The support of autonomous driving with robust fusion of different lane detection algorithms

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Dr. Orosz György
Department of Measurement and Information Systems

Road lane detection is a fundamental aspect of advanced driver assistant systems (ADAS), at the same time sensor fusion has an increasing importance because of the sharp increase in the number of vehicle-mounted sensors. In this final thesis different ADAS sensors and road lane detection algorithms are mapped. Various aspects of sensor fusion are described, especially in case of advanced driver assistant systems. After the theoretical description, the practical task of this paper is to develop a sensor fusion algorithm of a system which consists of two camera sensors and vehicle odometry, and to test it on real, on-vehicle data. The purpose of the fusion is to increase redundancy and decrease uncertainty. In my final thesis work I evaluate the results of the fusion, make a proposal on further development opportunities, and discuss the method of the generation of ground truth data used by me. The main purpose of this final thesis is to apply the fusion algorithm met in literature in practice, on real measurements.


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