Abstract

The study "Road Hypnosis Detection Using Lane Detection" focuses on the phenomenon known as "road hypnosis" or "highway hypnosis," a mental state in which a person can operate a vehicle for extended distances while reacting to outside events as expected, all without recalling that they did so consciously. Long stretches of time spent driving on smooth, featureless highways can cause this syndrome, which lowers awareness and causes a lack of stimulation. The study suggests a novel approach that makes use of lane identification algorithms to identify road hypnosis. It keeps track of the car's location in the lane and the driver's steering movements using sophisticated image processing and machine learning algorithms. Unusualities in these patterns, which could signal the start of road hypnosis, can be detected by the system. This system attempts to improve road safety and avoid accidents caused by decreased driver alertness due to road hypnosis by giving the driver real-time feedback or initiating automatic safety measures. The suggested approach is thoroughly tested and validated throughout the study in a variety of driving situations and conditions, proving its efficacy and suitability for incorporation into contemporary car safety systems. This study addresses a prevalent but frequently disregarded problem that might result in catastrophic accidents, making a substantial contribution to the field of driver safety systems. It also creates new opportunities for utilizing technology to raise driver awareness and enhance general traffic safety.

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