Visibility of Lane Markings for Machine Vision

Assessment of Lane Detection Performance based on Different Lane Marking Properties under Optimal and Adverse Weather and Lighting Conditions

Master thesis (2021)

Authors

E. van der Kooij Civil Engineering & Geosciences

Contributors

B. van Arem Transport and Planning - CEG (supervisor 1)
H. Farah Transport and Planning - CEG (supervisor 2)
R. Happee Intelligent Vehicles - Mechanical, Maritime and Materials Engineering (supervisor 2)
Y. Dong Transport and Planning - CEG (supervisor 2)
Anastasia Tsapi Royal HaskoningDHV (supervisor 2)
Peter Morsink Royal HaskoningDHV (supervisor 2)
Faculty
Civil Engineering & Geosciences
Copyright: © 2021 Eline van der Kooij
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Published Date

28-06-2021

Language

English

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Faculty

Civil Engineering & Geosciences

Abstract

Advanced Driver Assistance Systems (ADAS) are becoming more available and will become mandatory for all new vehicle models from 2022 onward. In order to achieve the highest safety benefits, it is important that these systems are available. Lane Keep Assist (LKA) is part of ADAS and assists the driver in the lateral control of the vehicle. Lane markings are used by both human drivers and machine vision to stay on the road, but factors contributing to lane marking detection in different driving conditions are mostly unknown. A field test was conducted on Dutch provincial roads to evaluate lane marking visibility properties in relation to the LKA detection performance of different sensor types. The LKA detection performance of the mono camera was found to be higher in most weather and illumination conditions than the detection performance of the mono camera with infrared. The mono camera with infrared had a higher detection performance during rain in nighttime conditions than during dry daytime conditions. The highest detection performance for the mono camera and the mono camera with infrared were 97% in dry nighttime conditions and 91,4% in sunset conditions, respectively. Binary logistic regression was used to determine the effect of lane marking properties on the lane detection performance. A profiled lane marking type was found to increase the detection likelihood by 6-8 times as opposed to a smooth lane marking type. Other visibility properties, such as retroreflectivity and contrast with the road surface, were not found to be a significant contributor to the detection performance.