VISSIM-Based Smart Traffic Signal Control at Intersections: The Case of Ankara

Yıl 2025, Cilt: 13 Sayı: 4, 1476 - 1493, 31.12.2025

Cenk Fidan , Ebru Arıkan Öztürk

https://doi.org/10.29109/gujsc.1686955

Öz

The rapid increase in urban population, along with the rising number of private vehicles and their usage, has significantly elevated the demand for urban mobility. This increased mobility, particularly at signalized intersections, has brought challenges such as traffic congestion, delays, waiting times, traffic accidents, and environmental pollution. Fluctuations in traffic flow during the day often lead to unnecessary delays, fuel consumption, time losses, and occasionally traffic rule violations at fixed-time controlled intersections. Traffic-responsive systems, an application of Intelligent Transportation Systems (ITS), are widely used today as they assign signal timings based on real-time traffic data, minimizing delays and enhancing intersection performance. This study aims to demonstrate the benefits of operating four intersections with different geometries in Yenimahalle, Ankara, as traffic-responsive (smart) intersections. The VISSIM software was utilized to compare intersection performances. Simulations were conducted for morning peak hours by inputting the previous and proposed states of the selected intersections into the program. Improvements achieved were identified by comparing the current and optimized scenarios. The findings revealed that managing these intersections as smart intersections would result in significant improvements in delay times, queue lengths, and fuel consumption.

Anahtar Kelimeler

Intelligent Transportation Systems , Smart intersection , VISSIM

VISSIM Simülasyonuna Dayalı Akıllı Kavşak Sinyal Kontrolü: Ankara Örneği

Öz

Günümüzde, kentsel alanlarda yaşayan nüfusun hızla artması, bununla birlikte özel araç sayısı ve araç kullanımındaki artış, kentsel hareketlilik talebini artırmıştır. Bu hareketlilik, özellikle sinyalize kavşaklarda; trafik sıkışıklığı, gecikme ve beklemeler, trafik kazaları ve çevresel kirlilik gibi problemleri beraberinde getirmektedir. Gün içerisinde trafik akımındaki dalgalanmalar, sabit zamanlı olarak yönetilen kavşaklarda gereksiz beklemelere, yakıt sarfiyatına, zaman kayıplarına, hatta zaman zaman sürücülerin kural ihlallerine neden olabilmektedir. Bir Akıllı Ulaşım Sistemi uygulaması olan trafik uyarmalı sistemler, gerçek zamanlı trafik değerlerine göre süre ataması yaptıkları için, gecikmeleri minimuma indiren ve kavşak performansını artıran, günümüzde yaygın olarak kullanılan sistemlerdir. Bu çalışmada, Ankara Yenimahalle ilçesinde yer alan ve farklı geometriye sahip dört kavşağın, trafik uyarmalı (akıllı kavşak) olarak çalıştırılması durumunda, sağlanacak faydaların ortaya konulması amaçlanmaktadır. Çalışmada, kavşak performanslarının karşılaştırılabilmesi için VISSIM programı kullanılmıştır. Belirlenen kavşakların önceki ve sonraki durumları programa girilerek sabah zirve saatleri için simülasyonlar gerçekleştirilmiş, mevcut durum ve yeni durum karşılaştırması yapılarak meydana gelen iyileşmeler tespit edilmiştir. İncelenen kavşakların akıllı kavşak olarak yönetilmeleri durumunda; gecikme süreleri, kuyruk uzunlukları ve yakıt tüketiminde önemli iyileşmeler sağlayacağı tespit edilmiştir.

Anahtar Kelimeler

Akıllı Ulaşım Sistemleri , Akıllı Kavşak , VISSIM

Etik Beyan

Bu makalenin yazarları çalışmalarında kullandıkları materyal ve yöntemlerin etik kurul izni ve/veya yasal-özel bir izin gerektirmediğini beyan ederler.

