jitsa Akıllı Ulaşım Sistemleri ve Uygulamaları Dergisi 2636-820X 2636-820X Bandirma Onyedi Eylul University 10.51513/jitsa.1520267 Public Transport Toplu Taşıma Sürücü ihlal analizi: İETT örneği Driver violation analysis: IETT example https://orcid.org/0009-0004-9190-7560 Kaya Gizem https://orcid.org/0000-0002-1724-2925 Demirci Ebru İSTANBUL ÜNİVERSİTESİ https://orcid.org/0000-0002-9770-9838 Doğaner Duman Bükra ISTANBUL UNIVERSITY 03 25 2025 8 1 22 38 07 22 2024 02 10 2025 Copyright © 2018, Journal of Intelligent Transportation Systems and Applications 2018 Journal of Intelligent Transportation Systems and Applications

Bu makale, toplu taşıma güvenliğinin artırılmasında sürücü davranış analizinin önemini tartışmaktadır. Özellikle İstanbul'da otobüs, metrobüs, Beyoğlu nostaljik tramvayı ve Karaköy tünel füniküler sistemi dahil olmak üzere çok sayıda kamu aracını işleten İstanbul Büyükşehir Belediyesi İstanbul Elektrik Tramvay ve Tünel İşletmeleri Genel Müdürlüğü (İETT) örneğine odaklanmaktadır. Makale, İETT'nin sürüş davranışını analiz etmek için kullandığı GPS veri analizi, otobüs telemetri veri analizi ve sürücü davranışı veri analizi gibi çeşitli teknolojileri vurgulamaktadır. Ayrıca, İETT tarafından ihlalleri tespit etmek için kullanılan bir sürücü hareket analiz sisteminden elde edilen sürücü ihlal verilerinin bir analizini de sunmaktadır. Veriler, en çok ihlal edilen kuralın emniyet kemeri takma olduğunu, bunu dikkat dağınıklığı, uyuşukluk ve diğer ihlallerin izlediğini göstermektedir. Makale, sürücü davranışı verilerinin analiz edilmesinin, sürücü davranışının iyileştirilebileceği alanların belirlenmesine, kaza riskinin azaltılmasına ve genel güvenliğin iyileştirilmesine yardımcı olabileceğini öne sürmektedir.

This article discusses the importance of driver behavior analysis in improving public transportation safety. It specifically focuses on the case of Istanbul Metropolitan Municipality Istanbul Electricity Tram and Tunnel Operations General Directorate (IETT), which operates a large number of public vehicles in Istanbul, including buses, Metrobus, Beyoglu nostalgic tram, and Karakoy tunnel funicular system. The article highlights various technologies IETT uses to analyze driving behavior, such as GPS data analysis, bus telemetry data analysis, and driver behavior data analysis. It also presents an analysis of driver violation data obtained from a driver motion analysis system used by IETT to detect violations. The data shows that the most violated rule is seat belt fastening, followed by distraction, drowsiness, and other violations. The article suggests that analyzing driver behavior data can help identify areas where driver behavior can be improved, reduce the risk of accidents, and improve overall safety.

