Highway Lane Detection and Vehicle Monitoring

It is a well-known fact that perception of road (lane) plays a vital role in assisting drivers by using software that can convey them the possible risks in their surroundings. Lane lines are a significant factor of signaling traffic flow. The strategy of this work is to prevent car accidents on highways mainly due to rash driving that consists of sudden lane departure or not keeping up with the lane in case of curved roads. Hence, we propose a method to reduce these crashes by mounting a calibrated camera on the vehicle which will continuously keep track of the view in front of vehicle and deliver certain relevant warnings to the driver in case of any rash driving or fatal situations. Also, it can be helpful for self-driving cars by providing a wide range of possibilities to learn by software and move vehicle on its own in the lane. We employ image processing techniques to detect and solve some of the most prevalent roadway concerns. The problem statement is broken down into basic building blocks to better understand the comprehensive list of potential techniques within this framework. It comes with a decision model that will provide the driver the required cautions.