Destekleyen Kurum

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Teşekkür

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Kaynakça

• [1] Anadolu Ajansı. Erişim tarihi: 15.01.2025. https://www.aa.com.tr/tr/dunya/dunya-nufusu-2030da-8-6-milyara-ulasacak/858027
• [2] Lee W.H., ve Chiu C.Y. (2020). Design and implementation of a smart traffic signal control system for smart city applications. Sensors, 20(2), 508. https://doi.org/10.3390/s20020508
• [3] Akıllı Ulaşım Sistemleri (AUS) Değerlendirme Endeksi Geliştirme AR-GE Projesi Sonuç Raporu (2018). Akıllı Ulaşım Sistemleri Derneği (AUSDER). https://austurkiye.org.tr/uploads/blog/file_25-aus-degerlendirme-endeksi-gelistirme-ar-ge-projesi-sonuc-raporu-915.pdf
• [4] Çapali B. (2009). Akıllı Ulaşım Sistemleri ve Türkiye’deki uygulamaları. Yüksek Lisans Tezi, Süleyman Demirel Üniversitesi, Fen Bilimleri Enstitüsü.
• [5] Li Y., Hao H., Gibbons R., Medina A. (2021). Understanding gap acceptance behavior at unsignalized Intersections using naturalistic driving study data. Transportation Research Record, 2675(9), 1345-1358. https://doi.org/10.1177/036119812110071
• [6] Xu B., Li S.E., Bian Y., Li S., Ban X.J., Wang J., Li K. (2018). Distributed conflict-free cooperation for multiple connected vehicles at unsignalized intersections. Transportation Research Part C: Emerging Technologies, 93, 322-334. https://doi.org/10.1016/j.trc.2018.06.004
• [7] Zhou J., Shen Z., Wang X., Wang L. (2024). Unsignalized Intersection Management Strategy for Mixed Autonomy Traffic Streams. Electrical Engineering and Systems Science, https://doi.org/10.48550/arXiv.2204.03499
• [8] Xiao G., Liu K., Sun N., Zhang Y. (2024). Game-Based Vehicle Strategy Equalization Algorithm for Unsignalized Intersections. World Electric Vehicle Journal, 15(4), 146. https://doi.org/10.3390/wevj15040146
• [9] Shi Y., Liu Y., Qi Y., Han Q. (2022). A Control Method with Reinforcement Learning for Urban Un-Signalized Intersection in Hybrid Traffic Environment. Sensors, 22(3), 779. https://doi.org/10.3390/s22030779
• [10] Chen J, Sugumaran V, Qu P. (2022). Connected and automated vehicle control at unsignalized intersection based on deep reinforcement learning in vehicle-to-infrastructure environment. International Journal of Distributed Sensor Networks, 18(7). https://doi.org/10.1177/155013292211140
• [11] Szűcs H., Szűcs J. (2024). The Environmental Sustainability Potential of Autonomous Vehicles: An Overview. Periodica Polytechnica Transportation Engineering, 52(3), 246–256. https://doi.org/10.3311/PPtr.23933
• [12] Guériau, M., & Dusparic, I. (2020). Quantifying the impact of connected and autonomous vehicles on traffic efficiency and safety in mixed traffic. IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC), Rhodes, Greece. DOI: 10.1109/ITSC45102.2020.9294174.
• [13] Ye, L., Yamamoto, T. (2019). Evaluating the impact of connected and autonomous vehicles on traffic safety. Physica A: Statistical Mechanics and its Applications, 526, 121009. https://doi.org/10.1016/j.physa.2019.04.245
• [14] SAE (Society of Automobile Engineers). (2021). SAE Levels of Driving Automation. https://www.sae.org/blog/sae-j3016-update
• [15] Al-Sharman M., Edes L., Sun B., Jayakumar V., Daoud M.A., Rayside D., Melek W. (2023). Autonomous Driving at Unsignalized Intersections: A Review of Decision-Making Challenges and Reinforcement Learning-Based Solutions. Computer Science, Robotics. https://doi.org/10.48550/arXiv.2409.13144
