Gendered Innovation Living Labs (GILL)

GILL will be implemented through an iterative co-creation approach structured on a four-phases cycle - understand, co-design, implement, evaluate - repeated twice to incorporate the feedbacks and evaluation results in fine-tuned and validated results.


Air-One: Designing and developing the 'world's smallest airport'

Within the Air-One project we will implement the first UKs first ‘pop up’ airport and charging hub for future electric Vertical Take-Off and Landing (eVTOL) aircraft .


Midlands Future Mobility

IFTC’s role in MFM supports future CAV testbed trials by developing guidance and case studies to assist users with test definition and planning.


ASSURED CAV Parking

The ASSURED CAV (Connected and Autonomous Vehicle) Parking project’s purpose is to create a bespoke and realistic, controlled set of parking environments to test and support the development of current and future connected and automated parking solutions.


SIMUSAFE (SIMUlator of behavioural aspects for SAFEr transport)

The goal of SIMUSAFE following the FESTA-V model methodology is to develop realistic multi-agent behavioural models in a transit environment where researchers will be able to monitor and introduce changes in every aspect, gathering data not available in real world conditions.


REducing WorkloAd Through EffiCient TechnOlogy and ProceduRes - REACTOR

The objective of the REACTOR project is to develop and evaluate a suite of technologies in support of reduced cockpit workload and improved situational awareness.


AREA – Augmented Reality Enhanced Assembly

This explored the use of augmented reality in the context of manufacturing assembly workers required to conduct complex product assemblies (such as high performance battery packs for electric vehicles) with increased efficiency.


Understanding user trust after software malfunctions and cyber intrusions of digital displays: A use case of automated automotive systems

This research investigates the cyber security, human factors and trust aspects of screen failures during automated driving.


PACE-AI: The Pedestrian Collision Forensics Evaluator from Coventry University

Our PACE-AI method is only using vehicle shape and pedestrian anthropometry. It can extract, in seconds, not only the vehicle impact speed (which takes the Police days), but also the pedestrian crossing speed, gait and crossing direction (impossible using Searle).