Game theoretic approaches for the mathematical control, modelling and optimization of interactions between autonomous vehicles and other road users (EPSRC DTP)

Supervisor(s)

Contact Professor Richard Romano (r.romano@leeds.ac.uk) with any questions about the topic.

Project description

The rapid advance in the development of autonomous vehicle (AV) technology has brought their widespread deployment to the near horizon. As well as their use in personal transportation, small robots such as the Starship have been designed to provide small goods deliveries such as groceries. However, deploying AVs in dense urban areas is a major unresolved challenge, given their need to interact safely and efficiently with regular vehicles, pedestrians and cyclists.

The purpose of the PhD study would be to explore the application of mathematical game theory to represent, understand and design such interactions. Like a game of chess, the AVs need to predict the intentions of other drivers and pedestrians and make manoeuvres that display the AVs intent thereby facilitating smooth interactions and appropriate priority.

Such techniques have been found to be previously useful in designing safe transportation systems (Elvik R, 2014: A review of game-theoretic models of road user behaviour. Accident Analysis & Prevention 62: 388–396). Building on research in the on-going funded projects NOHGV and interAct, and on the expertise of the supervisors in control theory, modelling and optimization of transport systems, the research would involve formulating alternative control systems, mathematical models, implementing and testing them computationally, and devising appropriate optimization/control mechanisms for both the AVs and the infrastructure, in order to ensure safe and efficient movement for all road users.

Depending on the skills and interests of the researcher, different foci are possible for this study, ranging from more theoretical mathematical studies, to a focus on game theory and optimal control or even work supported by empirical evidence from experiments with participants in the University of Leeds driving, cycle and pedestrian simulators.

The student will benefit from conducting this research in the vibrant multi-disciplinary environment of the Institute for Transport Studies at the University of Leeds, a world-leading centre for the study of all aspects of transport systems with a large PhD cohort.

The studentship can combine both analysis and development of automated vehicle systems and human-centred experiments. The experimental work will be conducted in the University of Leeds Driving Simulator or HIKER pedestrian simulator (http://www.uolds.leeds.ac.uk/), some of the most advanced such facilities in the world. The work will build on prior automated vehicle research at the University of Leeds.

Over the last ten years, researchers at the Institute for Transport studies have studied a variety of issues relating to automated vehicles via projects funded by Innovate UK, EPSRC and the EU.

Entry requirements

Applicants should have an appropriate background in engineering, psychology and/or human factors, ideally with some experience of work on game theory, control systems or optimisation methods. A good bachelors degree (first or upper second class or equivalent) is a requirement. A relevant masters qualification is desirable. 

If English is not your first language, you must provide evidence that you meet the University’s minimum English Language requirements.

How to apply

Formal applications for research degree study should be made online through the university's website.

If you require any further information, please contact the Graduate School Office e: phd@its.leeds.ac.uk, or t: +44 (0)113 343 35326.

We welcome scholarship applications from all suitably-qualified candidates, but UK black and minority ethnic (BME) researchers are currently under-represented in our Postgraduate Research community, and we would therefore particularly encourage applications from UK BME candidates. All scholarships will be awarded on the basis of merit.