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TRAFFIC LIGHT OPTIMIZATION AT INTERSECTIONS: A CASE STUDY IN ANKARA CITY

Year 2024, EARLY VIEW, 1 - 1

Tuğçe İnağ Murat Arıkan

https://doi.org/10.2339/politeknik.1369924

Abstract

The increasing population and the growing number of vehicles due to the population have made traffic congestion a significant problem. One of the most common places for traffic congestion is intersections. The main aim of this study is to improve traffic light management at the Polatlı Refik Cesur intersection, where high-density traffic is observed and vehicle queues form. To achieve the objectives, a simulation-based solution approach is proposed, together with the Webster and Modified Webster-based Ant Colony Algorithm (ACA), to determine the most suitable value for the traffic light cycle and minimize the average delay time of vehicles. The SUMO (Simulation of Urban Mobility) simulation platform was used in the implementation. The calculation results have shown that, compared to the current situation, the delay time decreased by approximately 32% and 42% with the Webster-based ACA and Modified Webster-based ACA methods, respectively. As a result, better management of cycle times and green light durations reduces traffic congestion, decreases the average waiting times for vehicles, and improves traffic flow.

Keywords

Traffic light management Webster Ant colony algorithm Modify webster

References

  • [1] Fu, X., Gao, H., Cai, H., Wang, Z.and Chen, W. “How to improve urban intelligent traffic? A case study using traffic signal timing optimization model based on swarm intelligence algorithm” Sensors, 21(8): 2631, (2021).
  • [2] Salawudeen, A.T., Umoh, I.J., Sadiq, B.O., Oyenike, O.I.and Mu'azu, M.B. “An adaptive ant colony optimisation for improved lane detection in intelligent automobile vehicles” International Journal of Bio-Inspired Computation, 19(2) : 108-123, (2022).
  • [3] Balta, M.and Ozcelik, I. “Traffic Signaling Optimization for Intelligent and Green Transportation in Smart Cities” International Conference on Smart City and Emerging Technology, ICSCET (2018).
  • [4] Rida, N., Ouadoud, M.and Hasbi, A., “Ant colony optimization for real time traffic lights control on a single intersection.” International Journal of Interactive Mobile Technologies, 14(2): 196-214, (2020).
  • [5] Cui, Z., Sun, B., Wang, G., Xue, Y.and Chen, J., “A novel oriented cuckoo search algorithm to improve DV-Hop performance for cyber–physical systems”, Journal of Parallel and Distributed Computing, 103: 42-52, (2017).
  • [6] Gao, K., Wu, N.and Wang, R., “Meta-heuristic and MILP for Solving Urban Traffic Signal Control”, International Conference on Industrial Engineering and Systems Management, IESM, (2019).
  • [7] Gao, K., Zhang, Y., Zhang, Y., Su, R.and Suganthan, P.N., “Meta-Heuristics for Bi-Objective Urban Traffic Light Scheduling Problems”, IEEE Transactions on Intelligent Transportation Systems, 20(7): 2618-2629, (2019).
  • [8] Shaikh, P.W., El-Abd, M., Khanafer, M.and Gao, K., “A Review on Swarm Intelligence and Evolutionary Algorithms for Solving the Traffic Signal Control Problem”, IEEE Transactions on Intelligent Transportation Systems, 23(1): 48-63, (2022).
  • [9] Salawudeen, A.T., Umoh, I.J., Sadiq, B.O., Oyenike, O.I.and Mu'azu, M.B., “An adaptive ant colony optimisation for improved lane detection in intelligent automobile vehicles”, International Journal of Bio-Inspired Computation, 19(2): 108-123, (2022).
  • [10] Rida, N., Ouadoud, M.and Hasbi, A., “Ant colony optimization for real time traffic lights control on a single intersection”, International Journal of Interactive Mobile Technologies, 14(2): 196-214, (2020).
  • [11] He, J.and Hou, Z., “Ant colony algorithm for traffic signal timing optimization”, Advances in Engineering Software, 43(1): 14-18, (2012).
  • [12] Liao, S., Wu, Y., Ma, K.and Niu, Y., “Ant Colony Optimization With Look-Ahead Mechanism for Dynamic Traffic Signal Control of IoV Systems”, IEEE Internet of Things Journal, 11(1): 366-377, (2024).
  • [13] Cui, Z., Sun, B., Wang, G., Xue, Y.and Chen, J.,” A novel oriented cuckoo search algorithm to improve DV-Hop performance for cyber–physical systems”, Journal of Parallel and Distributed Computing, 103: 42-52, (2017).
