Application and challenges of image sensing technology in intelligent driving

Image sensing technology is the core guarantee for autonomous driving to realize environmental perception and intelligent decision-making. It is of great significance to grasp the systematic research context of this field for industrial development. Based on the Web of Science data, this paper selects 508 studies in the highly correlated fields of image sensing and intelligent driving indexed in SCI-EXPANDED and SSCI. In this paper, the core author network, institutional cooperation mode, core keywords co-occurrence characteristics and research topic emergence trend are visualized and analyzed by using Vosviewer and CITESPACE software. The results show that the core authors are closely interconnected. Additionally, the pattern of institutional cooperation presents the bipolar distribution of China and South Korea, and shows a trend of sparse and uneven distribution. Furthermore, the core keywords are: “Semantic segmentation”, “Computer vision”, “Lane detection”, and so on, which focus on the direction of image sensing. Moreover, the research on emergent words from 2015 to 2025 has experienced three stages of evolution: the construction of basic systems, the deepening of Applied Technologies, and the breakthrough of interdisciplinary integration and innovation. This study vividly and clearly shows the knowledge structure of this field, clarifies the development context of this field, and provides an important reference for the follow-up research and industrial development.