A Study on Parking Space Allocation and Road Edge Detection for Optimizing Road Traffic

Road traffic has been increasing rapidly for the past few decades, which has resulted in air pollution, long waiting times in road traffic, frustration, wastage of effective time on the road etc. The driver's poor vision in identifying road edges, especially during the night, may result in major or minor accidents, which all lead to traffic congestion. Finding a parking space during peak hours also results in congestion. With the emergence of machine learning, IoT, computer vision etc., these problems can be minimised. Road edge detection helps to prevent vehicles that are running off the road and parking space allocation helps to allocate unoccupied space for vehicles even at peak times. The paper addressed a study on different methods through which road edge detection and parking space allocation is possible. This literature survey helps researchers to understand the importance of various cutting edge techniques in road edge detection and parking space allocation. Based on the study, a model is being proposed to provide a solution to edge detection of roads and allocate parking slots, thereby optimising the road traffic.