Vehicle Detection and Lane Keep Assist System for Self-driving Cars

The world's population expansion, along with the rapid increase in the vehicles on road, has resulted in an increase in traffic accidents each year, which has become a major concern. One of the most frequent causes of accident is unintentional lane deviations, which are committed by motorists and result in fatalities, injuries, and financial losses. Vehicle detection has elevated to the forefront of research among specialists in associated fields in recent years due to its social significance. The proposed system aims to create a lane keep assist model that is effective, has the high accuracy, and requires the least amount of processing. It consists of both vehicle and lane detection. Lane detection is achieved with Image Processing Module OpenCV and vehicle detection is developed using Support Vector Machine (SVM). The machine learning model for vehicle detection has been constructed using a data set that includes both vehicles and non-vehicles. The model is evaluated and found to have an accuracy of around 96%.