors, which is then processed in real-time and decisions are made by powerful computing units, leading to vehicle control actions. Throughout the design and implementation process, emphasis is placed on real-time performance, robustness, and safety considerations. System performance is continuously enhanced through algorithm optimizations, hardware advancements, and improvements in system integration strategies. The objective of this research is to provide a robust foundation for the advancement of autonomous vehicles, thereby propelling progress in smart transportation systems.