A Seminar on “Automotive Engineering and Autonomous Vehicles” Held at the Department of Automotive Engineering
17.03.2026
On March 13, 2026, a seminar titled “Automotive Engineering and Autonomous Vehicles” was organized by the Department of Automotive Engineering. As part of the event, Automotive Engineer Şeyma Uygur met with students and shared insights from her academic research and professional experience in the rapidly evolving field of autonomous vehicle technologies. Uygur completed her master’s degree at Gazi University, where she focused on research related to intelligent vehicle systems.
During the presentation, the current technological level reached in automotive engineering was examined through the perspective of autonomous driving systems. The fundamental components of autonomous vehicles—including sensing technologies, environmental perception systems, and artificial intelligence–based decision mechanisms—were discussed in detail. In addition, the working principles of driverless systems were explained and the potential impact of autonomous vehicles on traffic safety, driving comfort, and transportation efficiency was highlighted.
As part of the event, the speaker also introduced her master’s thesis completed at the Graduate School of Natural and Applied Sciences at Gazi University, titled “Development of a Reinforcement Learning-Based Lane Change Algorithm for Autonomous Vehicles.” In this study, a decision-making algorithm enabling autonomous vehicles to perform safe and efficient lane-changing maneuvers was developed. The research employed a Deep Q Network (DQN)–based reinforcement learning approach for decision-making, while path planning and path tracking processes were modeled and tested in the MATLAB/Simulink environment under various traffic scenarios.
In the later part of the talk, the role of artificial intelligence and machine learning methods in the development of autonomous vehicle technologies was discussed. Particular emphasis was placed on reinforcement learning techniques and their advantages in enabling vehicles to make adaptive and safe decisions in complex traffic environments. The presentation also addressed how intelligent algorithms can analyze environmental data and support autonomous vehicles in making reliable real-time driving decisions.
At the end of the event, students had the opportunity to ask questions regarding autonomous vehicle technologies, artificial intelligence–based control systems, and ongoing academic research in this field. The event attracted significant interest from students and provided a valuable platform for academic exchange, contributing to a broader understanding of emerging technologies shaping the future of automotive engineering.
