http://hdl.handle.net/20.500.12416/20 Mekatronik Mühendisliği yayınlarını içerir. 2026-10-28T16:55:25Z http://hdl.handle.net/20.500.12416/8436 Controller Design for CACC with Time-varying Communication Delays Bingöl, Hilal; Soysal, Gökhan; Schmidt, Klaus Werner Cooperative Adaptive Cruise Control (CACC) aims at the safe and comfortable travel of vehicles at short distances in the form of platoons. Hereby, it is generally desired to attenuate disturbances along vehicles in a platoon, which is captured by different string stability conditions. In this paper, we focus on L∞ string stability. This condition ensures reducing the magnitude of the acceleration signal along the platoon, which helps to avoid actuator saturation and increases driving comfort. Since the performance of CACC is adversely affected by timevarying communication and actuator delays, we develop the first controller design method for L∞-string stability, combining the Lyapunov-Krasovskii method and our custom bisection algorithm. Simulation experiments demonstrate the effectiveness of our method. 2023-01-01T00:00:00Z http://hdl.handle.net/20.500.12416/8435 Comprehensive Comparison of Various Machine Learning Algorithms for RF Fingerprints Classification Gündoğan, Boran; Ergezer, Halit In these days, the use of drones has become quite common. Remote controls can do the control of these drones with RF signals. It is important to prevent security vulnerabilities caused by using drones in our daily lives. A complex dataset was created by extracting the characteristics of the RF signals and preprocessing them. To solve this complex data set and problem, the application of models including Support Vector Machine (SVM), Random Forest, Decision Tree, Gradient Boosting, XGBoost and Neural Network (NN) models, including various ML models and comparison of optimization studies of these applied models are examined in this article. In addition, a wide range of studies was carried out to compare ML models, including comparison metrics such as Accuracy, Precision, Recall, Mean Squared Error (MSE), F1 Score, $R^{2}$ and Training Time. In line with these results, the highest score was obtained in the $\mathrm{R}^{2}$ comparison metric (97%) in the Neural Network (NN). Compared to the others, the results of Neural Network (NN) were more successful, but the Training Time (245 sec) in the Neural Network (NN) method is by far more than the other ML methods, which shows us that the NN method requires a very high computing process. As a result of the comparison, another outstanding Ensemble-based ML method is Decision Tree. This is because besides the very low Training Time $(5\sec)$, it has managed to be the 2nd ML algorithm with the highest $\mathrm{R}^{2}$ score (96%). Apart from these, among other ML methods, SVM performed slightly less well $(\mathrm{R}^{2}$ 91%) in solving this complex problem. The advanced Gradient Method (95%) and XGBoost (96%), which also have the Ensemble structure, showed a head-to-head performance regarding $\mathrm{R}^{2}$ scores. However, XGBoost (30 sec) has a very short Training Time compared to Gradient Boosting (180 sec). As a result, the approach of each ML method to solving the complex problem differed from each other, and the success rates and Training Time also differed equally. The most important work to be done here is to choose which ML method you want to achieve according to the limited system in hand and the performance-accuracy dilemma. 2023-01-01T00:00:00Z http://hdl.handle.net/20.500.12416/7934 String Stability Under Actuator Saturation on Straight Level Roads: Sufficient Conditions and Optimal Trajectory Generation Bingol, Hilal; Schmidt, Klaus Werner The heterogeneity of vehicles is an important factor when realizing cooperative adaptive cruise control (CACC) in practice. Specifically, it has to be considered that platoons generally consist of vehicles with both different dynamic properties and actuator limits on the engine and braking force, which is expected to have a negative impact on important properties such as string stability. Accordingly, the subject of this paper is the preservation of string stability for CACC in heterogeneous vehicle strings with potential actuator saturation. To this end, the paper formulates a velocity-dependent force bound that enables the derivation of sufficient conditions for preserving string stability during velocity changes of heterogeneous platoons. These conditions are then used for the analytical computation of trajectories for time-optimal velocity changes. The formal results of the paper are supported by an illustrative simulation study. 2022-12-01T00:00:00Z http://hdl.handle.net/20.500.12416/7908 Eyleyici doyumu altında dizi kararlı kooperatif otomatik seyir kontrolü Bingöl, Hilal; Çankaya, Erkam; Schmıdt, Klaus Werner Kooperatif otomatik seyir kontrolü (CACC), araçtan araca haberleşme yöntemiyle veri iletilmesini ve uzaklık ölçümlerine göre yoğun trafikte güvenilir araç takibinin yapılmasını sağlar. Kullanılan CACC dizaynları dizi kararlılığının temel özelliklerini sorunsuz bir şekilde yerine getirirken doğrusal araç modelleri için sınırlıdır. Bu makalede ise, doğrusal olmayan araç modeli kullanıldığında ve lider araca uygulanan giriş sinyali doyuma uğramadığında dizi kararlılığının korunabildiği gösterilmiştir. 2016-01-01T00:00:00Z