Research On Vehicle Collision Avoidance Control Algorithm Based On Millimeter Wave Radar

It is an essential condition for the active safety of the vehicle to avoid the false alarm rate and miss alarm rate.The reliability of the vehicle collision avoidance system is mainly related to the state of the vehicle and the adhesion coefficient of the road and the driver's reaction time.The cost of using sensors to measure the vehicle state and road surface adhesion coefficient is too high,so this paper proposes to use the double extended Calman filter to estimate the state of the vehicle and the road surface adhesion coefficient.The dual extended Calman filter algorithm is combined with the traditional NHTSA algorithm,and the driver's reaction time is taken into consideration to get a new anticollision algorithm.This paper established a HSRI tire model and a four degrees of freedom vehicle model,vehicle state variables measured by the sensor and tire and four degrees of freedom car model will be combined to estimate the road friction coefficient and vehicle state by using double extended Calman filter.Two extended Calman filters are used to estimate the state of the vehicle and the road surface adhesion coefficient respectively.The NHTSA anticollision algorithm is improved,and Matlab and CarSim are used to verify the reliability of the algorithm.The simulation results show that the double extended Calman filter can accurately estimate the vehicle's state and road surface adhesion coefficient.The vehicle collision avoidance system is closely related to reaction time of driver,the reaction time of drivers with a function that combines with NHTSA to further improve the reliability of the algorithm.After Matlab simulation,the simulation results show that vehicle collision avoidance system can reduce the false alarm rate and miss alarm rate of the vehicle.