YOĞUN SAATLERDE SİNYALİZE BİR KAVŞAĞIN TRAFİK SİMÜLASYONU: BİR VAKA ÇALIŞMASI

Loading...
Publication Logo

Date

2024

Authors

Sinem Özkan
Mert Paldrak
Erdinc Oner

Journal Title

Journal ISSN

Volume Title

Publisher

Open Access Color

GOLD

Green Open Access

No

OpenAIRE Downloads

OpenAIRE Views

Publicly Funded

No
Impulse
Average
Influence
Average
Popularity
Average

Research Projects

Journal Issue

Abstract

Bu çalışmada İzmir'in en yoğun sinyalize kavşaklarından biri olan Vakıflar Kavşağının trafiğin yoğun saatlerde simüle edilmesine odaklanılmıştır. Çalışma kavşaktaki darboğazları daha iyi anlamak analiz etmek ve iyileştirmek için çözümler önermek amacıyla ağ üzerindeki trafiği simüle etmek amacıyla yürütülmüştür. Simülasyon modeli ARENA Yazılımında oluşturulmuş ve ilk sonuçlar kavşağın doğu ve batı güzergahlarında önemli bir kuyruk problemi olduğunu göstermiştir. Sorunun üstesinden gelmek için kavşağın doğu ve batı taraflarını birbirine bağlayan bir alt geçit içeren yeni bir tasarım önerilmiştir. Geliştirilen modelden elde edilen sonuçlar Şehitler Caddesi ve Kamil Tunca Bulvarı'nda kuyrukta bekleyen araç sayısının ve bekleme süresinin önemli ölçüde azaldığını göstermiştir.

Description

Keywords

Endüstri Mühendisliği, Endüstri Mühendisliği, Trafik Sinyali;Simülasyon;Alt Geçitler;Dönel Kavşaklar, Industrial Engineering, Traffic Signal;Simulation;Underpasses;Roundabouts

