Project Description

Road freight transportation demand will further increase in the coming years. This leads to challenges for the freight sector such as steadily increasing energy consumption and the coping with limited traffic system capacity. One answer to these challenges is cooperative vehicle platooning. Related state-of-the-art vehicle automation technologies can increase traffic throughput, improve road safety, and reduce fuel consumption.

Control Concept

We developed a holistic distributed control concept to enable tight vehicle spacing and efficient platoon maneuvers with the option of utilizing vehicle-to-vehicle communication while providing collision safety at all times. This innovative platoon control architecture combines trajectory optimization and local model-predictive control of each vehicle.

Trucks send signals to trucks in front to determine an automatic distance

The manoeuvre specific reference trajectories for each platooning vehicle are optimized and communicated by the Platoon Coordinator. Each vehicle is locally controlled by model-predictive control (MPC) that incorporates the information received from the Platoon Coordinator. The MPC law is specifically formulated so that a safe stop in case of a sudden emergency braking maneuver of the preceding car is always possible. Also, communicated predictions and agreements among neighboring platooning vehicles are carefully considered to improve efficiency. The proposed concept remains highly scalable due to its distributed control structure. The local MPC is further enhanced by innovations to reduce safely realizable vehicle spacing and increase communication efficiency.


The proposed control concepts are validated via realistic co-simulations of high-fidelity vehicle dynamics for the exemplary case of truck platooning. Therefore, each individual vehicle is simulated by IPG TruckMaker®, while MATLAB® provides the simulation environment and Simulink® is used as communication interface between the individual vehicle instances. Additionally, a real-time-capable driving simulator was developed to allow human drivers to test the implemented control concepts in a human-in-the-loop setting.

Video Presentation

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Watch our project video on this exciting topic!

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Video Title: Energy-Efficient and Semi-Automated Truck Platooning


Gratzer, Alexander L., Sebastian Thormann, Alexander Schirrer, and Stefan Jakubek. "String Stable and Collision-Safe Model Predictive Platoon Control, opens an external URL in a new window." IEEE Transactions on Intelligent Transportation Systems (2022).

Schirrer, Alexander, Alexander L. Gratzer, Sebastian Thormann, Stefan Jakubek, Matthias Neubauer, and Wolfgang Schildorfer. "Energy-Efficient and Semi-Automated Truck Platooning Research and Evaluation, opens an external URL in a new window." (2022): 237.

Schirrer, A., T. Haniš, M. Klaučo, S. Thormann, M. Hromčík, and S. Jakubek. "Safety-extended explicit MPC for autonomous truck platooning on varying road conditions, opens an external URL in a new window." IFAC-PapersOnLine 53, no. 2 (2020): 14344-14349.

Kalteis, C., S. Thormann, A. Schirrer, and S. Jakubek. "Efficient Methods to Assess Linear and Non-Linear Automotive Platoon Control Stability and Performance, opens an external URL in a new window" In XI international conference on structural dynamics, pp. 748-757. 2020.

Thormann, Sebastian, Alexander Schirrer, and Stefan Jakubek. "Safe and Efficient Cooperative Platooning, opens an external URL in a new window." IEEE Transactions on Intelligent Transportation Systems (2020).

Wasserburger, Alexander, Alexander Schirrer, Nico Didcock, and Christoph Hametner. "A Probability-Based Short-Term Velocity Prediction Method for Energy-Efficient Cruise Control, opens an external URL in a new window." IEEE Transactions on Vehicular Technology 69, no. 12 (2020): 14424-14435.


  • January 2018 - December 2020

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Privatdoz. Dipl.-Ing. Dr.techn. Alexander Schirrer

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