Abstract:

Vehicle platooning, as one application of intelligent transportation, has received considerable attention in recent years. The majority of this interest stems from its potential to significantly benefit road transportation, such as improving traffic efficiency, increasing road safety, and lowering fuel consumption. The primary goal of platoon control is to ensure that all vehicles in a group move at the same speed while keeping a predetermined distance between any consecutive followers with vehicle-to-vehicle (V2V) communication technology. In this work, we proposed a distributed model predictive controller for the heterogeneous vehicle platoons subject to disturbances and modelling errors. To reduce or even eliminate the effect of the lumped disturbance, an unknown input proportional multiple-integral (PMI) observer and a tube-based robust method have been adopted in the proposed integrated control strategy. Compared to existing methods, the proposed strategy significantly improves control performance while decreasing computational time.