Our Projects

The UK is heavily reliant on private modes of transport. The car offers a type of freedom that other modes of transport don’t: flexibility, privacy, and often an extension of our own identities. The size of the car has increased steadily over the past few decades, meaning they require more resources to build, are more dangerous to pedestrians, and emit more greenhouse gases. The average number of occupants in our car journeys is below two, and most journeys are within cities and towns. Traffic congestion is a norm due to our reliance on the car.

The microcar may offer a solution to many of these issues. These tiny cars are less resource-intensive, easier to drive than average-sized cars, and are also cheaper to buy and run. A city filled with microcars means less congestion and a safer environment for pedestrians. However, the microcar industry is incredibly small, offering few options for consumers. How do we build the demand for microcars, and how can we make them desirable? These are the questions my PhD project will aim to answer.

Faye’s PhD seeks to improve our understanding of how the built environment (such as the transport networks and transport facilities around our homes) influences mental health, and whether this can be explained by active travel behaviour.

There are considerable gaps in knowledge that need addressing, such as uncertainties around which factors in the built environment are particularly important for health. By investigating the role of active travel behaviour in these relationships, this PhD aims to shed more light on why we see frequent associations between the built environment and mental health. 

Faye will also explore these relationships in childhood, and investigate how the built environment (including transport networks and facilities) and travel behaviour shapes child brain development. This is important for understanding why interventions targeted at the built environment and travel choices are not only important for planetary health, but also for population health.

The ever-growing global presence of the electric vehicle is seen as a positive solution to decarbonise the transport industry. As a result, chemists and material scientists are aiming to develop materials that can be used as a backbone for improved electrodes and electrolytes for next-generation batteries and supercapacitors.

Dan's research will focus on the generation of materials that are considered to be part of the next generation of batteries through the use of non-line-of-sight deposition techniques, including chemical vapour deposition (CVD) and atomic layer deposition (ALD). This will provide opportunities to produce current collectors and thin films that are well-defined. Through the methods chosen, the microstructure, morphology and chemistry of the composites can be finely-tuned to overcome potential challenges that battery materials face, such as volume changes during charging and the mechanical, chemical or electrochemical degradation of the electrodes.

Focus will be drawn to potential lithium- or sodium-chalcogenide intercalation or conversion type electrode, or electrolyte materials, such as Lithium sulfides, lithium phosphates and lithium anti-perovskites, and their sodium counterparts.

The initial stages will involve the synthesis of molecules that can be used as precursor material for CVD and ALD, which will then be characterised via a host of methods, including X-ray diffraction, NMR and elemental analysis. The thermal decomposition will be assessed, as will the ability of the precursor to create a thin film. The thin films will be characterised using scanning electron microscopy and will be assessed on its ability as a charge carrier.

The advantages of the chosen techniques (CVD and ALD) will be exploited to improve upon cell performance. These include the ability to deposit uniform layers on a surface which can be used as a protection against chemical degradation, the ability to deposit conformally active materials onto structured backbones, such as nano-tubes, -flakes or -rods. There is also the advantage of high levels of control over stoichiometry of new materials that will be tailored to suit the cell performance by appropriately choosing the precursor materials, changing the deposition parameters and through chemical doping.

Modelling has become critical in recent years for the development of new engine technologies, this is especially important for hydrogen due to its wide range of potential operation. However, modelling hydrogen combustion is particularly challenging due to its wide operating range and complex flame behaviour, including short quenching distances and susceptibility to flame instabilities.

As part of the Prosperity Partnership research group, experimental data will be gathered from a hydrogen engine at IAAPS. Combustion and emissions will be modelled using low-cost 1D simulation tools to generate accurate boundary conditions for more advanced 3D Computational Fluid Dynamics (CFD) simulations. This experimental data will serve to validate both the 1D and 3D models, ensuring their predictive accuracy across a range of operating conditions.

