Automated vehicle platooning bears high potential to increase traffic efficiency, improve road safety, and reduce fuel consumption. To realize platoons with small inter-vehicle distances, collision safety is the most crucial concern and needs to be considered carefully. Moreover, it is desired to attenuate disturbances along the platoon which is known as string stability. While model predictive control concepts achieve efficient, situation-aware, and safe platooning, establishing string stability properties is difficult. In this work string stability is characterized for a generic feedback setting. A workflow to design an extended time gap spacing policy is proposed for a safety-extended distributed model predictive platooning controller. It provides safe, tightly-packed platoon operation with robust string stability near steady-state even without vehicleto-vehicle-V2V-communication. Platoon performance is further improved by exploiting V2V-communication. Finally, the resulting closed-loop platoon dynamics are validated in a high-fidelity co-simulation study.

In the original version of the Chapter 5 (Truck Platoon Slipstream Effects Assessment) and Chapter 6 (Validation of Truck Platoon Slipstream Effects), the author “Dr. Christoph Irrenfried” name was not included as a co-author. This has now been rectified and the author’s name has been included.The chapters and the book have been updated with the changes.

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Cooperative platoon control strategies utilise provided information from vehicle-to-everything (V2X) communication to reduce energy consumption and improve traffic flow and safety. In this chapter, a distributed control concept for cooperative platooning is developed that combines trajectory optimisation and local model-predictive control of each vehicle. The presented control architecture ensures collision safety by design, platoon efficiency and situational awareness with the option of exploiting V2X communication. The resulting platoon control performance is tested and validated in a realistic setting by utilising a co-simulation-based validation framework with detailed vehicle dynamics.