Simulation and optimization of traffic lights for vehicles flow in high traffic areas
In today’s world, the increase of the population in the cities cause that the transportation of freight and passenger increase also increasing the number of automobiles and vehicles on the streets, directly impacting traffic on the roads and more in the critical points of the street, the intercessio...
- Autores:
-
Ramirez-Polo, Luis Eduardo
Jimenez Barros, Miguel Angel
Varela Narváez, Vladimir
Parodi, Carlos
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2022
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/9367
- Acceso en línea:
- https://hdl.handle.net/11323/9367
https://doi.org/10.1016/j.procs.2021.12.284
https://repositorio.cuc.edu.co/
- Palabra clave:
- Simulation
Optimization
Traffic light scheduling
- Rights
- openAccess
- License
- Atribución 4.0 Internacional (CC BY 4.0)
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Simulation and optimization of traffic lights for vehicles flow in high traffic areas |
| title |
Simulation and optimization of traffic lights for vehicles flow in high traffic areas |
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Simulation and optimization of traffic lights for vehicles flow in high traffic areas Simulation Optimization Traffic light scheduling |
| title_short |
Simulation and optimization of traffic lights for vehicles flow in high traffic areas |
| title_full |
Simulation and optimization of traffic lights for vehicles flow in high traffic areas |
| title_fullStr |
Simulation and optimization of traffic lights for vehicles flow in high traffic areas |
| title_full_unstemmed |
Simulation and optimization of traffic lights for vehicles flow in high traffic areas |
| title_sort |
Simulation and optimization of traffic lights for vehicles flow in high traffic areas |
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Ramirez-Polo, Luis Eduardo Jimenez Barros, Miguel Angel Varela Narváez, Vladimir Parodi, Carlos |
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Ramirez-Polo, Luis Eduardo Jimenez Barros, Miguel Angel Varela Narváez, Vladimir Parodi, Carlos |
| dc.subject.proposal.eng.fl_str_mv |
Simulation Optimization Traffic light scheduling |
| topic |
Simulation Optimization Traffic light scheduling |
| description |
In today’s world, the increase of the population in the cities cause that the transportation of freight and passenger increase also increasing the number of automobiles and vehicles on the streets, directly impacting traffic on the roads and more in the critical points of the street, the intercessions. To improve mobility at these intersections is necessary to appropriate coordination of signals and traffic lights that regulate traffic in various directions. This research shows the methodology to find the correct time of the lights to reduce the time in traffic of the vehicles on one of the principals and most congested roads in the city of Barranquilla, Colombia, using simulation and optimization techniques, were found the ideal cycle times and the different times of each color of the traffic lights to reduce the time in the line of the vehicles. This paper presents a literature review of similar works, a complete description of the case to be investigated, the construction of the simulation model required for the evaluation of the improvements, the optimization model developed, and the conclusions to which reached in the same way, it proposes a structure that can be replicated in any scenario that handles similar conditions |
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2022-07-14T16:45:07Z |
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2022-01-26 |
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Luis Ramirez-Polo, Miguel A. Jimenez-Barros, Vladimir Varela Narváez, Carlos Parodi Daza,Simulation and Optimization of Traffic Lights For Vehicles Flow in High Traffic Areas, Procedia Computer Science, Volume 198, 2022, Pages 548-553, ISSN 1877-0509, https://doi.org/10.1016/j.procs.2021.12.284. |
