Leicester study compares human hazard perception with AI

Researchers in Leicester’s School of Computing and Mathematical Sciences and Department of Neuroscience, Psychology and Behaviour are collaborating on the study, which will track participants’ eye movements when faced with multiple fast-moving hazards simultaneously.

The research will be used to inform the next generation of a rail safety device being developed as part of an Innovate UK Knowledge Transfer Partnership (KTP) between Leicester experts and systems engineering specialists Synoptix.

Installed at a Network Rail-operated level crossing near Cheltenham earlier this year, the OPTIMUS prototype uses machine learning and an AI-based object detection system, hosted locally on the small edge-based device, to identify and quantify different types of traffic.

Now, the new interdisciplinary aspect will allow researchers to compare the accuracy and speed of its detection capability to a human completing the same task.

George Leete, KTP research associate within the Artificial Intelligence, Data Analytics and Modelling (AIDAM) Centre at Leicester University, is leading development of the project’s machine learning aspect under the supervision of Professor Ivan Tyukin.