Skip to main content

Human Factors

Human Factors research primarily lies in applying a scientifically rigorous, mixed methods approach to understanding users’ interactions with technology, systems or services within simulated and real-world environments. Put simply, we aim to better understand how people interact with technology, and how this can lead to the design of better end products. One such application, which is the current focus of much of our research, surrounds Connected and Autonomous Vehicles (CAV - connected to the internet or other road users, and/or self-driving). CAV is an emerging field of research, both from a technological perspective (e.g. sensor fusion, Swarm Intelligence etc.) but also in terms of our social understanding (e.g. trust in automation, public acceptance etc.).

Our research interests and capabilities include:

  • User evaluations: Evaluating how people use technology is one of the cornerstones of our work within Human Factors. This can be completed in a simulated environment (i.e. using our 3xD Simulator) or real-world studies. By understanding how people interact with and react to the technology, we can make informed decisions about design.
  • Driver state monitoring: Understanding the current state of the driver by assessing physiology, biometrics, emotions and eye glance behaviours. By understanding this, we aim to infer in real-time aspects such as trust or engagement in technology. Another application is providing adaptive information to the driver via interface designs, or assessing the competence of the driver to 'takeover' from automation.
  • Understanding driver behaviour and performance: Even as we move towards fully autonomous vehicles, understanding driver behaviour is central to Human Factors research. Examples of this include designing effective multi-modal warnings for automated vehicle warnings and handover requests, or understanding users' knowledge requirements during different modes of driving. With the 3xD Simulator we have a unique facility for conducting truly driver-in-the-loop evaluations.
  • Requirements capture: Understanding user requirements is a key factor for the development of a successful system or interface. Novel, mixed methods are used to capture what people want and subsequently convert these user requirements into system functional specifications. This is essential for all applications, but its importance is often overlooked.
  • Public engagement: We regularly engage with the public, both to capture requirements through focus groups, but also to disseminate our research to a wider audience, including non-expert end users.
  • Electric vehicles: This area of research focuses on how people use and interact with Electric Vehicles (EVs), by understanding how driver behaviour can influence range of an EV and subsequent range anxiety, to parking behaviours to support Wireless Electric Vehicle Charging, and the design of EV charging points for usability.

  • Outside of Automotive: Within Human Factors we have conducted numerous research projects outside of the Automotive domain. Research includes design recommendations and user evaluations for an Intelligent Train seat reservation system, both for a customer facing app, but also the crew back end system, and human factors for military applications.


WiCET - Wireless Charging for Electric Taxis

Funder: Innovate UK
Partners: Cenex, IHI Europe Limited, Parking Energy Limited, Nottingham City Council, Transport for London

RACeD - Research for Advanced Concept Development; WMG / JLR EngD Programme

Funder: Jaguar Land Rover

SWARM - Self-organising Wide area Autonomous vehicle Real-time Marshalling
Funder: Innovate UK
Partners: RDM Group, Milton Keynes Council
LSAT User Evaluations

Funder: JLR, under subcontract via the UK Autodrive project (Innovate UK)

CloseR - Customer Loyalty and Seat Reservation for Intelligent Trains
Funder: Innovate UK
Partners: UniPart Rail, Train FX, Loyalty Prime, First Group, Cranfield University


Associate Professor, Human Factors
Professor of Experiential Engineering
Research Fellow (HVM Catapult)
Research Fellow (HVM Catapult)
Research Fellow (SWARM)
Ran Dong
Research Fellow (SWARM)
Claudia Geitner
EngD Candidate (Multi-modal interfaces)
Vadim Melnicuk
EngD Candidate (Driver State Monitoring)
Arun Ulahannan
EngD Candidate (HMI for autonomous vehicles)
Joe Smyth
EngD Candidate (Motion Sickness)
Jaume Perelló March
PhD Candidate (Biometrics and Trust)
Redho Kurnia
PhD Candidate (Interaction in partially automated vehicles)


See this link for a full list of the Human Factors in Intelligent Vehicles publications, or to the right for recent publications.


Alongside project delivery we strive to be at the forefront of our teaching activities, with the Human Factors team leading and contributing to Undergraduate, Postgraduate and Professional programme teaching. This includes leading the School of Engineering 4th Year module, Design for Vehicle Comfort, and contributing significantly to WMGs new MSc in Smart, Connected and Autonomous Vehicles (SCAV) for the core module of Human Technology Interaction.

Academic Lead

Dr Stewart Birrell

Dr Stewart Birrell




Recent Journal Publications

Oliveira L, Fox C, Birrell S and Cain R. 2019. Analysing passengers’ behaviours when boarding trains to improve rail infrastructure and technology. Robotics and Computer-Integrated Manufacturing, 57, 282-291.

Geitner C, Birrell S, Krehl C and Jennings P. 2018. A haptic pedal assistant system: Influence of shoe type, age, and gender on the perception of haptic pulses. Human Factors, 60, 496-509.

Khastgir S, Birrell S, Dhadyalla G and Jennings P. 2018. Calibrating Trust through Knowledge: Introducing the Concept of Informed Safety for Automation in Vehicles. Transportation Research Part C: Emerging Technologies, 96, 290-303.