Ricerc@Sapienza

The aim of determining fitness to drive is to achieve a balance between minimising any driving-related road safety risks for the individual and the community and maintaining the driver's lifestyle and employment-related mobility independence. Driving a car is a complex and dynamic task and there is a wide range of conditions that temporarily affect the ability to drive safely like consuming substances or fatigue. Professional drivers are particularly affected by fatigue. The main effect of fatigue is a progressive withdrawal of attention from the road and traffic demands leading to impaired driving performance. The particular practice of professional drivers includes working long hours, prolonged night work, working irregular hours, little or poor sleep, and early starting times which in many cases lead to fatigue. Fatigue causes reduced alertness, longer reaction times, memory problems, poorer psychometric coordination, and less efficient information processing. The results of different surveys world-wide show that over 50% of long-haul drivers have at some time almost fallen asleep at the wheel. The project will design, implement and test a new AI-based framework, for the monitoring and evaluation of driving performance, with particular regards to mental fatigue. The system will create neurophysiological models able to detect the onset of abnormal drivers' fitness based on data obtained while driving, in order to potentially trigger on-board intelligence. Artificial Intelligent models will associate different kinds of anomalous behaviour to its most probable cause: fatigue in particular, but potentially also stress, alcohol and drugs effects.
The project impact would be ground-breaking, since AI-DRIVE project by employing forefront data science and neuroscience methodologies will directly tackle road safety concerns.