Multi-obejective Scheduling For Cooperative Driving Of Connected And Automated Vehicles At Non-signalized Intersection

With the tremendous progress and breakthrough in the field of computing,perception,communication,and artificial intelligence technologies in the last decade,it is now an opportunity to explore the next advanced technologies on intelligent transportation system(ITS)and connected and automated vehicles(CAVs).As the most frequent merging and dispersing area of vehicles traveling on traffic network,the intersection has been attracted much attention.It was reported that the increasing economic loss and traffic accidents were intersection congestion related.Thus,one of the most important purposes of the researching and developing ITS is to solve the problem of multi-vehicles cooperating at the intersection area,so as to significantly improve the performance of traffic safety,traffic efficiency,and energy saving,etc.Similarly,one of the expected function of CAVs is controlling themselves crossing the intersection area safely,smoothly,economically,and comfortably based on the shared information of inter-vehicles.For multi-obejective scheduling for cooperative driving of CAVs at intersection,two methods based on Pontryagin's minimum principle(PMP)and Model predictive control(MPC)were proposed in this paper,respectively.In addition,three simulations are conducted to analyze and compare the advantages and disadvantages of the two proposed methods.The main contents and contributions of this paper are as follows.Firstly,the intersection-vehicle model considering multi-constraints is presented.We select the kinematic vehicle model and the dynamic vehicle model to construct the models of CAVs for velocity planning and tracking in the second chapter and in the third chapter,respectively.However,no matter which model is chosen,the functional zone with enough space is set to control the CAVs' velocity and adjust the timing of CAVs to enter the intersection.And the CAVs model is combined with each functional zone to form the intersection-vehicle model.Besides,the six constraints are proposed considering the movements of actual vehicles restricted by safety requirements,actuator saturation,and traffic laws.Secondly,we design the method of scheduling for cooperative driving of CAVs at intersection based on PMP.The four kinds of traffic situations of CAVs driving at the intersection area are described,and the optimal time of CAVs reaching each conflict point is analyzed.On the premise of ensuring safety,the complex problem of multi-CAVs cooperating at multi-conflict points can be converted into the problem of controlling each one to enter intersection at optimal time based on the kinematic relationship.Then,based on the optimal entering time and the PMP,the two optimal modes of velocity controlling are porposed.As results of the simulations,the optimization of CAVs' velocity can theoretically improve traffic efficiency,fuel economy,and ride comfort.Besides,the approaches are proposed to solve the rear-end collision and jerk of the CAVs driving at intersection area.This is the one of contributions in this paper.Thirdly,we also design the method of scheduling and cooperating for CAVs driving at intersection based on MPC.We analyze the collision threats of ego-CAV caused by others CAVs at the intersection area,and design four types of scenarios for safety control.Based on different scenarios,the multi-objective optimization functions of the corresponding model predictive controller is designed to improve the traffic safety,traffic efficiency,fuel economy,and ride comfort of CAVs traveling at the intersection area.Due to the constraints and multi-obejective of CAVs determined by their driving positions,these multi-objective optimization functions mostly need trigger conditions.Moreover,the simulation results show that the based-MPC method can also complete the safety control in sudden scenarios.This is the other contribution in this paper.Finlly,the simulations with unified conditions are conducted to compare the advantages and disadvantages of the two proposed methods.Difference of the methods of cooperative scheduling for CAVs at intersection based on two different theories was studied.Then we unify the environment and constraints of three different velocity simulations to analyze and compare the advantages and disadvantages of the two proposed methods in different performance indices.The simulation results show that the method based on MPC is superior in enhancing vehicle safety,traffic efficiency,and computability,while the method based on PMP has advantages in energy saving,emission reduction,improving ride comfort,and saving computational cost.This also provides ideas for the future study.