Elektronik ve Haberleşme Mühendisliği Bölümü

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/179

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Browsing Elektronik ve Haberleşme Mühendisliği Bölümü by Subject "Akıllı İletim Sistemleri"

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    Citation Count: Saraçoğlu, Kıvanç (2018). Lane keeping control for self-driving vehicles / Sürücüsüz arabalar için şerit koruma kontrolü. Yayımlanmış yüksek lisans tezi. Ankara: Çankaya Üniversitesi Fen Bilimleri Enstitüsü.
    Lane keeping control for self-driving vehicles
    (Çankaya Üniversitesi, 2018) Saraçoğlu, Kıvanç; Çankaya Üniveristesi, Fen Bilimleri Enstitüsü, Elektronik ve Haberleşme Mühendisliği Ana Bilim Dalı
    Intelligent Transportation Systems including Lane Keeping Systems (LKS) aim at providing comfort to drivers, preventing congestion, decreasing gas and CO2 emissions and the number of traffic accidents. LKSs will be widely employed in the automobile industry in the near future as an essential part of modern vehicles including cars, buses and trucks. When realizing a LKS, it is necessary to decide about the required signal measurements and to implement control algorithms that are suitable for different vehicle speeds, road curvatures and can be adapted to different types of vehicles such as passenger vehicles, buses and trucks. The main aim of this thesis is to evaluate and compare different lane keeping algorithms. These lane keeping algorithms are applied to a vehicle model, whose longitudinal motion is decoupled from the lateral motion. Four lane keeping control algorithms are investigated. The first two control algorithms measure the yaw rate and the displacement error at a pre-view distance to compute the necessary rate of change of the steering angle for following a road. The first control algorithms uses a linear controller transfer function, whereas the second control algorithm uses sliding mode control. The third control algorithm also measures the yaw rate and the displacement error at a pre-view distance but directly computes the required steering angle for lane keeping. The fourth control algorithm measures the yaw rate, the heading error and the displacement of the center of gravity (COG). These algorithms are evaluated using simulation experiments with given displacement errors and road profiles. The main outcomes of the thesis are as follows. As the first contribution, the thesis shows that the measurement of the displacement error at a pre-view distance increases the robustness of lane keeping control algorithms. On the downside, since the displacement error at the pre-view distance is controlled, the displacement error at the COG can become large at high velocities. As the second contribution, the thesis concludes that it is beneficial to combine measurements of the yaw rate, the displacement errors at the preview-distance and the COG as well as a prediction of the road curvature to obtain an efficient control algorithm. Such control algorithm is proposed in the thesis and its superior performance is shown by simulation experiments.