Traffic accidents have become one of the most serious problems in today's world. Roads are the mostly chosen modes of transportation and provide the finest connections among all modes. Most frequently occurring traffic problem is the negligence of the drivers and it has become more and more serious with the increase of vehicles. Increasing the safety and saving lives of human beings is one of the basic function of Intelligent Transportation System (ITS). Intelligent transportation systems are advanced applications which aim to provide innovative services relating to different modes of transport and traffic management.
What it does
This system enables various users to be better informed and make safer, more coordinated, and smarter use of transport networks.These road accidents can be reduced with the help of road lanes or white markers that assist the driver to identify the road area and non-road area. A lane is a part of the road marked which can be used by a single line of vehicles as to control and guide drivers so that the traffic conflicts can be reduced.
How I built it
Challenges I ran into
Most roads such as highways have at least two lanes, one for traffic in each direction, separated by lane markings. Major highways often have two roadways separated by a median, each with multiple lanes. To detect these road lanes some system must be employed that can help the driver to drive safely.Lane detection is an area of computer vision with applications in autonomous vehicles and driver support systems. Despite the perceived simplicity of finding white markings on a simple road, it can be very difficult to determine lane markings on various types of road.These difficulties can be shadows, occlusion by other vehicles, changes in the road surfaces itself, and different types of lane markings. A lane detection system must be able to detect all manner of markings from roadways and filter them to produce a reliable estimate of the vehicle position relative to the lane. To detect road markings and road boundaries various methodologies are used like Hough Transform, Canny edge detection algorithm, bilateral filter.
Accomplishments that I'm proud of
The lane detection has proved to be an efficient technique to prevent accidents in Intelligent Transportation Systems.The review on lane detection has shown that the most of the researchers has neglected the problem of the fog and noise in images.
What I learned
A lane detection system must be able to detect all manner of markings from roadways and filter them to produce a reliable estimate of the vehicle position relative to the lane. To detect road markings and road boundaries various methodologies are used like Hough Transform, Canny edge detection algorithm, bilateral filter.
What's next for lane_detection_opencv
In near future we will propose a new technique which will integrate the performance of lane detection by using bilateral filter.