Preventive Driver Analysis System for Highway Hypnosis

A Real-Time, Personalized, and Retrofittable Approach via Computer Vision

Abstract

The core research question of this study was to develop and evaluate an in-car driving safety system aimed at detecting and preventing highway hypnosis, a trance-like state that can endanger drivers. The methodology involved a combination of expert consultation, surveys, and engineering design. Initially, experts in advanced driving techniques were consulted to identify the key indicators of highway hypnosis, such as blink rate, eye openness, and head and body movements. This input, combined with survey results, led to the development of an algorithm designed to monitor these indicators via cameras integrated into the vehicle, using a Raspberry Pi platform.

During the engineering phase, the optimal placement of cameras within the vehicle was determined using 3D design software, ensuring the system's effectiveness. Testing the prototype revealed that the system successfully detected early signs of highway hypnosis and triggered appropriate warnings, thereby potentially preventing accidents.

The study concluded that the developed system could play a significant role in reducing traffic accidents and enhancing road safety by addressing a previously underexplored aspect of driver behavior. The findings suggest that implementing such systems in vehicles could be a vital step toward safer driving conditions, particularly on monotonous highways where the risk of highway hypnosis is higher. Further implications include the potential adaptation of the system for use in autonomous vehicles, where driver attention remains crucial.