Abstract: In response to the pain points of the complex operating environment of off-road tourist sightseeing vehicles (hereinafter referred to as "sightseeing vehicles"), the difficulty in supervising the operation of locomotives under high-frequency/high-load conditions, and the lagging traditional passive safety management, This paper systematically reviews the research status and development trends of domestic and international technologies for monitoring the safety situation of sightseeing vehicle bodies and preventing rollover, modeling and early warning control of anti-rollover dynamics, intelligent recognition and control of unsafe behaviors of personnel, and intelligent inspection technologies. By deeply analyzing the current technical bottlenecks faced by single-modal monitoring technology in complex unstructured scenic area environments, such as limited detection accuracy, the contradiction between edge-side computing power and ultra-fast real-time performance, and data privacy and security under vehicle-cloud collaboration, the four major development trends of intelligent early warning and control technology for sightseeing vehicles in the future are summarized and concluded. That is, to evolve towards the integrated GIS and IMU vehicle-road decoupled operation situation awareness, to leap towards the dual-driven braking health assessment of bi-directional long short-term memory (BiLSTM), to break through the behavior control based on temporal attention and cross-modal decoupling of people and vehicles, and to transform towards the standardized intelligent inspection based on digital twins. It aims to promote the upgrading of the special equipment safety management model from "passive accountability after the event" to a full life-cycle proactive risk prevention covering "pre-incident deterioration prediction-rapid intervention during the incident", and empower the high-quality development of the modern smart tourism transportation network.