SMART TRIAL SYSTEM

Abstract

Driving is a common and important mode of transportation in the daily lives of people. It allows people to move freely and independently from one place to another. To drive legally in Nepal, as in most countries, a person requires a driving license, for which he/she has to undergo a series of tests in the government office. In Nepal, a candidate applying for a license has to drive over a fixed path in front of the authorities. The candidate has to complete the test in accordance with specific rules and if he fails to do so he/she will be disqualified. Manually monitoring the errors of the candidates is done by these authorities. Also, the issue of bribery for obtaining a driver’s license is a significant problem in Nepal. To address this issue, we have proposed an AI-based solution named CarSight. CarSight is a Computer Vision model designed to analyze visual data from cameras that verifies whether a driver has passed or failed the driving test. It uses YOLO-v5 to detect and track the motion of the trial vehicles in a set of real-time videos obtained from cameras placed around the model track. The system gives an instant pass or fails result depending on the driver’s performance once they finish the trial exam. The accuracy of detecting and evaluating the driver’s performance was successfully demonstrated by our experimental results for our system. Our proposed system can help to bring fairness in the process of obtaining a driver’s license.