  • [14] Gao, K., Wu, N.and Wang, R., “Meta-heuristic and MILP for Solving Urban Traffic Signal Control”, International Conference on Industrial Engineering and Systems Management, IESM, (2019).
  • [15] Gao, K., Zhang, Y., Zhang, Y., Su, R.and Suganthan, P.N., “Meta-Heuristics for Bi-Objective Urban Traffic Light Scheduling Problems”, IEEE Transactions on Intelligent Transportation Systems, 20(7): 2618-2629, (2019).
  • [16] Zine-Dine, K.and Madani, A., “Using PSO algorithm for the traffic lights setting problem with cellular automaton model” Journal of Theoretical and Applied Information Technology, 53(1): 89-93, (2013).
  • [17] Wang, L., Gao, K., Lin, Z.and Huang, W., “Problem Feature-Based Meta-Heuristics with Reinforcement Learning for Solving Urban Traffic Light Scheduling Problems”, IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC, (2022).
  • [18] Chen, X.and Yuan, Z., “Environmentally friendly traffic control strategy-A case study in Xi’an city”, Journal of Cleaner Production, 249: 119397, (2020).
  • [19] Ji, Y., Hu, B., Hill, G., Guo, W., Blythe, P.and Gao, L., “Signal coordination scheme based on traffic emission”, IET Intelligent Transport Systems, 10(2): 89-96, (2016).
  • [20] Zhang, Q., Dong, W.and Xing, X., “PBIL algorithm for signal timing optimization of isolated intersection”, Communications in Computer and Information Science, 472: 606-610, (2014).
  • [21] Balta, M.and Ozcelik, I., “Traffic Signaling Optimization for Intelligent and Green Transportation in Smart Cities”, International Conference on Smart City and Emerging Technology, ICSCET, (2018).
  • [22] Elgarej, M., Khalifa, M.and Youssfi, M., “Traffic lights optimization with distributed ant colony optimization based on multi-agent system”, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 9944: 266-279, (2016).
  • [23] Witeck, G.R., Rocha, A.M.A.C., Silva, G.O., Silva, A., Durães, D.and Machado, J. “A Bibliometric Review and Analysis of Traffic Lights Optimization”. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatic, 13378: 43-54, (2022).
  • [24] Li, L., Ma, Y., Wang, B., Dong, H.and Zhang, Z., “Research on traffic signal timing method based on ant colony algorithm and fuzzy control theory”, Proceedings of Engineering and Technology Innovation, 11: 21-29, (2019).
  • [25] Srivastava, S.and Sahana, S.K., “Nested,hybrid evolutionary model for traffic signal optimization”, Applied Intelligence, 46(1): 113-123, (2017).
  • [26] Celtek, S.A., Durdu, A.and Alı, M.E.M.,” Real-time traffic signal control with swarm optimization methods”, Measurement: Journal of the International Measurement Confederation, 166, (2020).
  • [27] Tomescu, O., Moise, I.M., Stanciu, A.E.and Batros, I., “Adaptive traffic light control system using ad-hoc vehicular communications network”, Taiwanese Association for Artificial Intelligence, 74(2): 1-8, (2012).
  • [28] Duman, Z.N., Murat, Y.S.and YİLmaz, M., “Koordine Kavşaklarda Sinyalizasyon Sistemine Etki Eden Parametrelerin İncelenmesi Vaka Durum Çalışması”, Politeknik Dergisi, 1-1, (2023).
  • [29] Renfrew, D.and Yu, X.-H., “Traffic signal optimization using ant colony algorithm”,International Joint Conference on Neural Networks (IJCNN), (2012) .
  • [30] Shih, P.S., Liu, S.and Yu, X.H., “Ant Colony Optimization for Multi-phase Traffic Signal Control” 7th International Conference on Intelligent Transportation Engineering, ICITE, (2022).
  • [31] Song, Q., Zhao, Q., Wang, S., Liu, Q.and Chen, X., “Dynamic path planning for unmanned vehicles based on fuzzy logic and improved ant colony optimization”, IEEE Access, 8: 62107-62115, (2020).
  • [32] Putha, R., Quadrifoglio, L.and Zechman, E., “Comparing ant colony optimization and genetic algorithm approaches for solving traffic signal coordination under oversaturation conditions”, Computer‐Aided Civil and Infrastructure Engineering, 27(1): 14-28, (2012).
  • [33] Pérez-Carabaza, S., Gálvez, A.and Iglesias, A.,”Rank-Based Ant System with Originality Reinforcement and Pheromone Smoothing”, Applied Sciences (Switzerland), 12(21), (2022).
