A Controlling Traffic Light system using Fuzzy logic
DOI:
https://doi.org/10.29304/jqcm.2023.15.3.1271Keywords:
Fuzzy logic, Gaussian mixture classifier., traffic control system, image processingAbstract
Automatic control systems are a new advanced system uses computers and hardware controllers to act as a driving system. Increasing in cars numbers while we have the same infrastructure caused a large traffic problem so we need automatic adaptive controllers to control the open and close tasks of traffic light system. Fuzzy Logic is a conversation from classical logic with values of 0 for false and 1 for true to a range of values between 0 and 1.
This study aims to create an adaptive traffic control system using fuzzy logic and image processing, we have a camera on each traffic light to calculate the number of cars there and then we feed the number of cars to a fuzzy logic system to decide which traffic light must become on
Downloads
Download data is not yet available.
References
[1] Hartanti, Dian & Aziza, Rosida & Siswipraptini, Puji. “Optimization of smart traffic lights to prevent traffic congestion using fuzzy logic”, Telkomnika (Telecommunication Computing Electronics and Control). 17. 320-327,2019, doi: 10.12928/TELKOMNIKA.v17i1.10129
[2] Qadri, S.S.S.M., Gökçe, M.A. & Öner,” E. State-of-art review of traffic signal control methods: challenges and opportunities”,. Eur. Transp. Res. Rev. 12, 55 ,2020, doi.org/10.1186/s12544-020-00439-1.
[3] M. Mahali, B. Wulandari, E. Marpanaji, U. Rochayati, S. A. Dewanto, and N. Hasanah, “Smart traffic light based on IoT and mBaaS using high priority vehicles method,” Int. Conf. Electr. Eng. Comput. Sci. Informatics, vol. 2018-Octob, no. 22, pp. 703–707, 2018, doi: 10.1109/EECSI.2018.8752694.
[4] Eom, Myungeun & Kim, Byung-In. ,” The traffic signal control problem for intersections: a review”. European Transport Research Review. 12. 50.,2020, doi: 10.1186/s12544-020-00440-8
[5] Noaeen, Mohammad & Naik, Atharva & Goodman, Liana & Crebo, Jared & Abrar, Taimoor & Shakeri, Zahra & Bazzan, Ana & Far, Behroun,” Reinforcement learning in urban network traffic signal control: A systematic literature review”. Expert Systems with Applications eswa.,2022.,116830..doi: 199. 116830. 10.1016/j.
[6] D.Patel, & Y.Rohilla, ,”Infrared sensor based self–adaptive traffic signal system using arduino board”. In 2020 12th International Conference on Computational Intelligence and Communication Networks (CICN) (pp. 175-181) IEEE., 2020, September, doi: 10.1109/cicn49253.2020.9242560
[7] M.jha, SH. shukla,” design of fuzzy logic traffic controller for isolated intersections with emergency vehicle priority system using matlab simulation”https://arxiv.org/ftp/arxiv/papers/1405/1405.0936.pdf.
[8] A.Nigam., M.Chaturvedi, & S.Srivastava ,”An Empirical Study on Parameters Affecting Traffic Stream Variables Under Rainy Conditions”. In 2022 14th International Conference on COMmunication Systems & NET work S (COMSNETS) (pp. 818-823). IEEE. 2022, January.
[9] S. komsiyah,, E. desvania, “traffic lights analysis and simulation using fuzzy inference system of mamdani on three-signaled intersections”., science direct journal, volume 179, 2021, pages 268-280, https://doi.org/10.1016/j.procs.2021.01.006,
[10] T. dereli, C. çetinkaya, N. çelik, “designing a fuzzy logic controller for a single intersection: a case study in Gaziantep”, sigma j eng & nat sci 36 (3), 2018, 767-781, 2018.
[11] C.Shirke., N.Sabar, E.Chung; A.,Bhaska,”. Metaheuristic approach for designing robust traffic signal timings to effectively serve varying traffic demand”, J. Intell. Transp. Syst. 26, 343–355, 2022,doi: 10.5772/intechopen.99395
[12] C.Nie.; H.Wei., J.Shi.; Zhang, “M. Optimizing actuated traffic signal control using license plate recognition data: Methods for modeling and algorithm development”, Transp. Res. Interdiscip. Perspect. ,2021, doi.org/10.1016/j.trip.2021.100319
[13] S.Park., E.Han.; S.Park.,H.Jeong; I.Yun,” Deep Q-network-based traffic signal control models. PLoS ONE”, 2021, 16, e256405, doi.org/10.1371/journal.pone.0256405.
