Future transport: TRL's top 10 research projects

Research topics to be pursued by TRL during the coming year have been revealed in the company's latest quartely report, pointing to the future direction of transport technology in the UK.

The list of the 10 research projects has been drawn up by the TRL Academy and includes research to be funded with support from TRL's parent company, the not-for-profit Transport Research Foundation.

The quartely research report, available here, gives an update on projects already under way, together with those continuining and starting anew – offering a glimpse into the themes considered to be most important for overcoming transport challenges to come.

Announcing the report and research list, TRL Academy director, Nick Reed, said: “It is an honour to be part of a process which helps to drive the future of transport. Choosing the projects that will go on to shape policy, design and technological development is always a challenge but we apply key criteria around ensuring the research is relevant, disruptive and deliverable. More than that, it is about providing the TRL team with the opportunity to follow their ideas – no matter how left field – in a structured and strategic way."

The TRL Academy top 10 projects:

Cybersecurity and the Internet of Things – The Internet of Things (IoT) is the broad concept of linking objects (including those in the transport domain). Although in its infancy, it is expected to have a profound effect on transport and mobility. Cybersecurity is already critical as transport becomes more connected, so cybersecurity in the IoT world encapsulates an important intersection of issues that will be explored.

Machine Learning – Computer science project to explore application of Machine Learning to transport data. Enabling a dynamic and self-learning approach, artificial intelligence of this nature has the potential for significant efficiency and performance improvements, to optimise the transport network.

Mental Health – an increasingly important area of interest across many sectors, yet little consideration has been given to the relationship between transport and mental health. This research project will understand the ways in which transport systems can impact and improve mental health, providing the basis for future interventions and countermeasures that will improve the mental health of road and rail users.

Truck Platooning – While a lot of this new technology is focusing on the automation of cars, the automation of heavy goods vehicles (HGVs) is gathering pace. This project will explore the implications of this type of automation on transport network infrastructure.

Wireless Mesh Sensor Networks – The asset management technology review project (FY15/16) identified Wireless Sensor Mesh Networks (WSMN) as a promising ‘smart infrastructure’ technology. This project will understand the feasibility and opportunity for WSMN for asset management applications.

Automated Vehicles – exploring how occupant protection characteristics of vehicles may need to evolve in order to provide passengers with an acceptable level of impact protection in this new era of vehicle design.

Head Injuries – considering a state-of-the-art approach to head injury assessments and its potential applications for collision investigations.

Virtual Reality – This project builds on last year’s 3D capture and visualisation research. Taking TRL’s virtual reality experience further, the project will explore the application of this technology to support a range of complex transport related scenarios.

Driving Simulation – working in partnership with other simulator facilities to establish the protocols for shared simulated driving studies, which may be vital for extending research on connected and automated vehicle operation.

Data Science – TRL will continue its work on data science in transport scenarios. This project will explore the application of data science techniques to identify and solve complex transport issues. The project forms the basis of TRL’s connection to the Strategic Alliance Programme at CSAIL – MIT’s Computer Science and Artificial Intelligence Laboratory.