Coordination And Control Of Multiple Connected And Automated Vehicles For Cooperative On-ramps Merging

The highway or urban expressways on-ramps area is the section where traffic conflicts,congestion and accidents occur frequently.Cooperative planning and control of Connected and Automated vehicles(CAVs)is an effective way to mitigate traffic conflict at ramp merge areas.This paper focuses on the cooperative merging control of CAVs.The vehicle trajectory planning with multiple safety constraints and the merging sequence optimization problem are studied in this paper.In addition,an experiment platform of CAV is built and an experimental research on cooperative meging is conducted.This paper aims at inproving the driving safety and traffic efficiency of ramp merge area while reducing vehicle fuel consumption.The specific research work of this paper is presented as following four parts:(1)The merging motion control of CAVs based on PMP(Pontryagin’s Minimum Principle).Following the FIFO(first-in-first-out)merging sequence,a hierarchical control framework based on V2 X for cooperative meging of CAVs is designed.Coordination principles for the CAVs’ arrival time to merging points is proposed to avoid vehicle conflicts.With the aim of improving the fuel economy and ride comfort of CAVs in the merging area,the optimal control problem of cooperative merging with fixed vehicle initial and terminal states is established.And the analytical solution of the optimal merging control problem is given based on PMP.(2)A safe merging trajectory planning method considering vehicle dynamics.Nonlinear vehicle longitudinal dynamics model is developed firstly.When formulating the problem of multi-vehicle cooperative merging control under multiple constraints,safe constraints including vehicle state,control input and safety vehicle distance constraints are considerd.A CLF(Control Lyapunov Function)is designed to convert the vehicle travel time optimization problem into a nonlinear system stabilization problem and a CBF(Control Barrier Function)is designed to transform the multiple safety constraints into control input constraints.Later,the CLF and CBF are brought together to build a QP(Quadratic planning)problem with the goal of minimizing merging time and energy consumption.Finally,a fast solution for the trajectory optimization of CAVs for on-ramps merging is achieved.(3)The merging sequence optimization of CAVs based on dynamic programming.Based on the above merging trajectory optimization method of CAVs,a binary decision variable is introduced to control the right-of-way of main roads and ramps.The number of merging vehicles on the main or ramp road and the current right-of-way are the state varaiable.And the right-of-way of the main or ramp road is control input with the aim of improving traffic efficiency.The merging sequence optimization problem is constructed as MILP(mixed integer linear programming)problem and solved by DP(dynamic programmin)method.The time complexity of the above dynamic programming algorithm is the square of the number of vehicles,and the computational efficiency could meet the real-time computational requirements.(4)CAV experiment platform construction and experimental research on cooperative drving strategy.The hardware and software framework of CAV is built and the cooperative merging experiments based on virtual vehicles is conducted.To demonstrate the stability of the platnoon when the merge is completed,vehicle platoon cooperative driving experiment is conducted based on Leader-follwer communication topology.