• [16] Zhuang H., Lei C., Chen Y., Tan X. (2023). Cooperative Decision-Making for Mixed Traffic at an Unsignalized Intersection Based on Multi-Agent Reinforcement Learning. Applied Sciences, 13(8), 5018. https://doi.org/10.3390/app13085018
• [17] Chen X., Sun Y., Ou Y., Zheng X., Wang Z. and Li M.(2020). A Conflict Decision Model Based on Game Theory for Intelligent Vehicles at Urban Unsignalized Intersections. IEEE Access, 8, 189546-189555. DOI: 10.1109/ACCESS.2020.3031674
• [18] Hızarcı S., Tanyel S., Dündar S., Gökaşar I., Şengöz B., Topal A. (2023). Işıksız Kavşaklarda Kritik Aralık Kabulü İçin Yeni Bir Yaklaşım. Turkish Journal of Civil Engineering, 34(4), 105-132. https://doi.org/10.18400/tjce.1314559
• [19] Rachakonda Y., & Pawar D.S. (2023). Evaluation of intersection conflict warning system at unsignalized intersections: A review. Journal of Traffic and Transportation Engineering, 10 (4), 530-547. https://doi.org/10.1016/j.jtte.2023.04.003
• [20] Balaban, S. & Arıkan Öztürk E. (2022). Tam Trafik Uyarmalı Sinyalizasyon Sisteminde Gecikme Sağlayan İyileşmeler. Kent Akademisi, 15(2), 564-577. https://doi.org/10.35674/kent.1058968
• [21] Gülsün, B., & Gonca, C. K. (2019). Adaptif trafik yönetim sistemleri. OHS Academy, 2(1), 32-40.
• [22] Xu H., Zhang K., Zhang D. Zheng Q. (2022) Traffic-Responsive Control Technique for Fully-Actuated Coordinated Signals. IEEE Transactions on Intelligent Transportation Systems, 23(6), 5460-5469. DOI: 10.1109/TITS.2021.3054054.
• [23] US-DOT (U.S. Department of Transportation). (2008). Traffic Signal Timing Manual. Federal Highway Administration, Publication Number: FHWA-HOP-08-024. https://ops.fhwa.dot.gov/publications/fhwahop08024/fhwa_hop_08_024.pdf
• [24] Ali M.E.M. (2021). Akıllı Şehirler İçin Koordineli Adaptif Trafik Sinyalizasyon Kontrolü. Doktora Tezi, Selçuk Üniversitesi, Fen Bilimleri Enstitüsü.
• [25] Michailidis P., Michailidis I., Lazaridis C.R., Kosmatopoulos E. (2025). Traffic Signal Control via Reinforcement Learning: A Review on Applications and Innovations. Infrastructures, 10(5), 114. https://doi.org/10.3390/infrastructures10050114
• [26] Politi R.R. (2025). Yapay Zeka Yöntemleri ile Yakın Mesafeli Kavşaklarda Sinyal Optimizasyonu. Doktora Tezi, Dokuz Eylül Üniversitesi, Fen Bilimleri Enstitüsü.
• [27] Agrahari A., Dhabu M.M., Deshpande P.S., Tiwari A., Baig M.A., Sawarkar, A.D. (2024). Artificial Intelligence-Based Adaptive Traffic Signal Control System: A Comprehensive Review. Electronics, 13(19), 3875. https://doi.org/10.3390/electronics13193875
• [28] Miller A.J. (1963). Settings for fixed-cycle traffic signals. Operational Research Quarterly, 14(4)4: 373-386. https://doi.org/10.2307/3006800
• [29] Wang Y., Yang X., Liang H. and Liu Y. (2018). A Review of the Self-Adaptive Traffic Signal Control System Based on Future Traffic Environment. Journal of Advanced Transportation, 1096123:12 https://doi.org/10.1155/2018/1096123
• [30] Güler E. (2023). Işıklı Kavşakların Başarımının Belirlenmesinde Yeni Bir Model Önerisi. Yüksek Lisans Tezi, Dokuz Eylül Üniversitesi, Fen Bilimleri Enstitüsü.
