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This abstract deals with the control of truck platoons traveling in freeways. In order to improve their travel performance, in terms of travelling times and comfort and to guarantee safety, a hierarchical control scheme is proposed for each platoon. At the high level, the reference speed is computed according to a PI-based control rule with the main aim of reducing the time spent by the platoon in the congested area. This reference speed is communicated to the low control level which implements a Linear Quadratic Tracking policy and determines the optimal speed for each truck in the platoon. The application of these hierarchical controllers to a case study shows the effectiveness of the proposed scheme.

An optimal-control based path planning algorithm has been developed recently for Connected and Automated Vehicles (CAVs) driving on a lane-free highway, including vehicle nudging. That vehicle movement strategy considers, in the lateral direction, a lateral desired speed that had been set to zero in previous works; in other words, vehicles avoid lateral movement if this is not helpful in achieving some of their goals, e.g. achieving a longitudinal desired speed by overtaking slower vehicles. In this work, a lateral positioning strategy for the vehicles is proposed, aiming to improve the vehicles’ longitudinal speeds and the traffic flow, mainly at intermediate densities, by distributing laterally the vehicles based on their longitudinal desired speeds. The intention is to leverage the existing optimal control formulation to move the CAVs to appropriate lateral positions, while respecting other, higher-priority sub-objectives, such as avoiding crashes. First, the longitudinal desired speed of each vehicle is mapped to a lateral desired position under the premise “faster vehicles drive farther left”. Then, the value of the desired lateral speed is updated in real-time in dependence on the vehicle’s current versus the desired lateral position, letting the optimal control problem, with the given sub-objective priorities, decide on the actual vehicle path. The proposed strategy is demonstrated via traffic simulations, involving various traffic densities, on a ring-road. Several quantities, such as the reached average flows and statistical measures of the error in the lateral position are computed for evaluation and comparison purposes.