  • [34] Balta, M. and Özçelik, İ., “Şehir içi kavşak yönetim sistemleri için SDN temelli bir VANET mimari önerisi”, Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 34(3): 1451-1468, (2019).
  • [35] Zakariya, A.Y.and Rabia, S.I., “Estimating the minimum delay optimal cycle length based on a time-dependent delay formula”, Alexandria Engineering Journal, 55(3): 2509-2514, (2016).
  • [36] Wagner, P., Gartner, N., Oertel, R.and Lu, T., “Webster’s Delay Formula – revisited”, 93rd Annual MeetingTransportation Research Board, Washington, (2014).
  • [37] Teply, S., Allingham, D., Richardson, D.and Stephenson, B. “Canadian capacity guide for signalized intersections”, (2008).
  • [38] Webster, F.V., “Traffic Signal Settings,” Road Research Technique, 39, (1958).
  • [39] Ali, M.E.M., Durdu, A., Celtek, S.and Yilmaz, A. An Adaptive Method for Traffic Signal Control Based on Fuzzy Logic With Webster and Modified Webster Formula Using SUMO Traffic Simulator”, IEEE Access, 1-1, (2021).
  • [40] Cheng, D., Messer, C.J., Tian, Z.Z.and Liu, J., “Modification of Webster’s minimum delay cycle length equation based on HCM 2000”, Transportation Research Board for Presentation and Publication at the 2003 Annual Meeting in Washington. DC, (2003).
  • [41] Kotusevski, G.and Hawick, K., “A review of traffic simulation software”, Research Letters in the Information and Mathematical Sciences, 13: 35-54, (2009).
  • [42] Manandhar, B.and Joshi, B., “Adaptive traffic light control with statistical multiplexing technique and particle swarm optimization in smart cities”, IEEE 3rd International Conference on Computing, Communication and Security (ICCCS), (2018).
  • [43] Zaatouri, K., Jeridi, M.H.and Ezzedine, T.,”Adaptive traffic light control system based on WSN: algorithm optimization and hardware design”, 26th International Conference on Software, Telecommunications and Computer Networks (SoftCOM), (2018).
  • [44] Andayani, U., Arisandi, D., Siregar, B., Syahputra, M., Muchtar, M., Manurung, O.Y., Nasution, T.,”Simulation of Dynamic Traffic Light Setting Using Adaptive Neuro-Fuzzy Inference System (ANFIS”,. Journal of Physics: Conference Series, (2019).
  • [45] Walukow, S.B., Doringin, F.J., Katuuk, R.E.and Wauran, A.S.,” Regulation of the Real Time Traffic Light at Teling Intersection in Manado City by using Fuzzy Logic and ANFIS”, International Conference on Applied Science and Technology (iCAST), (2018).
  • [46] Wei, H., Zheng, G., Yao, H.and Li, Z., “Intellilight: A reinforcement learning approach for intelligent traffic light control”, 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, (2018).
  • [47] Lee, S., Younis, M., Murali, A.and Lee, M., “Dynamic local vehicular flow optimization using real-time traffic conditions at multiple road intersections” IEEE Access, 7: 28137-28157, (2019).
  • [48] Saidallah, M., El Fergougui, A.and Elalaoui, A.E., “A comparative study of urban road traffic simulators”, MATEC Web of Conferences, (2016).
  • [49] Solmaz, H., Kocakulak, T.and Şahin, F., “Control and Optimization of Pre-Transmission Parallel Hybrid Vehicle with Fuzzy Logic Method and Comparison with Conventional Rule Based Control Strategy”, Politeknik Dergisi, 26(3): 1035-1047, (2023).
  • [50] Ali, M.E.M., Durdu, A., Celtek, S.A.and Yilmaz, A. An Adaptive Method for Traffic Signal Control Based on Fuzzy Logic With Webster and Modified Webster Formula Using SUMO Traffic Simulator, IEEE Access, 9, 102985-102997, (2021).
  • [51] Faezi, S.and Dolatabadi, M.M., “Saturation Flow Rate of Urban At-Grade Signalized Intersection Under Different Climatic Conditions (Case Study: Sattari-Mokhberi Intersection)” Iranian Journal of Science and Technology, Transactions of Civil Engineering, 1-12, (2021).
  • [52] Mohiddin, S.K., Prasanth, C., Rathore, G.S.and Hemanth, C.,“Mathematical analysis of adaptive queue length-based traffic signal control”, Lecture Notes in Electrical Engineering, (2019).
  • [53] Akçelik, R., Smit, R.and Besley, M., “Recalibration of a vehicle power model for fuel and emission estimation and its effect on assessment of alternative intersection treatments”, 4th International Roundabout Conference, Seattle, WA, USA, (2014).