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https://repositorio.cuc.edu.co/ |
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Luis Ramirez-Polo, Miguel A. Jimenez-Barros, Vladimir Varela Narváez, Carlos Parodi Daza,Simulation and Optimization of Traffic Lights For Vehicles Flow in High Traffic Areas, Procedia Computer Science, Volume 198, 2022, Pages 548-553, ISSN 1877-0509, https://doi.org/10.1016/j.procs.2021.12.284. 18770509 10.1016/j.procs.2021.12.284 Corporación Universidad de la Costa REDICUC - Repositorio CUC |
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[1] N. Casas, “Deep deterministic policy gradient for urban traffic light control,” arXiv. arXiv, Mar. 27, 2017. [2] X. Liang, X. Du, G. Wang, and Z. Han, “Deep reinforcement learning for traffic light control in vehicular networks,” arXiv. 2018, doi: 10.1109/TVT.2018.2890726. [3] S. S. Mousavi, M. Schukat, and E. Howley, “Traffic light control using deep policy-gradient and value-function-based reinforcement learning,” in IET Intelligent Transport Systems, 2017, vol. 11, no. 7, doi: 10.1049/iet-its.2017.0153. [4] J. Jin, X. Ma, and I. Kosonen, “An intelligent control system for traffic lights with simulation-based evaluation,” Control Eng. Pract., vol. 58, 2017, doi: 10.1016/j.conengprac.2016.09.009. [5] Yamanoi et al, “United States Patent: TRAFFIC LIGHT RECOGNITION DEVICE AND TRAFFIC LIGHT RECOGNITION METHOD,” 2019. [6] M.-A. Lebre, F. Le Mouël, E. Ménard, A. Garnault, B. Bradaï, and V. Picron, “Real scenario and simulations on GLOSA traffic light system for reduced CO2 emissions, waiting time and travel time,” 2015. Accessed: Apr. 21, 2021. [Online]. Available: https://arxiv.org/abs/1506.01965. [7] C. Suthaputchakun and Z. Sun, “A novel traffic light scheduling based on TLVC and vehicles’ priority for reducing fuel consumption and CO 2 emission,” IEEE Syst. J., vol. 12, no. 2, 2018, doi: 10.1109/JSYST.2015.2500587. [8] L. Xue, Y. Yang, and D. Dong, “Roadside Infrastructure Planning Scheme for the Urban Vehicular Networks,” Transp. Res. Procedia, vol. 25, pp. 1380–1396, Jan. 2017, doi: 10.1016/J.TRPRO.2017.05.163. [9] L. Guevara and F. A. Cheein, “The Role of 5G Technologies: Challenges in Smart Cities and Intelligent Transportation Systems,” Sustain. 2020, Vol. 12, Page 6469, vol. 12, no. 16, p. 6469, Aug. 2020, doi: 10.3390/SU12166469. [10] L. E. Ramírez Polo, A. R. Santander-Mercado, and M. A. Jimenez-Barros, “Development Methodology to Share Vehicles Optimizing the Variability of the Mileage,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Oct. 2020, vol. 12133 LNCS, pp. 426–435, doi: 10.1007/978-3-030-47679-3_36. [11] P. J. Vidal and A. C. Olivera, “Management of urban traffic flow based on traffic lights scheduling optimization,” IEEE Lat. Am. Trans., vol. 17, no. 1, pp. 102–110, Jan. 2019, doi: 10.1109/TLA.2019.8826701. [12] M. Lima, M. de Alcantara, A. Rosenthal, and R. Deliza, “Effectiveness of traffic light system on Brazilian consumers perception of food healthfulness,” Food Sci. Hum. Wellness, vol. 8, no. 4, pp. 368–374, Dec. 2019, doi: 10.1016/j.fshw.2019.10.001. [13] R. Li, C. Zheng, and W. Li, “Optimization Model of Transit Signal Priority Control for Intersection and Downstream Bus Stop,” Math. Probl. Eng., vol. 2016, 2016, doi: 10.1155/2016/9487190. [14] L. Ramírez-Polo, F. D. J. Medoza Mola, A. Parody, F. Gonzalez Solano, L. J. Castro Bolaño, and M. A. Jimenez Barros, “Simulation model to find the slack time for schedule of the transit operations in off-peak time on the main terminal of massive transport system,” Espacios, vol. 38, no. 13, 2017. |
