A Novel Constrained Car-Following Control System for Autonomous Vehicles With Only Relative Distance and Angle Measurements

This paper proposes a novel coordinated car-following controller for two connected Ackermann steering vehicles subjected to actuator saturation, model uncertainties, limited filed-of-view, limited sensing and communication ranges, without velocity measurements, without collision between vehicles, and with path curvature compensation. To comply with the controller design, relative constrained distance and angle between vehicles are transformed into an efficient Euler-Lagrange formulation in terms of unconstrained errors. Then, two new sets of nonlinear filtered error variables are devised to propose a novel saturated proportional-integral-derivative observer-based control scheme which takes the advantages of the amplitude-limited PID control structure. The unknown model parameters and external disturbances are compensated via an operational combination of an adaptive robust control (ARC) scheme and a neural network (NN). The controller stability is proved by Lyapunov's direct method. Comparative simulation results will show the main benefits of the proposed control system.