KAVŞAKLARDA TRAFİK IŞIK OPTİMİZASYONU: ANKARA İLİ’NDE BİR UYGULAMA

Year 2024, EARLY VIEW, 1 - 1

Tuğçe İnağ Murat Arıkan

https://doi.org/10.2339/politeknik.1369924

Abstract

Giderek artan nüfus ve nüfusa bağlı artan araç sayısı trafik sıkışıklığını önemli bir sorun haline getirmektedir. Trafik sıkışıklığının en yaygın olduğu yerlerden biri kavşaklardır. Bu çalışmanın temel amacı, yüksek yoğunluklu trafiğin gözlemlendiği ve araç kuyruklarının oluştuğu Polatlı Refik Cesur kavşağındaki trafik ışık yönetimini iyileştirmektir. Hedeflere ulaşmak için, trafik ışığı döngüsünün en uygun değerini belirleyerek araçların ortalama gecikme süresini en aza indirmek amacıyla Webster ve Modifiye Webster tabanlı Karınca Kolonisi algoritması (KKA) ile birlikte simülasyon tabanlı bir çözüm yaklaşımı önerilmiştir. Uygulamada SUMO (Simulation of Urban Mobility) simülasyon platformu kullanılmıştır. Hesaplama sonuçları, gecikme süresinin mevcut duruma göre, Webster tabanlı KKA ve Modifiye Webster tabanlı KKA yöntemleri ile ortalama bekleme süresi değerlerini sırasıyla %32 ve %42 oranlarında azaltığını göstermiştir. Sonuç olarak, devre süresinin ve yeşil ışık sürelerinin daha iyi yönetilmesi, trafik sıkışıklığını ve araç ortalama bekleme sürelerini azaltmakta ve trafik akışının düzelmesini sağlamaktadır.

