Cooperative driving of heterogeneous uncertain nonlinear connected and autonomous vehicles via distributed switching robust PID-like control

In this work, the leading-tracking control problem for heterogeneous and uncertain nonlinear autonomous vehicles is addressed. These latter communicate their status information over a wireless communication network and engage in cooperative movements in extraurban traffic environment. The nonlinear vehicle dynamics are affected by time-varying parameter uncertainties, and the air-drag reduction caused by platooning is explicitly considered. The variation of V2V links as a result of cooperative manoeuvres is modelled by incorporating switching into the communication network topology. To this aim, we develop a novel robust distributed Proportional-Integral-Derivative (PID)-like control protocol which ensures that all vehicles within the platoon robustly track the behaviour of the leader, despite the presence of both unknown parameters uncertainties and network switching. The analytical stability of the proposed control strategy is demonstrated using Lyapunov theory. Sufficient stability conditions are expressed as a set of feasible Linear Matrix Inequalities (LMIs) whose solution allows the robust control gains to be properly tuned. The effectiveness of the approach is evaluated via the Mixed Traffic Simulator (MiTraS) co-simulation platform, which combines MATLAB/Simulink with SUMO microscopic traffic simulator. The exhaustive simulation analysis, involving the Monte Carlo method, is carried out considering different cooperative platooning manoeuvres, and confirms the theoretical derivation.

Automated summary

This work addresses the leading-tracking control problem for heterogeneous and uncertain nonlinear autonomous vehicles. The vehicles communicate their status information over a wireless communication network and engage in cooperative movements in extraurban traffic environment. A novel robust distributed PID-like control protocol is developed to ensure that all vehicles within the platoon robustly track the behavior of the leader, despite uncertainties and network switching. The effectiveness of the approach is evaluated through simulation analysis.