[14] D.Hartanti, R. Ningrum, K.Djunaidi,”Designing Traffic Light Simulator Based on Queue Control Movement “,in Indonesia Perancangan Simulator Traffic Light Berdasarkan Gerakan Kendali Antrian).FIFO. 2018; (10) ,doi: 10.22441/fifo.v10i1.2938
[15]T. Mahmood , A. MEM, A.Durdu,” A two stage fuzzy logic adaptive traffic signal control for an isolated intersection based on real data using SUMO simulator”,. Electron Comm Eng. 3: 656-659,2019, [doi:10.31142/ijtsrd23873]
[16] L.Dewasme ,T.Jiang; Z.Wang,F.Chen,”, Urban Traffic Signals Timing at Four-Phase Signalized Intersection Based on Optimized Two-Stage Fuzzy Control Scheme”. Math. Probl. Eng. 2021, doi: 10.1155/2021/6693562
[17] S. Parekh, N. Dhami, S. Patel, and J. Undavia, “Traffic signal automation through iot by sensing and detecting traffic intensity through ir sensors,” Smart Innov. Syst. Technol., vol. 106, pp. 53–65, 2019, doi: 10.1007/978-981-13-1742-2_6.
[18] S.km.,K.Priyadharshini, “Automatic Traffic Control System Based on the Vehicular Density,” Int. Res. J. Eng. Technol., vol. 06, no. 04, pp. 1–3, 2019.
[19]R. Jimenez-Moreno, J. E. M. Baquero, and L. A. R. Umana, “Ambulance detection for smart traffic light applications with fuzzy controller,” Int. J. Electr. Comput. Eng., vol. 12, no. 5, pp. 4876–4882, 2022, doi: 10.11591/ijece.v12i5.pp4876-4882.
[20] A. N. A. Yusuf, A. S. Arifin, and F. Y. Zulkifli, “Recent development of smart traffic lights,” IAES Int. J. Artif. Intell., vol. 10, no. 1, pp. 224–233, 2021, doi: 10.11591/ijai.v10.i1.pp224-233.
[21] R. Yuliani Kartikasari, G. Prakarsa,and D. Pradeka, “ Optimization of Traffic Light Control Using Fuzzy Logic Sugeno Method”, International Journal of Global Operations Research, Vol. 1, No. 2, pp. 51-61, 2020. DOI: 10.47194/ijgor.v1i2.37
[22] Hlavacek, J., & Gotthans, J. (2022, April). Evaluation of Traffic Crossings Situations using Machine Learning. In 2022 32nd International Conference Radioelektro, DOI: 10.3844/jcssp.2022.1085.1099
[23] N. A. Yusuf, A. S. Arifin, and F. Y. Zulkifli, “Recent development of smart traffic lights,” IAES Int. J. Artif. Intell., vol. 10, no. 1, pp. 224–233, 2021, doi: 10.11591/ijai.v10.i1.pp224-233.
[24] R. P. Prasetya, “Implementasi Fuzzy Mamdani Pada Lampu Lalu Lintas Secara Adaptif Untuk Meminimalkan Waktu Tunggu Pengguna Jalan,” J. Mnemon., vol. 3, no. 1, pp. 24–29, 2020, doi: 10.36040/mnemonic.v3i1.2526.
[25] O. Avatefipour and F. Sadry, “Traffic Management System Using IoT Technology - A Comparative Review,” IEEE Int. Conf. Electro Inf. Technol., vol. 2018-May, pp. 1041–1047, 2018, doi: 10.1109/EIT.2018.8500246.
[26] S. Mohanaselvi and B. Shanpriya, “Application of fuzzy logic to control traffic signals,” AIP Conf. Proc., vol. 2112, no. June, 2019, doi: 10.1063/1.5112230
[27] A. Chabchoub, A. Hamouda, S. Al-Ahmadi, and A. Cherif, “Intelligent Traffic Light Controller using Fuzzy Logic and Image Processing,” Int. J. Adv. Comput. Sci. Appl., vol. 12, no. 4, pp. 396–399, 2021, doi: 10.14569/IJACSA.2021.0120450.
[28] M. Shelke, A. Malhotra, and P. N. Mahalle, “Fuzzy priority based intelligent traffic congestion control and emergency vehicle management using congestion-aware routing algorithm,” J. Ambient Intell. Humaniz. Comput., no. 0123456789, 2019, doi: 10.1007/s12652-019-01523-8.
[29] R. Jimenez-Moreno, J. E. M. Baquero, and L. A. R. Umana, “Ambulance detection for smart traffic light applications with fuzzy controller,” Int. J. Electr. Comput. Eng., vol. 12, no. 5, pp. 4876–4882, 2022, doi: 10.11591/ijece.v12i5.pp4876-4882.