Keywords

Trafik ışık optimizasyonu Webster yöntemi Karınca kolonisi algoritması Modifiye Webster yöntemi

References

  • [1] Fu, X., Gao, H., Cai, H., Wang, Z.and Chen, W. “How to improve urban intelligent traffic? A case study using traffic signal timing optimization model based on swarm intelligence algorithm” Sensors, 21(8): 2631, (2021).
  • [2] Salawudeen, A.T., Umoh, I.J., Sadiq, B.O., Oyenike, O.I.and Mu'azu, M.B. “An adaptive ant colony optimisation for improved lane detection in intelligent automobile vehicles” International Journal of Bio-Inspired Computation, 19(2) : 108-123, (2022).
  • [3] Balta, M.and Ozcelik, I. “Traffic Signaling Optimization for Intelligent and Green Transportation in Smart Cities” International Conference on Smart City and Emerging Technology, ICSCET (2018).
  • [4] Rida, N., Ouadoud, M.and Hasbi, A., “Ant colony optimization for real time traffic lights control on a single intersection.” International Journal of Interactive Mobile Technologies, 14(2): 196-214, (2020).
  • [5] Cui, Z., Sun, B., Wang, G., Xue, Y.and Chen, J., “A novel oriented cuckoo search algorithm to improve DV-Hop performance for cyber–physical systems”, Journal of Parallel and Distributed Computing, 103: 42-52, (2017).
  • [6] Gao, K., Wu, N.and Wang, R., “Meta-heuristic and MILP for Solving Urban Traffic Signal Control”, International Conference on Industrial Engineering and Systems Management, IESM, (2019).
  • [7] Gao, K., Zhang, Y., Zhang, Y., Su, R.and Suganthan, P.N., “Meta-Heuristics for Bi-Objective Urban Traffic Light Scheduling Problems”, IEEE Transactions on Intelligent Transportation Systems, 20(7): 2618-2629, (2019).
  • [8] Shaikh, P.W., El-Abd, M., Khanafer, M.and Gao, K., “A Review on Swarm Intelligence and Evolutionary Algorithms for Solving the Traffic Signal Control Problem”, IEEE Transactions on Intelligent Transportation Systems, 23(1): 48-63, (2022).
  • [9] Salawudeen, A.T., Umoh, I.J., Sadiq, B.O., Oyenike, O.I.and Mu'azu, M.B., “An adaptive ant colony optimisation for improved lane detection in intelligent automobile vehicles”, International Journal of Bio-Inspired Computation, 19(2): 108-123, (2022).
  • [10] Rida, N., Ouadoud, M.and Hasbi, A., “Ant colony optimization for real time traffic lights control on a single intersection”, International Journal of Interactive Mobile Technologies, 14(2): 196-214, (2020).
  • [11] He, J.and Hou, Z., “Ant colony algorithm for traffic signal timing optimization”, Advances in Engineering Software, 43(1): 14-18, (2012).
  • [12] Liao, S., Wu, Y., Ma, K.and Niu, Y., “Ant Colony Optimization With Look-Ahead Mechanism for Dynamic Traffic Signal Control of IoV Systems”, IEEE Internet of Things Journal, 11(1): 366-377, (2024).
  • [13] Cui, Z., Sun, B., Wang, G., Xue, Y.and Chen, J.,” A novel oriented cuckoo search algorithm to improve DV-Hop performance for cyber–physical systems”, Journal of Parallel and Distributed Computing, 103: 42-52, (2017).
  • [14] Gao, K., Wu, N.and Wang, R., “Meta-heuristic and MILP for Solving Urban Traffic Signal Control”, International Conference on Industrial Engineering and Systems Management, IESM, (2019).
  • [15] Gao, K., Zhang, Y., Zhang, Y., Su, R.and Suganthan, P.N., “Meta-Heuristics for Bi-Objective Urban Traffic Light Scheduling Problems”, IEEE Transactions on Intelligent Transportation Systems, 20(7): 2618-2629, (2019).
  • [16] Zine-Dine, K.and Madani, A., “Using PSO algorithm for the traffic lights setting problem with cellular automaton model” Journal of Theoretical and Applied Information Technology, 53(1): 89-93, (2013).
  • [17] Wang, L., Gao, K., Lin, Z.and Huang, W., “Problem Feature-Based Meta-Heuristics with Reinforcement Learning for Solving Urban Traffic Light Scheduling Problems”, IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC, (2022).
