Research On Adaptive Cruise Control System Based On Driving Characteristics

In today’s era of intelligent vehicle popularization,adaptive cruise control system has become a research hotspot in the field of autonomous driving,at the same time,it is also an indispensable positive force for intelligent network communication environment.Because the driver’s acceptance and satisfaction of this function on the increasing number of intelligent vehicles are poor,and the driver,as the system leading,carries on the most direct dynamic control to the vehicle driving,so it must consider its characteristics and influence.Therefore,it is very important to consider the driver behavior characteristics in the design of adaptive cruise control system.In the research of adaptive cruise control system,the design of personalized adaptive cruise control strategy combined with driving behavior characteristics,and the safety and fuel economy index as the system design requirements are the key to the research of personalized adaptive cruise control system at present.Based on the driving behavior characteristics of real road environment,the control strategy of adaptive cruise control system is designed.On this basis,the main contents of this article are as follows:(1)Modeling of Vehicle Longitudinal Dynamics SystemFirst,the longitudinal vehicle dynamics system model of intelligent vehicle was constructed through CarSim,and then the inverse model of vehicle longitudinal dynamics system was constructed using MATLAB/Simulink.At the same time,the driving and braking system switching criteria were also formulated.After joint verification,the designed model has good Longitudinal dynamic response characteristics.(2)Identify and Analyze Driving Behavior CharacteristicsFirst,conduct a real car test under typical urban road conditions,collect actual driving data of 20 drivers in this scenario,and select key parameters that can reflect the characteristics of driving behavior;then use K-means clustering The algorithm divides three different driving style types;finally,a driving style recognition model is established through BP neural network,and its validity verification is completed.(3)Research on control strategy of personalized adaptive cruise systemAnalyze the behavior data of different driving styles collected by the actual car,select the parameters that reflect the driving behavior characteristics: the following time and the stopping distance of the car,establish different models of the safe distance of the car,and combine different driving style The upper layer control algorithm is designed for the difference in the expected longitudinal acceleration of the vehicle.At the same time,multiple factors such as following and safety are also considered to form a system control algorithm under multi-objective constraints.(4)System Validation and AnalysisThe most typical working conditions in the actual application scenario of the adaptive cruise control function are designed: constant speed cruise mode,carfollowing mode and the front vehicle cycle mode.The joint simulation experiment platform composed of CarSim and Simulink is used to control the system Algorithm to verify.In addition,the decision algorithm of the longitudinal control system under linear quadratic optimal control is compared.It has been verified that the control strategy of the personalized adaptive cruise system designed in this paper conforms to the characteristics of driving behavior and improves the driving comfort and fuel economy of the vehicle.