Research On Adaptive Cruise Control Algorithm Considering Road Conditions

With the rapid development and progress of computer,electronics,communication and automotive electronic control technology,intelligent automobile and cc driving technology have gradually become a new direction of automobile industry development.As an important part of the development of automated driving technology,Advanced Driver Assistance System(ADAS)has great application prospects and research value.As one of the important ADAS systems,the purpose of Adaptive Cruise Control(ACC)system is to realize the longitudinal control of vehicle,reduce drivers'labor intensity,and improve the safety,comfort and economy of vehicles.China's road traffic environment is complicated.Urban traffic flow is large,driving speed is low,and there is a risk of congestion.In addition,due to the limitation of geographical environment,road forms such as slope road and curve road occupy a large proportion in China's highway traffic network.However,the traditional ACC is only suitable for simple traffic conditions such as expressways,and it is difficult to deal with complex and changeable traffic and road conditions.In urban roads,the complex and changeable traffic environment causes frequent start and stop of vehicles.In slope road environment,the fluctuation of road causes the rapid rise of fuel consumption level of vehicles,and vehicles'economy is significantly reduced.However,the traditional cruise control strategy cann't effectively use the terrain to optimize the fuel economy of vehicles.In curve road environment,the target loss of radar causes unreasonable acceleration/deceleration of vehicles,which reduce the comfort and safety of vehicles.In addition,when vehicles enter the low adhesion curves or small radius curves such as the ring road,excessive speed will lead to vehicle sideslip.All of these have become factors to reduce the performance of ACC.Therefore,optimization and design ACC control strategy for different road conditions has grown up to be an important research direction.Combining the National Key R&D Project"Test and Evaluation Technology of Auto-Driving Electric Vehicle"and the School-Enterprise Cooperation Project"ADAS Simulation Platform Algorithms Development and Scene Verification",the relevant research about“Adaptive Cruise Control Algorithm Considering Road Conditions”has been carried out.This thesis mainly includes the following aspects:1)An adaptive cruise control system architecture with multi-condition adaptability is proposed.The functional requirements and research objectives of the system are analyzed,and the strategy of condition selection considering road conditions and driving tasks is put forward.Based on the hierarchical controller structure,the design of ACC controller is completed through two layers:planning decision layer and actuator control layer.In the design of planning decision layer,speed control mode and distance control mode are realized by using PID algorithm,and the mode switching strategy between speed control and distance control is designed.In the design of actuator control layer,the longitudinal control function of vehicle is realized based on the inverse model of driving system,the inverse model of braking system and the switching strategy between driving control and braking control.2)Research on eco-cruise control strategy for slope road based on dynamic programming theory(DP).Firstly,based on DP theory,vehicle's eco-cruise control problem is converted into a multistage decision problem.Secondly,system's state transition equation is established,the constraints and disturbances of the system are analyzed,and the optimization objective of system is established.Therefore,the problem of economic speed programming is realized.Finally,based on the fuel consumption model of vehicle engine,the cost matrix of system is solved and the abstract network model of system is established.Based on the abstract network model,the optimal vehicle speed is extracted by Dijstra algorithm,and the eco-cruise control of vehicle is realized.3)The optimization of ACC strategy under the curve road condition.Based on the relationship of vehicles'motion,the rule of sub working condition partition for curved road is proposed.On this basis,the algorithm of distance compensation for curve road and the mechanism of radar failure compensation are proposed.In the following mode,a curve radius prediction algorithm based on preceding vehicle trajectory fitting is proposed,which is based on the identification of pre-vehicle's active steering kinestate.In cruise mode,based on the identification of host vehicle's active steering kinestate,a curve radius prediction algorithm based on steering wheel angle information is proposed.Finally,the lateral safety control strategy of vehicle passing through curve road is proposed,based on the prediction algorithm of curve radius.4)Test Verification and Result Analysis.Based on dSPACE/ASM~?virtual simulation platform and driver in the loop test bench,the ACC,the eco-cruise control strategy for slope road and the optimization of control strategy for curve road,proposed in this article,are simulated and tested.Secondly,on the basis of intelligent vehicle experimental platform,the actual vehicle test of ACC system and curve radius prediction algorithm,proposed in this thesis,is completed.The simulation and test results show that the ACC architecture and optimization algorithm,proposed in this thesis,have good applicability in different road conditions.The economy of system under slope road conditions and the safety of system under bend conditions are improved.