INSIGHT
Full title: Impairment Navigation through Systematic Investigation & Glance Habit Tracking
The INSIGHT project aims to enhance road safety by developing a sophisticated system to detect driver impairment in real-time. The issue addressed is the real-time detection of impaired driving ability, which is expected to lead to a reduction in accidents, injuries, and fatalities on the road. By leveraging advanced data analytics and behavioural science, INSIGHT seeks to mitigate these risks, contributing to safer, more reliable, and intuitive automotive technologies. The primary goal of the INSIGHT project is to create a predictive model that uses real driving data, including glance behaviour, to identify patterns of normal driving and detect deviations indicative of impaired driving ability. This system is expected to serve as a crucial component for improving road safety by subsequently providing early warnings or interventions when potential impairments are detected. For example, it could warn the driver and, if there is no response, then slow down the car with the hazard lights activated. The utility of this project extends across several dimensions, including enhancing driver awareness, aiding in the development of safer automotive technologies, and supporting regulatory bodies in formulating data-driven policies for road safety.
Traffic safety benefit: INSIGHT aims to improve traffic safety through a system that detects impaired driving in real-time using data analysis of multi-modal data. The goal is a predictive model that, based on real driving data, such as gaze behavior, identifies deviations and warns the driver.
Key words: driver impairment, glance behaviour, driver awareness, real-time, data analytics