  • [18] Chen, X.and Yuan, Z., “Environmentally friendly traffic control strategy-A case study in Xi’an city”, Journal of Cleaner Production, 249: 119397, (2020).
  • [19] Ji, Y., Hu, B., Hill, G., Guo, W., Blythe, P.and Gao, L., “Signal coordination scheme based on traffic emission”, IET Intelligent Transport Systems, 10(2): 89-96, (2016).
  • [20] Zhang, Q., Dong, W.and Xing, X., “PBIL algorithm for signal timing optimization of isolated intersection”, Communications in Computer and Information Science, 472: 606-610, (2014).
  • [21] Balta, M.and Ozcelik, I., “Traffic Signaling Optimization for Intelligent and Green Transportation in Smart Cities”, International Conference on Smart City and Emerging Technology, ICSCET, (2018).
  • [22] Elgarej, M., Khalifa, M.and Youssfi, M., “Traffic lights optimization with distributed ant colony optimization based on multi-agent system”, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 9944: 266-279, (2016).
  • [23] Witeck, G.R., Rocha, A.M.A.C., Silva, G.O., Silva, A., Durães, D.and Machado, J. “A Bibliometric Review and Analysis of Traffic Lights Optimization”. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatic, 13378: 43-54, (2022).
  • [24] Li, L., Ma, Y., Wang, B., Dong, H.and Zhang, Z., “Research on traffic signal timing method based on ant colony algorithm and fuzzy control theory”, Proceedings of Engineering and Technology Innovation, 11: 21-29, (2019).
  • [25] Srivastava, S.and Sahana, S.K., “Nested,hybrid evolutionary model for traffic signal optimization”, Applied Intelligence, 46(1): 113-123, (2017).
  • [26] Celtek, S.A., Durdu, A.and Alı, M.E.M.,” Real-time traffic signal control with swarm optimization methods”, Measurement: Journal of the International Measurement Confederation, 166, (2020).
  • [27] Tomescu, O., Moise, I.M., Stanciu, A.E.and Batros, I., “Adaptive traffic light control system using ad-hoc vehicular communications network”, Taiwanese Association for Artificial Intelligence, 74(2): 1-8, (2012).
  • [28] Duman, Z.N., Murat, Y.S.and YİLmaz, M., “Koordine Kavşaklarda Sinyalizasyon Sistemine Etki Eden Parametrelerin İncelenmesi Vaka Durum Çalışması”, Politeknik Dergisi, 1-1, (2023).
  • [29] Renfrew, D.and Yu, X.-H., “Traffic signal optimization using ant colony algorithm”,International Joint Conference on Neural Networks (IJCNN), (2012) .
  • [30] Shih, P.S., Liu, S.and Yu, X.H., “Ant Colony Optimization for Multi-phase Traffic Signal Control” 7th International Conference on Intelligent Transportation Engineering, ICITE, (2022).
  • [31] Song, Q., Zhao, Q., Wang, S., Liu, Q.and Chen, X., “Dynamic path planning for unmanned vehicles based on fuzzy logic and improved ant colony optimization”, IEEE Access, 8: 62107-62115, (2020).
  • [32] Putha, R., Quadrifoglio, L.and Zechman, E., “Comparing ant colony optimization and genetic algorithm approaches for solving traffic signal coordination under oversaturation conditions”, Computer‐Aided Civil and Infrastructure Engineering, 27(1): 14-28, (2012).
  • [33] Pérez-Carabaza, S., Gálvez, A.and Iglesias, A.,”Rank-Based Ant System with Originality Reinforcement and Pheromone Smoothing”, Applied Sciences (Switzerland), 12(21), (2022).
  • [34] Balta, M. and Özçelik, İ., “Şehir içi kavşak yönetim sistemleri için SDN temelli bir VANET mimari önerisi”, Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 34(3): 1451-1468, (2019).
  • [35] Zakariya, A.Y.and Rabia, S.I., “Estimating the minimum delay optimal cycle length based on a time-dependent delay formula”, Alexandria Engineering Journal, 55(3): 2509-2514, (2016).
  • [36] Wagner, P., Gartner, N., Oertel, R.and Lu, T., “Webster’s Delay Formula – revisited”, 93rd Annual MeetingTransportation Research Board, Washington, (2014).