The CFD analysis will enhance understanding of hydrogen combustion and emission formation mechanisms, supporting the optimisation of hydrogen engine development.

Computer vision plays a crucial role in almost all autonomous driving systems and has the potential to be used with traffic management systems of the future. This technology involves the use of cameras and image processing algorithms to interpret and understand the surrounding environment, in the context of automation, allowing the more efficient and accurate management of traffic, automatic crash detection systems, parking management and autonomous driving applications.

In this research project, the primary objective is to enhance the capabilities of computer systems in understanding and predicting the behaviour of vehicles on the road, with the ultimate goal of improving road safety and efficiency. The project will focus on improving the robustness of object tracking by leverage the increased predictability and contextual information of vehicle driving scenarios. Object tracking is the process of observation of vehicles and important information about them, colour, vehicle type, shape, size etc, and the correlation of these properties across video frames in order to associate the same vehicle across an entire video.

The aim is to develop advanced computer algorithms capable of accurately identifying key attributes of vehicles, such as their movements and intentions, in real-time. This understanding of vehicle behaviour will contribute to safer driving scenarios. Additionally, the project seeks to improve existing object tracking algorithms by incorporating contextual information, like lane detection, to enhance trajectory prediction and situational awareness. The involvement of contextual clues specific to automotive situations should allow the algorithms to provide a more robust and reliable result that more generic algorithms.

Sam's project will be completed using a mix of analytical and machine learning algorithms. Where the two different approaches will be compared against each over for speed accuracy and ease of use. In an attempt to find a solution that can both provide usable results in a real-world scenario but also run on systems capable of being deployed.

Dimitry's research focuses on inclusive design for emerging Mobility as a Service (MaaS) systems, targeting neurodivergent populations with Autistic Spectrum Disorder (ASD), Attention Deficit Hyperactivity Disorder (ADHD), Dyslexia, and Dyspraxia. Individuals with these cognitive differences are part of the broader spectrum of neurodiversity and represent an estimated 15% of the global population.

Existing MaaS systems integrate multiple mobility solutions into one platform and involve a complex network of stakeholders. Despite of this complexity, these platforms overlook the unique requirements of users with diverse cognitive profiles. Moreover, these design needs of these demographics are underexplored in academic community across disciplines. This oversight not only impacts user adoption, but also aggravates social inequalities.

In collaboration with multidisciplinary team of experts, and through co-designing with neurodivergent individuals, this research aims to identify unmet needs of target public mobility users, develop system prototypes, conduct empirical testing, and propose tailored design recommendations for inclusive MaaS.

​Cryogenics is a branch of science studying materials that undergoes phase change between -150 and -273 Degrees Celsius. Most popular examples for cryogenic materials are Oxygen,Nitrogen,  Helium and Hydrogen.

Yue's project aims to improve traffic management by studying how economic incentives, such as tolls and subsidies, can reduce congestion and make traffic systems more efficient. Traffic management can be viewed as a resource allocation problem, where limited road space should be used strategically to reduce congestion and help all drivers reach their destinations efficiently.

Typically, drivers will act in their own interests choosing the route they believe will minimise their travel time, which often leads to system inefficiencies. In this project, congestion game models will be used to better understand how individual route choices affect the entire system and how incentives can encourage choices that enhance overall traffic flow and reduce total travel time.

The focus of Jac's thesis is to research the economic realities and financing requirements of efforts to electrify UK bus fleets, with a particular focus on SME operators who may feel more uncertain and less supported by policymakers. By working closely with a small to medium sized UK electric bus operator he hopes to capture the additional complexities and considerations often lost in purely theoretical academic study. Specifically, he will use novel methods and real world data to connect differences in scheduling, vehicle downtime, and financial ratios to their economic cost.

It is his aim that research conducted within this thesis will deliver clear guidance to policymakers and bus operators seeking to decarbonise their fleets, while also encouraging future research to consider the issues raised by his analysis