• [31] Ma C., Yu C., Yang X. (2021). Trajectory planning for connected and automated vehicles at isolated signalized intersections under mixed traffic environment. Transportation Research Part C: Emerging Technologies, 130, 103309. https://doi.org/10.1016/j.trc.2021.103309
• [32] Filocamo B., Ruiz J.A., Sotelo M.A. (2020). Efficient Management of Road Intersections for Automated Vehicles-The FRFP System Applied to the Various Types of Intersections and Roundabouts. Applied Sciences, 10(1), 316. https://doi.org/10.3390/app10010316
• [33] Bento L.C., Parafita R., Rakha H.A., Nunes U.J. (2019). A study of the environmental impacts of intelligent automated vehicle control at intersections via V2V and V2I communications. Journal of Intelligent Transportation Systems Technology, Planning, and Operations, 23 (1), 41-59. https://doi.org/10.1080/15472450.2018.1501272
• [34] Jing P., Huang H., Chen L. (2017). An Adaptive Traffic Signal Control in a Connected Vehicle Environment: A Systematic Review. Information, 8(3), 101. https://doi.org/10.3390/info8030101
• [35] Çakıcı Z. (2020). Sinyalize Kavşaklar İçin Optimizasyon Tabanlı Trafik Yönetim Modeli. Doktora Tezi, Pamukkale Üniversitesi, Fen Bilimleri Enstitüsü.
• [36] Samadi S., Rad A.P., Kazemi F.M. & Jafarian H. (2012). Performance evaluation of intelligent adaptive traffic control systems: A case study. Journal of Transportation Technologies, 2:248-259. http://dx.doi.org/10.4236/jtts.2012.23027
• [37] Yılmaz Ö. (2012). Karayolu Ulaşımında Akıllı Ulaştırma Sistemleri. Uzmanlık Tezi, Kalkınma Bakanlığı Yayın No: 2840. https://www.sbb.gov.tr/wp-content/uploads/2022/08/Karayolu-Ulasiminda-Akilli-Ulastirma-Sistemleri-Ozhan-Yilmaz.pdf
• [38] Gündoğan F., Karagöz Z., Koçyiğit N., Karadağ A., Ceylan H. & Murat Y.Ş. (2014). An evaluation of adaptive traffic control system in Istanbul, Turkey. Journal of Traffic and Logistics Engineering, 2(3): 198-201. https://www.jtle.net/uploadfile/2014/0604/20140604034552236.pdf
• [39] Swaminathan N., Rathinavel N., Duraisamy S. & Karuppanan G. (2014). Design of vehicle actuated signal using simulation. GRADEVINAR, 66(7): 635-641. https://doi.org/10.14256/JCE.1008.2014
• [40] Bayrak C., ve diğ. (2014). İllerde Dinamik Kavşak Yönetiminin Etkileri: Çorum Örneği, ISSD Akademik yayınlar. https://www.issd.com.tr/wp-content/uploads/2024/03/Illerde_Dinamik_Kavsak_Yonetiminin_Etkileri.pdf
• [41] Shi M., Jiang H., & Li S. (2016). An intelligent traffic-flow-based real-time vehicles scheduling algorithm at intersection. 14th International Conference on Control, Automation, Robotics and Vision (ICARCV). 13-15th November 2016 Phuket, Thailand. https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7838779
• [42] Erol D., (2018). Kentiçi Işıklı ve Dönel Kavşak Uygulamalarının Performans Kriterlerine Etkisi: Denizli Örneği. Yüksek Lisans Tezi, Pamukkale Üniversitesi, Fen Bilimleri Enstitüsü.
• [43] Uludamar E. ve Tüccar, G. (2018). Comparison of Traffic Densities at Different Signalization Timings In Roundabouts. Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, 7:1, 217-223. https://doi.org/10.28948/ngumuh.386593
• [44] Promraksa T., Satiennam T. & Satiennam W. (2019). Vehicle actuated signal control for low carbon society. International Journal of GEOMATE, 16(55): 86-91. https://doi.org/10.21660/2019.55.4766