[30] P. Devi and S. Anila, “Intelligent Ambulance with Automatic Traffic Control,” 2020 Int. Conf. Comput. Inf. Technol. ICCIT 2020, pp. 374–377, 2020, doi: 10.1109/ICCIT-144147971.2020.9213796.
[2] Qadri, S.S.S.M., Gökçe, M.A. & Öner,” E. State-of-art review of traffic signal control methods: challenges and opportunities”,. Eur. Transp. Res. Rev. 12, 55 ,2020, doi.org/10.1186/s12544-020-00439-1.
[3] M. Mahali, B. Wulandari, E. Marpanaji, U. Rochayati, S. A. Dewanto, and N. Hasanah, “Smart traffic light based on IoT and mBaaS using high priority vehicles method,” Int. Conf. Electr. Eng. Comput. Sci. Informatics, vol. 2018-Octob, no. 22, pp. 703–707, 2018, doi: 10.1109/EECSI.2018.8752694.
[4] Eom, Myungeun & Kim, Byung-In. ,” The traffic signal control problem for intersections: a review”. European Transport Research Review. 12. 50.,2020, doi: 10.1186/s12544-020-00440-8
[5] Noaeen, Mohammad & Naik, Atharva & Goodman, Liana & Crebo, Jared & Abrar, Taimoor & Shakeri, Zahra & Bazzan, Ana & Far, Behroun,” Reinforcement learning in urban network traffic signal control: A systematic literature review”. Expert Systems with Applications eswa.,2022.,116830..doi: 199. 116830. 10.1016/j.
[6] D.Patel, & Y.Rohilla, ,”Infrared sensor based self–adaptive traffic signal system using arduino board”. In 2020 12th International Conference on Computational Intelligence and Communication Networks (CICN) (pp. 175-181) IEEE., 2020, September, doi: 10.1109/cicn49253.2020.9242560
[7] M.jha, SH. shukla,” design of fuzzy logic traffic controller for isolated intersections with emergency vehicle priority system using matlab simulation”https://arxiv.org/ftp/arxiv/papers/1405/1405.0936.pdf.
[8] A.Nigam., M.Chaturvedi, & S.Srivastava ,”An Empirical Study on Parameters Affecting Traffic Stream Variables Under Rainy Conditions”. In 2022 14th International Conference on COMmunication Systems & NET work S (COMSNETS) (pp. 818-823). IEEE. 2022, January.
[9] S. komsiyah,, E. desvania, “traffic lights analysis and simulation using fuzzy inference system of mamdani on three-signaled intersections”., science direct journal, volume 179, 2021, pages 268-280, https://doi.org/10.1016/j.procs.2021.01.006,
[10] T. dereli, C. çetinkaya, N. çelik, “designing a fuzzy logic controller for a single intersection: a case study in Gaziantep”, sigma j eng & nat sci 36 (3), 2018, 767-781, 2018.
[11] C.Shirke., N.Sabar, E.Chung; A.,Bhaska,”. Metaheuristic approach for designing robust traffic signal timings to effectively serve varying traffic demand”, J. Intell. Transp. Syst. 26, 343–355, 2022,doi: 10.5772/intechopen.99395
[12] C.Nie.; H.Wei., J.Shi.; Zhang, “M. Optimizing actuated traffic signal control using license plate recognition data: Methods for modeling and algorithm development”, Transp. Res. Interdiscip. Perspect. ,2021, doi.org/10.1016/j.trip.2021.100319
[13] S.Park., E.Han.; S.Park.,H.Jeong; I.Yun,” Deep Q-network-based traffic signal control models. PLoS ONE”, 2021, 16, e256405, doi.org/10.1371/journal.pone.0256405.
[14] D.Hartanti, R. Ningrum, K.Djunaidi,”Designing Traffic Light Simulator Based on Queue Control Movement “,in Indonesia Perancangan Simulator Traffic Light Berdasarkan Gerakan Kendali Antrian).FIFO. 2018; (10) ,doi: 10.22441/fifo.v10i1.2938
[15]T. Mahmood , A. MEM, A.Durdu,” A two stage fuzzy logic adaptive traffic signal control for an isolated intersection based on real data using SUMO simulator”,. Electron Comm Eng. 3: 656-659,2019, [doi:10.31142/ijtsrd23873]
[16] L.Dewasme ,T.Jiang; Z.Wang,F.Chen,”, Urban Traffic Signals Timing at Four-Phase Signalized Intersection Based on Optimized Two-Stage Fuzzy Control Scheme”. Math. Probl. Eng. 2021, doi: 10.1155/2021/6693562
[17] S. Parekh, N. Dhami, S. Patel, and J. Undavia, “Traffic signal automation through iot by sensing and detecting traffic intensity through ir sensors,” Smart Innov. Syst. Technol., vol. 106, pp. 53–65, 2019, doi: 10.1007/978-981-13-1742-2_6.