 Driver violation Driving behavior Driver motion analysis urban transportation Sürücü ihlali Sürüş davranışı Sürücü hareket analizi kentsel ulaşım Adhikari, B. (2023). Using Visual and Vehicular Sensors for Driver Behavior Analysis: A Survey. arXiv preprint arXiv:2308.13406. Retrieved from https://arxiv.org/abs/2308.13406 Ahmed, S., Uddin, M. S., Feroz, S. I., Alam, M. R. B., Farabi, F. A., Uddin, M. M., & Rifaat, S. M. (2023, January). The tendency of intra-city bus drivers to use a cell phone while driving using ordered probit model. Int AIP Conference Proceedings (Vol. 2643, No. 1, p. 030007). AIP Publishing LLC. Caird, J. K., Willness, C. R., Steel, P., & Scialfa, C. (2008). A meta-analysis of the effects of cell phones on driver performance. Accident Analysis & Prevention, 40(4), 1282-1293. D’souza, K. A., & Maheshwari, S. K. (2015). A methodological approach for studying public bus transit driver distraction. International Journal of Sustainable Development and Planning, 10(2), 229-244. De Waard, D., & Brookhuis, K. A. (1996). The measurement of drivers' mental workload. Donmez, B., Boyle, L. N., Lee, J. D., & McGehee, D. V. (2006). Drivers’ attitudes toward imperfect distraction mitigation strategies. Transportation research part F: traffic psychology and behavior, 9(6), 387-398. El hafidy, A., Rachad, T., Idri, A., & Zellou, A. (2021). Gamified Mobile Applications for Improving Driving Behavior: A Systematic Mapping Study. Mobile Information Systems, 2021, 1-24. Farah, H., Polus, A., Bekhor, S., & Toledo, T. (2007). Study of passing gap acceptance behavior using a driving simulator. Advances in Transportation Studies an International Journal, 9-16. Hamarat, B., & Duran, S. (2020). Factors Influencing Aggressive Driving Behaviors: A Case Study from Çanakkale Province. Journal of Awareness, 5(4), 503–514. Hansen, J. H., Busso, C., Zheng, Y., & Sathyanarayana, A. (2017). Driver modeling for detection and assessment of driver distraction: Examples from the UTDrive test bed. IEEE Signal Processing Magazine, 34(4), 130-142. Helvaci, S., Senova, A., Kar, G., & Gören, S. (2018). Improving driver behavior using gamification. In Mobile Web and Intelligent Information Systems: 15th International Conference, MobiWIS 2018, Barcelona, Spain, August 6-8, 2018, Proceedings 15 (pp. 193-204). Springer International Publishing. Horrey, W. J., & Wickens, C. D. (2006). Examining the impact of cell phone conversations on driving using meta-analytic techniques. Human factors, 48(1), 196-205. Ishigami, Y., & Klein, R. M. (2009). Is a hands-free phone safer than a handheld phone? Journal of safety research, 40(2), 157-164. Kaptein, N. A., Theeuwes, J., & Van Der Horst, R. (1996). Driving simulator validity: Some considerations. Transportation research record, 1550(1), 30-36. Khosravinia, P., Perumal, T., & Zarrin, J. (2023). Enhancing Road Safety through Accurate Detection of Hazardous Driving Behaviors with Graph Convolutional Recurrent Networks. arXiv preprint arXiv:2305.05670. Li, N., Jain, J. J., & Busso, C. (2013). Modeling of driver behavior in real-world scenarios using multiple noninvasive sensors. IEEE transactions on multimedia, 15(5), 1213-1225. Liang, Y., Reyes, M. L., & Lee, J. D. (2007). Real-time detection of driver cognitive distraction using support vector machines. IEEE transactions on intelligent transportation systems, 8(2), 340-350. Liu, Y., & Hansen, J. (2019). Analysis of Driving Performance Based on Driver Experience and Vehicle Familiarity. SAE International Journal of Transportation Safety, 7(2), 175-190. Mahajan, K., Velaga, N. R., Kumar, A., & Choudhary, P. (2019). Effects of driver sleepiness and fatigue on violations among truck drivers in India. International journal of injury control and safety promotion, 26(4), 412-422. Masello, L., Castignani, G., Sheehan, B., Guillén, M., & Murphy, F. (2023). Using contextual data to predict risky driving events: A novel methodology from explainable artificial intelligence. Accident Analysis & Prevention, 184, 106997. Nilsson, H., Mullaart, M., Strand, N., & Eriksson, A. (2021). The effects of information relevancy on driving behavior: A simulator study on professional bus drivers. Cognition, Technology & Work, 23, 429-437. Paas, F. G., & Van Merriënboer, J. J. (1993). The efficiency of instructional conditions: An approach to combine mental effort and performance measures. Human factors, 35(4), 737-743. Papantoniou, P., Antoniou, C., Pavlou, D., Papadimitriou, E., Yannis, G., & Golias, J. (2017). Exploratory analysis of the effect of distraction on driving behavior through a driving simulator experiment. International Journal Transportation, 5, 35-46. Porwik, P., Orczyk, T., & Doroz, R. (2022, December). A Stable Method for Detecting Driver Maneuvers Using a Rule Classifier. In Intelligent Information and Database Systems: 14th Asian Conference, ACIIDS 2022, Ho ChiMinh City, Vietnam, November 28–30, 2022, Proceedings, Part I (pp. 156-165). Cham: Springer International Publishing. Rakauskas, M. E., Gugerty, L. J., & Ward, N. J. (2004). Effects of naturalistic cell phone conversations on driving performance. Journal of safety research, 35(4), 453-464. Sathyanarayana, A., Boyraz, P., & Hansen, J. H. (2014). Effects of multitasking on drivability through can-bus analysis. Smart Mobile In-Vehicle Systems: Next Generation Advancements, 169-182. Shaaban, K., Gaweesh, S., & Ahmed, M. M. (2018). Characteristics and mitigation strategies for cell phone use while driving among young drivers in Qatar. Journal of Transport & Health, 8, 6-14. Strayer, D. L., Drews, F. A., & Johnston, W. A. (2003). Cell phone-induced failures of visual attention during simulated driving. Journal of experimental psychology: Applied, 9(1), 23. Terzi, R. (2019). Big Data-Based Driver Behavior and Driving Models for Fleet and Public Transportation Vehicles (Doctoral dissertation). Gazi University, Institute of Science. Trafik Hizmetleri Başkanlığı. (n.d.). The Role of Driver Behaviors in Accident Risk: Violations, Errors, and Inattentiveness. Trafik Hizmetleri Başkanlığı Publications. Retrieved from https://www.trafik.gov.tr/ Verwey, W. B. (2000). On-line driver workload estimation. Effects of road situation and age on secondary task measures. Ergonomics, 43(2), 187-209. Wang, L., Wang, Y., Shi, L., & Xu, H. (2022). Analysis of risky driving behaviors among bus drivers in China: The role of enterprise management, external environment and attitudes towards traffic safety. Accident Analysis & Prevention, 168, 106589.