• [45] Muresan M., Fu L., & Pan, G. (2019). Adaptive Traffic Signal Control with Deep Reinforcement Learning An Exploratory Investigation. 97th Annual Meeting of the Transportation Research Board. https://doi.org/10.48550/arxiv.1901.00960
• [46] Chen P., Zhu Z., Lu G.(2019). An Adaptive Control Method for Arterial Signal Coordination Based on Deep Reinforcement Learning. 2019 IEEE Intelligent Transportation Systems Conference (ITSC), Auckland, New Zealand. DOI: 10.1109/ITSC.2019.8917051.
• [47] Jamal A., Tauhidur Rahman M., Al-Ahmadi H.M., Ullah I., Zahid M. (2020). Intelligent Intersection Control for Delay Optimization: Using Meta-Heuristic Search Algorithms. Sustainability, 12(5), 1896. https://doi.org/10.3390/su12051896
• [48] Çakıcı Z. ve Murat Y.Ş. (2021). Sinyalize Dönel kavşaklarda diferansiyel gelişim algoritması ile sinyal süre optimizasyonu. El-Cezerî Journal of Science and Engineering, 8(2): 635-651. https://doi.org/10.31202/ecjse.861429
• [49] Nie C., Wei H., Shi J. & Zhang M. (2021). Optimizing actuated traffic signal control using license plate recognition data: Methods for modeling and algorithm development. Transportation Research Interdisciplinary Perspectives, 9(2021)100319. https://doi.org/10.1016/j.trip.2021.100319
• [50] Wu Q., Wu J., Shen J., Du B., Telikani A., Fahmideh M., Liang, C. (2022). Distributed agent-based deep reinforcement learning for large scale traffic signal control. Knowledge-Based Systems, 241, 108304. https://doi.org/10.1016/j.knosys.2022.108304
• [51] Çakıcı Z., Murat Y.S., Aydın M.M. (2022). Design of an efficient vehicle-actuated signal control logic for signalized intersections. Sharif University of Technology Scientia Iranica Transactions A: Civil Engineering, 29(3), 1059-1076. DOI: 10.24200/SCI.2021.57231.5126
• [52] Özkul T. (2023). 10.Yıl Arterindeki 3 Eş Düzey Sinyalize Kavşağın Akıllı Kavşak Performanslarının İncelenmesi. Yüksek Lisans Tezi, Bilecik Şeyh Edebali Üniversitesi Lisansüstü Eğitim Enstitüsü.
• [53] Duraku R. and Boshnjaku D. (2024). Enhancing Traffic Sustainability: An Analysis of Isolation Intersection Effectiveness through Fixed Time and Logic Control Design Using VisVAP Algorithm. Sustainability, 16: 2930. https://doi.org/10.3390/su16072930
• [54] Yaman T. (2024). Farklı Trafik Uyarmalı Sinyalize Kavşakların Performanslarının Karşılaştırılması. Yüksek Lisans Tezi, Ondokuz Mayıs Üniversitesi, Lisansüstü Eğitim Enstitüsü.
• [55] Agrahari A., Dhabu M.M., Deshpande P.S., Tiwari A., Baig M.A., Sawarkar A. D. (2024). Artificial Intelligence-Based Adaptive Traffic Signal Control System: A Comprehensive Review. Electronics, 13(19), 3875. https://doi.org/10.3390/electronics13193875
• [56] PTV VISSIM, Erişim tarihi: 21.03.2025. https://www.ptvgroup.com/en/products/ptv-vissim
• [57] T.C. Çevre Şehircilik ve İklim Değişikliği Bakanlığı. “Yeni Ankara Adalet Sarayının Temeli Törenle Atıldı”. Erişim tarihi: 16.12.2024. https://csb.gov.tr/yeni-ankara-adalet-sarayinin-temeli-torenle-atildi-bakanlik-faaliyetleri-40266
• [58] Önder M., Keçel S., Önder H.G., Ulvi H. (2014). Ankara Ulaşım Ana Planı Hane Halkı Araştırması Sonuçları. Gazi Üniversitesi Ankara Ulaşım Ana Planı Çalışması. https://kutem.gazi.edu.tr/view/page/189765?siteUri=kutem
• [59] Aslan C. (2019). Kent İçi Ulaşım Hizmetleri Memnuniyet Araştırması: Ankara İli Örneği. Yüksek Lisans Tezi. Ankara Hacı Bayram Veli Üniversitesi, Lisansüstü Eğitim Enstitüsü.