Research on an Intelligent Vehicle Emergency Avoidance Algorithm Based on User Behaviour Learning

With the development of the Internet of Vehicles and the high-precision lane-level navigation system, vehicles can receive more road details. And the systems will provide conditions for the development of the emergency avoidance function. This paper studies a vehicle automatic emergency avoidance algorithm based on user behaviour learning. The research is based on the Internet of Vehicles to obtain user driving data, generate a user database, and through the analysis of the avoidance track under the user's active operation conditions, generate a track equation or empirical formula, and the vehicle control unit executes the emergency avoidance action according to this. In the algorithm, the emergency avoidance function is defined as based on the vehicle's active safety system to avoid the event of a sudden situation, and the function will briefly disconnect the driver's partial operation when it is intervened, and the trigger conditions are set according to the trigger conditions of the parallel emergency braking function. The track equation is fitted using a sinusoidal signal, and the final output is the vehicle's front wheel angle.