Sağ Şeritten Kaçınma Fenomeninin Yol Performansı ve Güvenliği Üzerindeki Etkileri: Türkiye'den Bir Vaka Çalışması

Year 2025, Volume: 17 Issue: 2, 432 - 448, 15.07.2025

Erdem Doğan

https://doi.org/10.29137/ijerad.1607621

Abstract

Sürücülerin şerit seçim eğilimleri ve çok şeritli karayollarında araçların şeritler arasındaki dağılımı, yol performansı ve güvenliği üzerinde önemli bir etkiye sahiptir. Bu çalışma, Türkiye'deki çok şeritli karayollarında sıkça gözlemlenen "Sağ Şeritten Kaçınma Fenomeni"ni (RLAP) incelemekte ve bu olgunun yol performansı ve güvenliği üzerindeki etkilerini değerlendirmektedir. RLAP'nin yoğun olarak görüldüğü bir yol kesiminden trafik verileri toplanmış ve kalibre edilmiş bir SUMO (Simulation of Urban Mobility) mikro simülasyon modeli kullanılarak analizler gerçekleştirilmiştir. Performans analizlerinde araç gecikmeleri ve şeritler arasındaki trafik yoğunluğu dağılımı gibi göstergeler, güvenlik analizlerinde ise "Çarpışma Süresine Kalan Zaman" gibi dolaylı güvenlik ölçütleri kullanılmıştır. Sonuçlar, RLAP'nin yol performansı ve güvenliği ciddi şekilde olumsuz etkilediğini göstermektedir. Özellikle, ortalama hızın üzerinde seyahat etmeyi hedefleyen otomobiller ve otobüsler en çok etkilenen araç türleri olarak tespit edilmiştir. Güvenlik açısından, RLAP koşullarında riskli olayların ideal koşullara göre yaklaşık dört kat daha sık gerçekleştiği görülmüştür. Bu çalışma, RLAP'yi çeşitli açılardan ele alarak kapsamlı bir şekilde inceleyen ilk araştırmadır. Bulgular, RLAP'nin olumsuz etkilerini anlamaya yönelik gelecekteki çalışmalar için önemli bir temel oluşturmakta ve bu olgunun önlenmesine yönelik gelişmiş stratejiler için başlangıç noktası sunmaktadır.

Keywords

Şerit Kullanımı , Yol Güvenliği , Çok Şeritli Karayolları , SUMO , Simülasyon , Türkiye

Effects of Rightmost Lane Avoidance Phenomenon on Road Performance and Safety: A Case Study in Türkiye

Abstract

The lane selection tendencies of drivers and vehicle distribution across lanes on multi-lane highways significantly influence road performance and safety. This study investigates the "Rightmost Lane Avoidance Phenomenon" (RLAP), a common traffic behavior on multi-lane highways in Turkey, and evaluates its impact on road efficiency and safety. Traffic data were collected from a highway section where RLAP is prevalent, and analyses were conducted using a calibrated SUMO (Simulation of Urban Mobility) microsimulation model. Key performance indicators included vehicle delays and lane-specific traffic density, while safety was assessed using surrogate safety measures like "Time to Collision." The results reveal that RLAP severely affects road performance and safety, with the phenomenon increasing the risk of safety-critical incidents nearly fourfold compared to ideal conditions. Among vehicle types, passenger cars and buses traveling at higher speeds are disproportionately impacted. This study is the first to comprehensively analyze RLAP, emphasizing its adverse consequences on road networks. Findings provide critical insights into the challenges posed by RLAP and highlight the need for targeted strategies to mitigate its effects. The study lays a foundation for future research aimed at understanding and addressing RLAP, contributing to enhanced traffic management and improved road safety outcomes.

Keywords

Lane utilization , Road safety , Multi-lane highways , SUMO , Simulation , Turkiye

Ethical Statement

Competing interests The author declares no competing interests Author contributions The paper is sole authored.

Thanks

The authors would like to acknowledge the General Directorate of Highways of Turkey for providing the traffic data used in this study