Fields of Science

Citation

Abdelghaffar H. M. Yang H. & Rakha H. A. (2017). Developing a de-centralized cycle-free nash bargaining arterial traffic signal controller. 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (pp. 544-549). Doi: https://doi.org/10.1109/MTITS.2017. 8005732Akcelik R. (1981). Traffic signals: Capacity and timing analysis. Melbourne: Australian Road Research Board ARR.Allsop R. E. (1972). Delay at a fixed time traffic signal—I: Theoretical analysis. Transportation Science 6(3) 260-285. Doi: https://doi.org/10.1287/trsc.6.3.260Araghi S. Khosravi A. & Creighton D. (2015). Intelligent cuckoo search optimized traffic signal controllers for multi-intersection network. Expert Systems with Applications 42(9) 4422-4431. Doi: https://doi.org/10.1016/j.eswa.2015.01.063Carson Y. & Maria A. (1997 December). Simulation optimization: methods and applications. In Proceedings of the 29th conference on Winter simulation (pp. 118-126). Doi: https://doi.org/10.1145/268437.268460Chen S. & Sun D. J. (2016). An improved adaptive signal control method for isolated signalized intersection based on dynamic programming. IEEE Intelligent Transportation Systems Magazine 8(4) 4-14. Doi: https://doi.org/10.1109/MITS.2016.2605318Dabiri S. & Abbas M. (2016 November). Arterial traffic signal optimization using particle swarm optimization in an integrated VISSIM-MATLAB simulation environment. IEEE 19th international conference on intelligent transportation systems (pp. 766-771). IEEE. Doi: https://doi.org/10.1109/ITSC.2016.7795641Eiben A. E. & Smith J. E. (2015). Introduction to evolutionary computing. Berlin: Springer. Gökçe M. A. Öner E. & Işık G. (2015). Traffic signal optimization with particle swarm optimization for signalized roundabouts. Simulation 91(5) 456-466. Doi: https://doi.org/10.1177/0037549715581473Hajbabaie A. & Benekohal R. F. (2015). A program for simultaneous network signal timing optimization and traffic assignment. IEEE Transactions on Intelligent Transportation Systems 16(5) 2573-2586. Doi: https://doi.org/10.1109/TITS.2015.2413360Jin J. Ma X. & Kosonen I. (2017). An intelligent control system for traffic lights with simulation-based evaluation. Control engineering practice 58 24-33. Doi: https://doi.org/10.1016/j.conengprac.2016.09.009Köhler E. & Strehler M. (2019). Traffic signal optimization: Combining static and dynamic models. Transportation science 53(1) 21-41. Doi: https://doi.org/10.1287/trsc.2017.0760Li Z. & Schonfeld P. (2015). Hybrid simulated annealing and genetic algorithm for optimizing arterial signal timings under oversaturated traffic conditions. Journal of advanced transportation 49(1) 153-170. Doi: https://doi.org/10.1002/atr.1274Louati A. Elkosantini S. Darmoul S. & Ben Said L. (2019). An immune memory inspired case-based reasoning system to control interrupted flow at a signalized intersection. Artificial Intelligence Review 52 2099-2129. Doi: https://doi.org/10.1007/s10462-017-9604-0Miletić M. Kapusta B. & Ivanjko E. (2018 September). Comparison of two approaches for preemptive traffic light control. In 2018 international symposium ELMAR (pp. 57-62). IEEE. Doi: https://doi.org/10.23919/ELMAR.2018.8534608Mok K. & Zhang L. (2024). Adaptive traffic signal management method combining deep learning and simulation. Multimedia Tools and Applications 83(5) 15439-15459. Doi: https://doi.org/10.1007/s11042-022-13033-5Murat Y. S. Cakici Z. & Tian Z. (2019). A signal timing assignment proposal for urban multi lane signalised roundabouts. Građevinar 71(02.) 113-124. Doi: https://doi.org/10.14256/JCE.2323.2018Nguyen P. T. M. Passow B. N. & Yang Y. (2016 July). Improving anytime behavior for traffic signal control optimization based on NSGA-II and local search. In 2016 International Joint Conference on Neural Networks (IJCNN) (pp. 4611-4618). IEEE. Doi: https://doi.org/10.1109/IJCNN.2016.7727804Otamendi J. Pastor J. M. & Garcı A. (2008). Selection of the simulation software for the management of the operations at an international airport. Simulation Modelling Practice and Theory 16(8) 1103-1112. Doi: https://doi.org/10.1016/j.simpat.2008.04.022Qadri S. S. S. M. Gökçe M. A. & Öner E. (2020). State-of-art review of traffic signal control methods: challenges and opportunities. European transport research review 12 1-23. Doi: https://doi.org/10.1186/s12544-020-00439-1 Robertson D.I. 1969. TRANSYT: a traffic network study tool. UK: CrowthorneSheu J. B. (2006). A composite traffic flow modeling approach for incident-responsive network traffic assignment. Physica A: Statistical Mechanics and its Applications 367 461-478. Doi: https://doi.org/10.1016/ j.physa.2005.11.039Spall J. C. & Chin D. C. (1997). Traffic-responsive signal timing for system-wide traffic control. Transportation Research Part C: Emerging Technologies 5(3-4) 153-163. Doi: https://doi.org/10.1016/S0968-090X(97)00012-0Stupin A. Kazakovtsev L. & Stupina A. (2022). Control of traffic congestion by improving the rings and optimizing the phase lengths of traffic lights with the help of anylogic. Transportation research procedia 63 1104-1113. Doi: https://doi.org/10.1016/j.trpro.2022.06.113Tang C. Xia S. Zhu C. & Wei X. (2019). Phase timing optimization for smart traffic control based on fog computing. IEEE Access 7 84217-84228. Doi: https://doi.org/10.1109/ACCESS.2019.2925134Van Woensel T. & Vandaele N. (2007). Modeling traffic flows with queueing models: a review. Asia-Pacific Journal of Operational Research 24(04) 435-461. Doi: https://doi.org/10.1142/S0217595907001383Venayagamoorthy G. K. K. (2009). A successful interdisciplinary course on coputational intelligence. IEEE Computational Intelligence Magazine 4(1) 14-23. Doi: https://doi.org/10.1109/MCI.2008.930983Webster F. V. (1958). Traffic signal settings. Road Research Laboratory London U.K. Road Res. Tech. Paper no. 39. Retrieved from https://trid.trb.org/View/113579Zhao D. Dai Y. & Zhang Z. (2011). Computational intelligence in urban traffic signal control: A survey. IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews) 42(4) 485-494. Doi: https://doi.org/10.1109/TSMCC.2011.2161577

WoS Q

Scopus Q

OpenCitations Logo
OpenCitations Citation Count
1

Source

Endüstri Mühendisliği

Volume

35

Issue

2

Start Page

136

End Page

166
PlumX Metrics
Captures

Mendeley Readers : 1

Google Scholar Logo
Google Scholar™
OpenAlex Logo
OpenAlex FWCI
0.3252

Sustainable Development Goals