Crowd sourced traffic control strategies

About the Project

Supervisory Team: Prof. Ben Waterson and Dr Ioannis Kaparias

About the project

This project will create a simulated road environment game, to understand how people prioritise different road users, and train the next generation of artificial intelligence based control algorithms to make traffic lights operate the way that people want them to.

The algorithms that control traffic lights are effective at maintaining safety while maximising the number of vehicles that can pass through road junctions, responding to real time variation in approaching traffic. But common control approaches fundamentally assume that all approaching objects are the same. But should we give more (or less) priority to Cyclists? Pedestrians? Buses? Heavy goods vehicles? Driverless cars? Electric cars? Cars with more people in them? Expensive cars?

It is widely considered that existing algorithms fail to sufficiently account for the increasing heterogeneity of objects using road junctions and therefore do not appear to operate in ways that those road users expect. This project therefore first seeks to understand how the general public want traffic lights to work through developing a traffic control simulation app to crowd sources preferences and operating strategies. This data will then be used to calibrate new control algorithms based on peoples’ preferences and contrast these with existing approaches to understand the impacts on delays of providing more socially acceptable systems.

Entry requirements

You must have a UK 2:1 honours degree, or its international equivalent.

Strong computer programming skills are essential.

Experience in mobile app development and machine learning algorithms is desirable.

Fees and funding

Full scholarships include tuition fees, a tax-free stipend at the UKRI rate for up to 3.5 years (totalling £20,780 for 2025/26, rising annually). UK, EU and Horizon Europe students are eligible for scholarships. Chinese Scholarship Council funded students are eligible for fee waivers. Funding for other international applicants is very limited and highly competitive. Overseas students who have secured or are seeking external funding are welcome to apply.

How to apply

Apply now

You need to:

• choose programme type (Research), 2026/27, Faculty of Engineering and Physical Sciences
• select Full time or Part time
• search for programme PhD Engineering & the Environment (7175)
• add name of the supervisor in section 2 of the application

Applications should include:

• your CV (resumé)
• 2 academic references
• degree transcripts and certificates to date
• English language qualification (if applicable)