[18] S.km.,K.Priyadharshini, “Automatic Traffic Control System Based on the Vehicular Density,” Int. Res. J. Eng. Technol., vol. 06, no. 04, pp. 1–3, 2019.
[19]R. Jimenez-Moreno, J. E. M. Baquero, and L. A. R. Umana, “Ambulance detection for smart traffic light applications with fuzzy controller,” Int. J. Electr. Comput. Eng., vol. 12, no. 5, pp. 4876–4882, 2022, doi: 10.11591/ijece.v12i5.pp4876-4882.
[20] A. N. A. Yusuf, A. S. Arifin, and F. Y. Zulkifli, “Recent development of smart traffic lights,” IAES Int. J. Artif. Intell., vol. 10, no. 1, pp. 224–233, 2021, doi: 10.11591/ijai.v10.i1.pp224-233.
[21] R. Yuliani Kartikasari, G. Prakarsa,and D. Pradeka, “ Optimization of Traffic Light Control Using Fuzzy Logic Sugeno Method”, International Journal of Global Operations Research, Vol. 1, No. 2, pp. 51-61, 2020. DOI: 10.47194/ijgor.v1i2.37
[22] Hlavacek, J., & Gotthans, J. (2022, April). Evaluation of Traffic Crossings Situations using Machine Learning. In 2022 32nd International Conference Radioelektro, DOI: 10.3844/jcssp.2022.1085.1099
[23] N. A. Yusuf, A. S. Arifin, and F. Y. Zulkifli, “Recent development of smart traffic lights,” IAES Int. J. Artif. Intell., vol. 10, no. 1, pp. 224–233, 2021, doi: 10.11591/ijai.v10.i1.pp224-233.
[24] R. P. Prasetya, “Implementasi Fuzzy Mamdani Pada Lampu Lalu Lintas Secara Adaptif Untuk Meminimalkan Waktu Tunggu Pengguna Jalan,” J. Mnemon., vol. 3, no. 1, pp. 24–29, 2020, doi: 10.36040/mnemonic.v3i1.2526.
[25] O. Avatefipour and F. Sadry, “Traffic Management System Using IoT Technology - A Comparative Review,” IEEE Int. Conf. Electro Inf. Technol., vol. 2018-May, pp. 1041–1047, 2018, doi: 10.1109/EIT.2018.8500246.
[26] S. Mohanaselvi and B. Shanpriya, “Application of fuzzy logic to control traffic signals,” AIP Conf. Proc., vol. 2112, no. June, 2019, doi: 10.1063/1.5112230
[27] A. Chabchoub, A. Hamouda, S. Al-Ahmadi, and A. Cherif, “Intelligent Traffic Light Controller using Fuzzy Logic and Image Processing,” Int. J. Adv. Comput. Sci. Appl., vol. 12, no. 4, pp. 396–399, 2021, doi: 10.14569/IJACSA.2021.0120450.
[28] M. Shelke, A. Malhotra, and P. N. Mahalle, “Fuzzy priority based intelligent traffic congestion control and emergency vehicle management using congestion-aware routing algorithm,” J. Ambient Intell. Humaniz. Comput., no. 0123456789, 2019, doi: 10.1007/s12652-019-01523-8.
[29] R. Jimenez-Moreno, J. E. M. Baquero, and L. A. R. Umana, “Ambulance detection for smart traffic light applications with fuzzy controller,” Int. J. Electr. Comput. Eng., vol. 12, no. 5, pp. 4876–4882, 2022, doi: 10.11591/ijece.v12i5.pp4876-4882.
[30] P. Devi and S. Anila, “Intelligent Ambulance with Automatic Traffic Control,” 2020 Int. Conf. Comput. Inf. Technol. ICCIT 2020, pp. 374–377, 2020, doi: 10.1109/ICCIT-144147971.2020.9213796.
Downloads
Published
2023-09-30
How to Cite
Gdeeb, R. T. (2023). A Controlling Traffic Light system using Fuzzy logic. Journal of Al-Qadisiyah for Computer Science and Mathematics, 15(3), Comp Page 141–153. https://doi.org/10.29304/jqcm.2023.15.3.1271
Issue
Section
Computer Articles
