TY - JOUR
T1 - An Improved Vision-Based Lane Departure Warning System under High Speed Driving Condition
AU - Liu, X. T.
AU - Zou, Y.
AU - Guo, H. W.
N1 - Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2019/7/17
Y1 - 2019/7/17
N2 - Recently, Lane departure warning system has attracted great attention as it contributes to vehicle active safety. In this paper, a vision-based lane departure warning system under high-speed driving is proposed. The system consists of two functional parts: lane markings detection and vehicle departure identification. The Hough Transform is applied to detect lane boundaries, which is a most effective detection method with high reliability. Based on the road line, a method using several Euclidean-distance-related parameters to calculate vehicle's position and its deviating status is proposed, which addresses the problem of efficient detection of lane departure under high-speed driving condition. The algorithm is tested and verified in various real driving conditions and proved a reliable and steady performance.
AB - Recently, Lane departure warning system has attracted great attention as it contributes to vehicle active safety. In this paper, a vision-based lane departure warning system under high-speed driving is proposed. The system consists of two functional parts: lane markings detection and vehicle departure identification. The Hough Transform is applied to detect lane boundaries, which is a most effective detection method with high reliability. Based on the road line, a method using several Euclidean-distance-related parameters to calculate vehicle's position and its deviating status is proposed, which addresses the problem of efficient detection of lane departure under high-speed driving condition. The algorithm is tested and verified in various real driving conditions and proved a reliable and steady performance.
UR - http://www.scopus.com/inward/record.url?scp=85069968866&partnerID=8YFLogxK
U2 - 10.1088/1742-6596/1267/1/012053
DO - 10.1088/1742-6596/1267/1/012053
M3 - Conference article
AN - SCOPUS:85069968866
SN - 1742-6588
VL - 1267
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
IS - 1
M1 - 012053
T2 - 2019 3rd International Conference on Artificial Intelligence, Automation and Control Technologies, AIACT 2019
Y2 - 25 April 2019 through 27 April 2019
ER -