  • [37] Teply, S., Allingham, D., Richardson, D.and Stephenson, B. “Canadian capacity guide for signalized intersections”, (2008).
  • [38] Webster, F.V., “Traffic Signal Settings,” Road Research Technique, 39, (1958).
  • [39] Ali, M.E.M., Durdu, A., Celtek, S.and Yilmaz, A. An Adaptive Method for Traffic Signal Control Based on Fuzzy Logic With Webster and Modified Webster Formula Using SUMO Traffic Simulator”, IEEE Access, 1-1, (2021).
  • [40] Cheng, D., Messer, C.J., Tian, Z.Z.and Liu, J., “Modification of Webster’s minimum delay cycle length equation based on HCM 2000”, Transportation Research Board for Presentation and Publication at the 2003 Annual Meeting in Washington. DC, (2003).
  • [41] Kotusevski, G.and Hawick, K., “A review of traffic simulation software”, Research Letters in the Information and Mathematical Sciences, 13: 35-54, (2009).
  • [42] Manandhar, B.and Joshi, B., “Adaptive traffic light control with statistical multiplexing technique and particle swarm optimization in smart cities”, IEEE 3rd International Conference on Computing, Communication and Security (ICCCS), (2018).
  • [43] Zaatouri, K., Jeridi, M.H.and Ezzedine, T.,”Adaptive traffic light control system based on WSN: algorithm optimization and hardware design”, 26th International Conference on Software, Telecommunications and Computer Networks (SoftCOM), (2018).
  • [44] Andayani, U., Arisandi, D., Siregar, B., Syahputra, M., Muchtar, M., Manurung, O.Y., Nasution, T.,”Simulation of Dynamic Traffic Light Setting Using Adaptive Neuro-Fuzzy Inference System (ANFIS”,. Journal of Physics: Conference Series, (2019).
  • [45] Walukow, S.B., Doringin, F.J., Katuuk, R.E.and Wauran, A.S.,” Regulation of the Real Time Traffic Light at Teling Intersection in Manado City by using Fuzzy Logic and ANFIS”, International Conference on Applied Science and Technology (iCAST), (2018).
  • [46] Wei, H., Zheng, G., Yao, H.and Li, Z., “Intellilight: A reinforcement learning approach for intelligent traffic light control”, 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, (2018).
  • [47] Lee, S., Younis, M., Murali, A.and Lee, M., “Dynamic local vehicular flow optimization using real-time traffic conditions at multiple road intersections” IEEE Access, 7: 28137-28157, (2019).
  • [48] Saidallah, M., El Fergougui, A.and Elalaoui, A.E., “A comparative study of urban road traffic simulators”, MATEC Web of Conferences, (2016).
  • [49] Solmaz, H., Kocakulak, T.and Şahin, F., “Control and Optimization of Pre-Transmission Parallel Hybrid Vehicle with Fuzzy Logic Method and Comparison with Conventional Rule Based Control Strategy”, Politeknik Dergisi, 26(3): 1035-1047, (2023).
  • [50] Ali, M.E.M., Durdu, A., Celtek, S.A.and Yilmaz, A. An Adaptive Method for Traffic Signal Control Based on Fuzzy Logic With Webster and Modified Webster Formula Using SUMO Traffic Simulator, IEEE Access, 9, 102985-102997, (2021).
  • [51] Faezi, S.and Dolatabadi, M.M., “Saturation Flow Rate of Urban At-Grade Signalized Intersection Under Different Climatic Conditions (Case Study: Sattari-Mokhberi Intersection)” Iranian Journal of Science and Technology, Transactions of Civil Engineering, 1-12, (2021).
  • [52] Mohiddin, S.K., Prasanth, C., Rathore, G.S.and Hemanth, C.,“Mathematical analysis of adaptive queue length-based traffic signal control”, Lecture Notes in Electrical Engineering, (2019).
  • [53] Akçelik, R., Smit, R.and Besley, M., “Recalibration of a vehicle power model for fuel and emission estimation and its effect on assessment of alternative intersection treatments”, 4th International Roundabout Conference, Seattle, WA, USA, (2014).
There are 53 citations in total.

