Autonomous Vehicles and AI Perception Technology

Autonomous vehicles represent an advanced application of AI technology in the transportation field. The core challenge lies in how a vehicle can “understand” the road environment and make safe, reasonable driving decisions. To achieve this, autonomous driving systems are equipped with various sensors such as LiDAR, high-definition cameras, and millimeter-wave radar, which collect three-dimensional spatial information around the vehicle. AI models then fuse and process this multi-source data to identify objects like pedestrians, vehicles, traffic signs, and road obstacles, while also predicting their movement trajectories.

Deep learning neural networks handle decision-making actions such as acceleration, braking, and steering to avoid collisions and traffic violations. Many car manufacturers have already made commercial progress in assisted driving technologies, such as automatic parking, lane keeping, and adaptive cruise control. In some regions, fully autonomous driving tests are permitted under limited conditions, accelerating the technology's maturity. In the future, with the development of vehicle-to-everything (V2X) communication, cars will be able to interact with infrastructure and other vehicles in real time to enhance road safety and traffic efficiency.

However, autonomous driving still faces challenges in legal liability and ethical decision-making standards. Collaboration among government, industry, and academia is essential to establish regulations that ensure the safe and widespread adoption of these technologies.