References

• Amundsen, F. H., & Hyden, C. (1977). Proceedings of first workshop on traffic conflicts. Oslo, TTI, Oslo, Norway and LTH Lund, Sweden, 78.
• Duret, A., Ahn, S., & Buisson, C. (2012). Lane flow distribution on a three-lane freeway: General features and the effects of traffic controls. Transportation Research Part C: Emerging Technologies, 24, 157–167. https://doi.org/10.1016/j.trc.2012.02.009
• Fu, Q., Lin, H., & Yang, X. (2006). Study on a phenomenon caused by cars’ lane choice behavior in Chinese freeway. ITST 2006 - 2006 6th International Conference on ITS Telecommunications, Proceedings, 1–4. https://doi.org/10.1109/ITST.2006.288746
• Gao, J., Dai, L., & Gan, X. (2018). Traffic flow and safety analysis. Theoretical and Applied Mechanics Letters, 8(5), 304–314. https://doi.org/https://doi.org/10.1016/j.taml.2018.05.005
• Golias, J., & Tsamboulas, D. (1995). Macrolevel estimation of highway lane usage. Journal of Transportation Engineering, 121(1), 40–49. https://doi.org/10.1061/(ASCE)0733-947X(1995)121:1(40)
• Gunay, B. (2009). Rationality of a non-lane-based car-following theory. Proceedings of the Institution of Civil Engineers: Transport, 162(1), 27–37. https://doi.org/10.1680/tran.2009.162.1.27
• Gunay, Banihan. (2003). Methods to quantify the discipline of lane-based-driving. Traffic Engineering and Control, 44(1), 22–26.
• Gunay, Banihan. (2004). An investigation of lane utilisation on Turkish highways. Transport, 157(1), 43–49. https://doi.org/10.1680/tran.157.1.43.36467
• Habibzadeh, F. (2024). Data Distribution: Normal or Abnormal? Journal of Korean Medical Science, 39(3).
• Heidemann, D. (1994). Distribution of traffic to the individual lanes on multilane unidirectional roadways. PROCEEDINGS OF THE SECOND INTERNATIONAL SYMPOSIUM ON HIGHWAY CAPACITY, VOLUME 1.
• Kim, T. J., & Ferris, J. B. (2024). Adopting the Performance Margin in Horizontal Curve Design. Transportation Research Record: Journal of the Transportation Research Board.
• KRAAY, J. H. (1982). Proceedings of the third international workshop on traffic conflicts techniques.
• Krauß, S. (1998). Microscopic modeling of traffic flow: Investigation of collision free vehicle dynamics.
• Kurle, S., Behara, K. N. S., Prasad, J. R., Arkatkar, S., & Sarkar, A. K. (2016). Study of lane utilization on Delhi-Gurgaon expressway. Transportation Research Procedia, 17, 674–684.
• Lee, J., & Park, B. B. (2011). Determining lane use distributions using basic freeway segment density measures. Journal of Transportation Engineering, 138(2), 210–217. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000313
• Lee, J., & Park, B. B. (2012). Determining lane use distributions using basic freeway segment density measures. Journal of Transportation Engineering, 138(2), 210–217.
• Lee, Y.-C., Wen, F., & Wang, C.-H. (2023). Round-trip driving effects on driving performances and mental workload under different traffic rules. International Journal of Industrial Ergonomics, 95, 103437.
• Lopez, P. A., Behrisch, M., Bieker-Walz, L., Erdmann, J., Flötteröd, Y.-P., Hilbrich, R., Lücken, L., Rummel, J., Wagner, P., & Wießner, E. (2018). Microscopic traffic simulation using sumo. 2018 21st International Conference on Intelligent Transportation Systems (ITSC), 2575–2582.
• Mahalel, D., & Hakkert, A. S. (1983). Traffic arrival patterns on a cross section of a multilane highway. Transportation Research Part A: General, 17(4), 263–270.
• Mahmud, S. M. S., Ferreira, L., Hoque, M. S., & Tavassoli, A. (2019). Micro-simulation modelling for traffic safety: A review and potential application to heterogeneous traffic environment. IATSS Research, 43(1), 27–36.
• Mutlu Aydin, M., & Topal, A. (2016). Effect of road surface deformations on lateral lane utilization and longitudinal driving behaviours. Transport, 31(2), 192–201.
• Paz, A., Molano, V., Martinez, E., Gaviria, C., & Arteaga, C. (2015). Calibration of traffic flow models using a memetic algorithm. Transportation Research Part C: Emerging Technologies, 55, 432–443.
• Pompigna, A., & Rupi, F. (2017). Lane-distribution models and related effects on the capacity for a three-lane freeway section: case study in Italy. Journal of Transportation Engineering, Part A: Systems, 143(10), 5017010.
• Sasahara, F., Staichak Carvalho, L. G., Chowdhury, T. D., Jerome, Z., Elefteriadou, L., & Skabardonis, A. (2020). Predicting lane-by-lane flows and speeds for freeway segments. Transportation Research Record, 2674(9), 1052–1068.
• Shirke, C., Sumanth, N., Arkatkar, S., Bhaskar, A., & Joshi, G. (2019). Modeling expressway lane utilization and lane choice behaviour: a case study on Delhi–Gurgaon Expressway. Transportation Letters, 11(5), 250–263. https://doi.org/10.1080/19427867.2017.1336859
• Transportation Research Board (TRB). (2000). Highway capacity manual.
• Umamaheswari, R., & Avanija, J. (2024). Leveraging high-resolution remote sensing images for vehicle type detection using sparrow search optimization with deep learning. Multimedia Tools and Applications, 1–16.
• Vogel, K. (2003). A comparison of headway and time to collision as safety indicators. Accident Analysis & Prevention, 35(3), 427–433.
• Wu, N. (2005). Impact of traffic regulation on lane flow-distribution and capacity of motorways. The Website Server of the Ruhr University Bochum. Institute for Traffic Engineering, Ruhr University Bochum, Germany.
• Yang, X., & Nie, Y. (2016). Study on the Traffic Flow under Keep-Right-Except-to-Pass Rule Based on Dynamic Model. 2016 3rd International Conference on Information Science and Control Engineering (ICISCE), 664–668.
• Yousif, S., Al-Obaedi, J., & Henson, R. (2013). Drivers’ lane utilization for United Kingdom motorways. Journal of Transportation Engineering, 139(5), 441–447. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000531
• Zhang, H., Guo, Y., Yuan, W., & Li, K. (2023). On the importance of working memory in the driving safety field: a systematic review. Accident Analysis & Prevention, 187, 107071.