Details

Primary Language Turkish
Subjects Transportation and Traffic, Industrial Engineering
Journal Section Research Article
Authors

Tuğçe İnağ 0000-0002-8800-6727

Murat Arıkan 0000-0003-1437-8939

Early Pub Date May 16, 2024
Publication Date
Submission Date October 2, 2023
Published in Issue Year 2024 EARLY VIEW

Cite

APA İnağ, T., & Arıkan, M. (2024). KAVŞAKLARDA TRAFİK IŞIK OPTİMİZASYONU: ANKARA İLİ’NDE BİR UYGULAMA. Politeknik Dergisi1-1. https://doi.org/10.2339/politeknik.1369924
AMA İnağ T, Arıkan M. KAVŞAKLARDA TRAFİK IŞIK OPTİMİZASYONU: ANKARA İLİ’NDE BİR UYGULAMA. Politeknik Dergisi. Published online May 1, 2024:1-1. doi:10.2339/politeknik.1369924
Chicago İnağ, Tuğçe, and Murat Arıkan. “KAVŞAKLARDA TRAFİK IŞIK OPTİMİZASYONU: ANKARA İLİ’NDE BİR UYGULAMA”. Politeknik Dergisi, May (May 2024), 1-1. https://doi.org/10.2339/politeknik.1369924.
EndNote İnağ T, Arıkan M (May 1, 2024) KAVŞAKLARDA TRAFİK IŞIK OPTİMİZASYONU: ANKARA İLİ’NDE BİR UYGULAMA. Politeknik Dergisi 1–1.
IEEE T. İnağ and M. Arıkan, “KAVŞAKLARDA TRAFİK IŞIK OPTİMİZASYONU: ANKARA İLİ’NDE BİR UYGULAMA”, Politeknik Dergisi, pp. 1–1, May 2024, doi: 10.2339/politeknik.1369924.
ISNAD İnağ, Tuğçe - Arıkan, Murat. “KAVŞAKLARDA TRAFİK IŞIK OPTİMİZASYONU: ANKARA İLİ’NDE BİR UYGULAMA”. Politeknik Dergisi. May 2024. 1-1. https://doi.org/10.2339/politeknik.1369924.
JAMA İnağ T, Arıkan M. KAVŞAKLARDA TRAFİK IŞIK OPTİMİZASYONU: ANKARA İLİ’NDE BİR UYGULAMA. Politeknik Dergisi. 2024;:1–1.
MLA İnağ, Tuğçe and Murat Arıkan. “KAVŞAKLARDA TRAFİK IŞIK OPTİMİZASYONU: ANKARA İLİ’NDE BİR UYGULAMA”. Politeknik Dergisi, 2024, pp. 1-1, doi:10.2339/politeknik.1369924.
Vancouver İnağ T, Arıkan M. KAVŞAKLARDA TRAFİK IŞIK OPTİMİZASYONU: ANKARA İLİ’NDE BİR UYGULAMA. Politeknik Dergisi. 2024:1-.

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