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Keynote Lectures

Cooperative Automated Driving: From Platooning to Maneuvering
Jeroen Ploeg, 2getthere B.V., Utrecht and Eindhoven University of Technology (The Netherlands ), Netherlands

Traffic Control Schemes for Sustainable Freeway Networks: State of the Art and Future Challenges
Simona Sacone, University of Genova, Italy


Cooperative Automated Driving: From Platooning to Maneuvering

Jeroen Ploeg
2getthere B.V., Utrecht and Eindhoven University of Technology (The Netherlands )

Brief Bio

Jeroen Ploeg received the M.Sc. degree in mechanical engineering from Delft University of Technology, Delft, The Netherlands, in 1988 and the Ph.D. degree in mechanical engineering on the control of vehicle platoons from Eindhoven University of Technology, Eindhoven, The Netherlands, in 2014.

He is currently with 2getthere, Utrecht, The Netherlands, were he leads the research and development activities in the field of cooperative automated driving for automated transit systems, in particular platooning. Since 2017, he also holds the position of part-time Associate Professor with the Mechanical Engineering Department, Eindhoven University of Technology, Eindhoven, The Netherlands. From 1989 to 1999, he was with Tata Steel, IJmuiden, The Netherlands, where his interest was in the development and implementation of dynamic process control systems for large-scale industrial plants. He was with TNO, Helmond, The Netherlands, from 1999 until 2017, ultimately as a Principal Scientist in the field of vehicle automation and road safety assessment.

His research interests include control system design for cooperative and automated vehicles, in particular string stability of vehicle platoons, the design of interaction protocols for complex driving scenarios, and motion control of wheeled mobile robots.


Autonomous vehicles do not intrinsically improve traffic since they optimize towards reaching their own goals. Cooperative driving, on the other hand, aims for optimizing the collective behavior, thus having the potential to improve the traffic system. Connectivity is instrumental for cooperative driving because traffic participants can express and share their intention more easily and precisely. When combined with vehicle automation, a powerful approach arises for improving traffic efficiency and safety.

A well-known application of cooperative automated driving (CAD) is cooperative adaptive cruise control (CACC) or platooning, which improves traffic throughput by adopting very short intervehicle distances. This is particularly of interest in automated transit systems (people movers) which, when used for first-/last-mile transportation, must have a high transport capacity. Also truck platooning is a promising application because fuel consumption decreases due to reduced aerodynamic drag at short distances. To fully exploit these potential benefits, a platoon needs to be string stable, which refers to attenuation of the effects of disturbances in upstream direction along the platoon. String stability contributes to safety, but it is only a necessary condition, not a sufficient one. To also guarantee safety in the presence of failing communication or common threats such as cutting in of other vehicles, additional measures are required which are only addressed in literature to a limited extent.

Next to ongoing developments in the field of platooning, cooperative automated maneuvering attracts attention to an increasing extent, acknowledging the fact that traffic is not a one-dimensional string of vehicles. Many approaches are still investigated in this field. One such approach relies on explicit decision making, employing so-called interaction protocols; This approach was illustrated by i-GAME, a European-funded project, whereas other projects, such as Autonet2030, adopt an optimization-based approach for path planning.

In summary, CACC and platooning are promising first applications of CAD, but further research and development in the field of safety is required, especially when considering the current world-wide standardization and road approval activities. At the same time, the application domain is extended towards cooperative automated maneuvering, ultimately leading to a truly ‘automated intelligent transportation system’.



Traffic Control Schemes for Sustainable Freeway Networks: State of the Art and Future Challenges

Simona Sacone
University of Genova

Brief Bio

Simona Sacone is Associate Professor of Automatic Control at the Department of Informatics, Bioengineering, Robotics and Systems Engineering of the University of Genova in Italy, where she teaches Systems Theory, Identification and Estimation Techniques, and Optimization and Control of Logistic Systems and where she acts as the coordinator of the PhD Course on Systems Engineering.

Her research activity is devoted to optimization and control of complex physical processes by means of discrete-event and hybrid modelling and control approaches. The main application fields are freeway traffic control and logistic networks planning. About these themes, she has authored and co-authored one book (A. Ferrara, S. Siri, S. Sacone, “Freeway Traffic Modelling and Control”, Advances in Industrial Control Series, Springer, 2018), and more than 120 papers published on international journals, international books and international conference proceedings.

Presently she serves as Associate Editor for the IEEE Transactions on Intelligent Transportation Systems and for the IEEE Control Systems Magazine.

She is the Chair of the Technical Committee on “Planning and Control of Transportation and Logistic Networks” of the IEEE Intelligent Transportation Systems Society. Since 2019 she is Member of the Board of Governors of the IEEE Intelligent Transportation Systems Society.


The design and development of mobility and traffic systems meeting the needs of present citizens and future generations, is experiencing nowadays an increasing attention to sustainability issues. Various definitions of sustainability have been provided, all agreeing about the necessity of strengthening actions now that do not neglect the possible negative externalities that may occur in the long period.

The lecture will present traffic control strategies for freeway networks aimed at improving the overall sustainability of such systems. This means that the proposed traffic management and control strategies are designed not only for maximally exploiting the road capacity and preventing congestion phenomena, but also for reducing pollutant emissions, fuel consumptions, and accidents. This, in turn, is also tied to the possibility of improving safety on freeway traffic systems.

Starting from simple feedback strategies and going towards more complex predictive controllers, several regulation schemes for freeway networks have been conceived and will be presented. These schemes are defined with the aim of optimizing objective functions considering traffic related performance, emissions reduction and safety improvement. The proposed control schemes are, then, based on multi-objective optimization in which several, possibly conflicting, cost functions, are present and explicitly analyzed. Moreover, all the considered controllers have a multi-class nature, meaning that different classes of vehicles are explicitly considered and dedicated control actions are determined for each class.  For each of the proposed controllers, an experimental analysis will also be described with the aim of comparing the obtained results in the considered multi-objective framework.

Finally, the main present and future research challenges for freeway traffic modelling and control will also be discussed. Specifically, it is now necessary to include in traffic control schemes, the innovation brought by the emerging information and communication technologies, changing the concept of vehicles in intelligent and connected agents, able to measure the traffic state and to implement specific traffic control policies. Some insights and new ideas about the way in which connected and automated vehicles can be considered and exploited in traffic control schemes will also be provided.