Collision Avoidance Systems for Vehicle Safety Using Ultrasonic Distance Sensing Eye Blink Sensor and Alcohol Detector

Abstract

Car wrecks are increasingly seen as a major safety issue; damage and fatality reports from these collisions are frequent. There are also more pedestrians who are killed by automobile accidents in cities and on highways. Additionally, autonomous cars often kill wild creatures that go farther into nature reserves. One cannot put a figure on the cost of a life, yet auto accidents hurt assets. This study looks at the creation and use of a complete collision avoidance system with the goal of improving vehicle safety by using cutting-edge technology. The suggested system includes an alcohol detector to stop accidents caused by intoxicated driving, an eye blink sensor to identify driver weariness, and an ultrasonic distance sensor to enable automated braking and collision avoidance. These sensors are seamlessly integrated to identify possible traffic dangers and initiate necessary reactions, all without depending on driver participation, thanks to the use of Arduino microcontrollers. The system design, methodology, and experimental findings are discussed in the study, which also shows how successful this integrated approach is at reducing road accidents. This study advances the global objective of increasing road safety by democratizing access to cutting-edge safety features that were previously only available in expensive cars.