Sensor Fusion Applications in Intelligent Driving

Abstract

With the rapid development of intelligent driving technology, the role of sensors becomes increasingly pivotal, as these devices serve as the fundamental elements responsible for perception within the system. Their performance and accuracy are directly correlated with the overall reliability and safety of the intelligent driving system. This article systematically introduces the current application status and technological characteristics of different sensors (including visible light, millimeter wave radar, and lidar) in intelligent driving systems. This article conducts a comprehensive analysis of various sensors' strengths and limitations in complex urban environments, particularly focusing on their performance in high-density traffic scenarios and adverse weather conditions. Based on these findings, the study proposes an optimized multi-sensor fusion solution specifically designed for urban road networks that considers both cost-effectiveness and reliability. Furthermore, it explores emerging technological directions for next-generation urban traffic sensing systems, including vehicle infrastructure cooperative perception and AI-enhanced sensor fusion, discussing their potential applications in smart city development and analyzing the key technical and standardization challenges in their implementation.