LANE DETECTION SYSTEM USING APPLICATION OF MACHINE LEARNING

Venkata ravi kiran kolla

Abstract


The annual increase in car ownership has caused traffic safety to become an important factor affecting the development of a city. To a large extent, the frequent occurrence of traffic accidents is caused by subjective reasons related to the driver, such as drunk, fatigue and incorrect driving operations. Smart cars can eliminate these human factors to a certain extent. Lane detection is an important foundation during intelligent vehicle development that directly affects the implementation of driving behaviors. Based on the driving lane, determining an effective driving direction for the smart car, and providing the accurate position of the vehicle in the lane are possible; these features contribute significantly towards improving the efficiency and driving safety of automatic driving. Based on the problems encountered in detecting objects by autonomous vehicles an effort has been made to demonstrate lane detection using OpenCV library.


References


LaneQuest: An accurate and energy-efficient lane detection system- paper Heba Aly; Anas Basalamah; Moustafa Youssef

N. Davy, B. Brabandere, S. Georgoulis, et al., “Towards end-to-end lane detection: an instance segmentation approach,” IEEE Intelligent Vehicles Symposium (IV), pp.286-291,

Wang, X., Qian, Y., Wang, C., & Yang, M. . Map-Enhanced Ego-Lane Detection in the Missing Feature Scenarios. IEEE Access, 8, 107958–107968.

S. P. Narote, P. N. Bhujbal, A. S. Narote, and D. M. Dhane, ‘‘A review of recent advances in lane detection and departure warning system,’’ Patt


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