| Adaptive Cruise Control(ACC)is an important auxiliary driving system for intelligent vehicles.In recent years,with the development of the field of intelligent connected information,how to carry out intelligent cruise control in a dynamic connected environment has become a research hotspot.To achieve comfort,economy,and road utilization of intelligent cruise vehicles during driving.This article establishes a safety distance model with dynamic adjustment of the minimum safety distance,which takes into account the influence of front vehicle speed and road adhesion coefficient on safety distance.Based on the Model Predictive Control(MPC)theoretical framework,driving comfort and energy economy are fully considered,and an intelligent cruise control system for vehicles based on dynamic network information is designed.The main research content is as follows:Firstly,a hierarchical control strategy for intelligent cruise control of automobiles was designed.The main idea is that the upper acceleration optimization controller achieves cruise and following modes.In following mode,maintaining a reasonable safety distance from the vehicle in front not only ensures the safety of the vehicle during driving,but also improves traffic efficiency.Therefore,this article designs an improved safety distance model,On the basis of the traditional model for calculating the safety distance between fixed vehicle heads,two safety distance models are switched based on the relative speed of the two vehicles.The improved safety distance model considers the effects of the speed of the preceding vehicle and road adhesion on the safety distance.This article establishes an inverse longitudinal dynamic model to convert the expected acceleration into throttle opening and brake master cylinder pressure,and verifies the rationality of the lower level acceleration tracking controller by inputting three typical acceleration signal lights.Furthermore,based on the MPC control theory,design the upper acceleration optimization controller for the intelligent cruise control system.Firstly,according to the state information of the car and the front car,the longitudinal kinematics model of the two cars is established to reflect the actual movement relationship of the two cars;Then,in response to the insufficient consideration of comfort and economy in the design of the current adaptive cruise control system,this paper optimizes and solves the comfort and economy indicators as MPC constraints;Finally,simulation experiments were conducted to verify the advantages of the improved safety distance model adopted in this article in road utilization,as well as the tracking effect of the intelligent cruise control system in real scenarios,achieving the safety,comfort,and economy of intelligent cruise vehicles.Finally,in an intelligent network environment,in order to further reduce the energy consumption of intelligent cruise vehicles passing through signal intersections,an intelligent energy-saving cruise controller design was designed that considers signal timing and front vehicle information.By building a dynamic networking simulation environment,the communication between vehicle to vehicle(V2V)and vehicle to transport infrastructure(V2I)is realized.Firstly,considering the signal lights and information of the vehicle in front obtained in advance,target speed planning was carried out to avoid vehicles stopping and waiting at red lights;Then,based on MPC,an intelligent energy-saving cruise controller is designed,with the driving speed and displacement of the vehicle as state variables,and the target speed,safe distance from the vehicle in front,and economy as optimization objectives.The driving torque and braking force are optimized to achieve control of the vehicle;Finally,the effectiveness of the intelligent energy-saving cruise control system designed in this paper was verified by designing two simulation scenarios: single vehicle scenario with a single signal light and two vehicle scenario with multiple signal lights. |
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