Treffer: Improvment of Tracking and Merging Algorithms in Metro Car Systems and Simulation With Python ; Metro Car Sistemlerinde Takip ve Birleşme Algoritmalarının İyileştirilmesi ve Python ile Simüle Edilmesi

The increasing number of individual vehicles today complicates the sustainability of urban transportation and heightens the need for more flexible, faster, and environmentally friendly transportation solutions in cities. In this context, the MetroCar System (MCS) has been developed as an innovative transportation model that addresses these requirements. MCS is a multi-agent, dual-mode system equipped with single-seater vehicles that provides speed, safety, and flexibility in urban transportation. This system offers users the convenience of transportation from one point to another, resembling the comfort of personal vehicle use, while also providing the advantage of a safe journey without the need for a driver through autonomous driving technology. Within the scope of this thesis, various improvements have been made to the 'Merging' and 'Tracking' algorithms to ensure that MCS operates more safely and efficiently; these improvements have been tested in a Python-based specialized simulation environment. The results demonstrates that the new algorithms provide a performance increase compared to the existing algorithms of the MCS. Specifically, the system has been enhanced to allow a vehicle tracking another vehicle to not only accelerate or decelerate but also maintain it's speed. Consequently, it has been observed that methods such as low-pass filters or hysteresis, which were previously necessary to dampen the sequential increases and decreases in speed during straight path tracking, are no longer required. In addition, an algorithm different from the existing merging algorithm has been developed, and performance tests have been conducted to compare these algorithms. The results indicate that the new algorithm offers superior performance compared to the existing one. In conclusion, the newly developed algorithms enhance the potential of MCS as a safe, efficient, and sustainable urban transportation solution, demonstrating higher performance relative to the existing algorithms. ; Günümüzde bireysel araç ...