Driver recognition system in public transportation: Case study in taxi

This study involves examining and developing the driver recognition system in taxis in the public transportation sector in Istanbul. This developed system aims to increase public transportation safety and service quality by identifying taxi drivers safely and effectively. The main purpose of the thesis is to evaluate the current situation regarding the use of driver recognition systems in taxis operating in Istanbul and to create the Turkish Taxi Driver Identification System by analyzing and developing the impact of these systems in the public transportation sector. In this study, a driver recognition system was developed using facial recognition technologies, biometric data analysis and deep learning algorithms and digital signature technologies. The data obtained was analyzed to evaluate the accuracy and effectiveness of the system. The thesis discusses the advantages and challenges of adopting driver recognition systems in the public transportation sector in Istanbul. In this context, the role of driver recognition systems in improving public transportation safety, their impact on customer experience and their general contributions to the sector are examined. The results of the study emphasize the need to encourage the use of driver recognition systems in the public transportation sector. Keywords: Driver Recognition System, Public Transportation, Taxi, Vehicle Tracking Systems, Face Recognition, Biometric Data Analysis, Deep Learning, Digital Signature Technologies