The multi-vision fusion intelligent driving assistance system uses various sensors (millimeter wave radar, lidar, mono/binocular camera and satellite navigation) installed on the car to sense the surrounding environment at any time during the driving process of the car, collect the environmental data inside and outside the car at the first time, identify, detect and track static and dynamic objects, and combine the navigation map data to carry out systematic operation and analysis, this can allow the driver to detect possible dangers in the fastest time, and effectively increase the comfort and safety of car driving. The development of the system is to improve the driver's driving experience and driving safety as the starting point, based on deep learning technology to achieve the detection and recognition of road traffic targets and lane lines. The system will intelligently judge the safe distance between the vehicle in front of the vehicle and the pedestrian, and automatically remind the driver to pay attention to the traffic signs. When the vehicle is deviating from the current road, it will prompt the driver. Relying on laser radar and camera to achieve parking blind spot detection. Through the detection and analysis of the driver's face, the driver is reminded that driving fatigue or distraction has occurred when necessary. The system also realizes the interconnection between the vehicle terminal and the mobile terminal through the local area network, and the user can view or download the driving record from the terminal according to his own preference.