The high popularity of automobiles has led to frequent collisions. According to the latest statistics of the United Nations, about 1.25 million people worldwide die from road traffic accidents each year. In order to improve the safety of vehicles in driving, the active safety system has become a research hotspot of various car companies and research institutions around the world. Among them, the more mature and popular active security system are Forward Collision Warning(FCW) and Autonomous Emergency Braking(AEB). However, the current active safety system is based on traditional sensors such as radar and camera. Therefore, the system itself has many limitations due to the shortage of traditional sensors. Compared to traditional sensors, Vehicle to Everything (V2X) technology has the advantages of richer vehicle parameter information, no perceived blind spots, dynamic prediction of dangerous vehicle status, and no occlusion restriction. In order to overcome the many shortcomings of the existing anti-collision warning system and strategy, this paper proposes a curved road collision prevention warning strategy based on V2X technology. Through V2X technology, the state information released by the neighboring car and the road environment information issued by the roadside unit are obtained. Using the above information and the state information of the vehicle, the relative positional relationship between the car and the neighboring car is dynamically predicted in real time, and then a two-degree-of-freedom dynamic collision time model and a two-degree-of-freedom collision time threshold model are proposed and designed. Finally, based on the output parameters of the above model, a two-degree-of-freedom curved road collision prevention warning system of automobile based on V2X technology is proposed, and a layered early warning mechanism is established. Through the PreScan environment, the typical working conditions and early warning strategy models are built by Matlab & Simulink, and the simulation of the early warning strategy is completed.