Transport Innovation Gender Observatory (TInnGO)

TInnGO, the Transport Research Observatory, is a pan European observatory for gender smart transport innovation, that provides a nexus for data collection, analysis, dissemination of gender mainstreaming tools and open innovation, encouraging smart mobility.


Gyrodrive Original Equipment Development

In this project, Coventry University has joined with GKN Hybrid Power, GKN AutoStructures, S&S Windings and Alexander Dennis Limited, to develop a Gyrodrive system solution that will be optimised for fitment to buses as original equipment.


UK Connected Intelligent Transport Environment (UK CITE)

The overall project aim is to create one of the world’s most advanced environments for connected and autonomous driving.


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 .


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.


Supporting Urban Integrated Transport Systems (SUITS)

SUITS is one of the three projects of the EU’s CIVITAS 2020 initiative focusing on sustainable urban mobility plans.


Multi-Area Connected Automated Mobility (MACAM)

The Multi-Area Connected Automated Mobility (MACAM) project is a collaborative initiative. It encompasses a multi-city, multi-operator, and multi-purpose self-driving trial. 


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.


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).