In order to comprehensively understand the application of video detection algorithms in road intelligent transportation systems and delve into the future development trends of this technology, a thorough exploration was conducted. Employing keyword analysis, the algorithms in this category were classified into three groups based on the perspective of detection objects: road and environment, vehicles, and road participants. A comprehensive comparison, analysis, and summarization of these algorithms were performed, along with a summary of their current application status in different road traffic scenarios. The core image processing algorithms utilized for various object detection tasks were categorized and compared. The development trend and key technical difficulties of video detection technology are systematically analyzed and summarized from three aspects: algorithms, detection objects and application scenarios. The research results show that video detection technology plays an important role in road intelligent traffic systems and is widely used. In the future, it is expected to further develop in the directions of deep learning algorithms, complex backgrounds, diverse objects.