Assistant Professor Intelligent Vehicles for Safe and Efficient Traffic

These are challenging but exciting times for transport scientists and engineers. There is pressure to reduce the impact of mobility especially regarding car traffic with its associated externalities such as pollution and waste of productive time in congestion. But never as before have transport engineers had such powerful tools and methods at their disposal to increase transport systems efficiency. Information and communication technologies empower vehicles, infrastructure and mobility managers to create safer, more resilient and efficient transport systems.

This tenure track position focuses on decision-making and control methods for intelligent vehicles (automated and cooperative) taking into account the traffic flow and intelligent roadway infrastructure context. Controlling intelligent vehicles with the objective of increasing traffic efficiency and safety requires new models and methods that are able to take decisions in real time. This requires knowledge in control theory, optimization, traffic flow theory, big data and traffic simulation. You will develop research and education in those methods in order to support the development of the next generation cooperative road vehicle systems.  

The research and education that you will perform and coordinate will not only lead to new scientific theoretical and methodological insights, but also to innovative real-world applications and adoption in relevant planning and policy processes. You play a visible role in advising on deployment and valorisation of research findings. In addition to working with traffic and transport data, modelling and simulation approaches, your work will also comprise design and engineering.

You will work at the Department of Transport & Planning in the Electric and Automated Transport Lab (hEAT Lab) and connect to other labs such as the Traffic and Transportation Safety Lab and the Traffic Dynamics Modeling and Control Lab and to other faculties active in this field, such as the faculty of 3ME (Mechanical, Maritime and Materials Engineering).

You will contribute to the BSc and MSc education of CEG, as well as to the education in the interfacultary Master Transport Infrastructure and Logistics (TIL). These contributions pertain to developing and executing courses, in particular the MSc course “Intelligent Vehicles for Safe and Efficient Traffic” and the supervision of Bachelor and Master students.