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Ramirez-Polo, Luis EduardoJimenez Barros, Miguel AngelVarela Narváez, VladimirParodi, Carlos2022-07-14T16:45:07Z2022-07-14T16:45:07Z2022-01-26Luis Ramirez-Polo, Miguel A. Jimenez-Barros, Vladimir Varela Narváez, Carlos Parodi Daza,Simulation and Optimization of Traffic Lights For Vehicles Flow in High Traffic Areas, Procedia Computer Science, Volume 198, 2022, Pages 548-553, ISSN 1877-0509, https://doi.org/10.1016/j.procs.2021.12.284.18770509https://hdl.handle.net/11323/9367https://doi.org/10.1016/j.procs.2021.12.28410.1016/j.procs.2021.12.284Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/In today’s world, the increase of the population in the cities cause that the transportation of freight and passenger increase also increasing the number of automobiles and vehicles on the streets, directly impacting traffic on the roads and more in the critical points of the street, the intercessions. To improve mobility at these intersections is necessary to appropriate coordination of signals and traffic lights that regulate traffic in various directions. This research shows the methodology to find the correct time of the lights to reduce the time in traffic of the vehicles on one of the principals and most congested roads in the city of Barranquilla, Colombia, using simulation and optimization techniques, were found the ideal cycle times and the different times of each color of the traffic lights to reduce the time in the line of the vehicles. This paper presents a literature review of similar works, a complete description of the case to be investigated, the construction of the simulation model required for the evaluation of the improvements, the optimization model developed, and the conclusions to which reached in the same way, it proposes a structure that can be replicated in any scenario that handles similar conditions6 páginasapplication/pdfengElsevier BVNetherlandsAtribución 4.0 Internacional (CC BY 4.0)© 2021 The Authors. Published by Elsevier B.https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Simulation and optimization of traffic lights for vehicles flow in high traffic areasArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARThttp://purl.org/coar/version/c_970fb48d4fbd8a85https://www.sciencedirect.com/science/article/pii/S1877050921025230?via%3DihubProcedia Computer Science[1] N. Casas, “Deep deterministic policy gradient for urban traffic light control,” arXiv. arXiv, Mar. 27, 2017.[2] X. Liang, X. Du, G. Wang, and Z. Han, “Deep reinforcement learning for traffic light control in vehicular networks,” arXiv. 2018, doi: 10.1109/TVT.2018.2890726.[3] S. S. Mousavi, M. Schukat, and E. Howley, “Traffic light control using deep policy-gradient and value-function-based reinforcement learning,” in IET Intelligent Transport Systems, 2017, vol. 11, no. 7, doi: 10.1049/iet-its.2017.0153.[4] J. Jin, X. Ma, and I. Kosonen, “An intelligent control system for traffic lights with simulation-based evaluation,” Control Eng. Pract., vol. 58, 2017, doi: 10.1016/j.conengprac.2016.09.009.[5] Yamanoi et al, “United States Patent: TRAFFIC LIGHT RECOGNITION DEVICE AND TRAFFIC LIGHT RECOGNITION METHOD,” 2019.[6] M.-A. Lebre, F. Le Mouël, E. Ménard, A. Garnault, B. Bradaï, and V. Picron, “Real scenario and simulations on GLOSA traffic light system for reduced CO2 emissions, waiting time and travel time,” 2015. Accessed: Apr. 21, 2021. [Online]. Available: https://arxiv.org/abs/1506.01965.[7] C. Suthaputchakun and Z. Sun, “A novel traffic light scheduling based on TLVC and vehicles’ priority for reducing fuel consumption and CO 2 emission,” IEEE Syst. J., vol. 12, no. 2, 2018, doi: 10.1109/JSYST.2015.2500587.[8] L. Xue, Y. Yang, and D. Dong, “Roadside Infrastructure Planning Scheme for the Urban Vehicular Networks,” Transp. Res. Procedia, vol. 25, pp. 1380–1396, Jan. 2017, doi: 10.1016/J.TRPRO.2017.05.163.[9] L. Guevara and F. A. Cheein, “The Role of 5G Technologies: Challenges in Smart Cities and Intelligent Transportation Systems,” Sustain. 2020, Vol. 12, Page 6469, vol. 12, no. 16, p. 6469, Aug. 2020, doi: 10.3390/SU12166469.[10] L. E. Ramírez Polo, A. R. Santander-Mercado, and M. A. Jimenez-Barros, “Development Methodology to Share Vehicles Optimizing the Variability of the Mileage,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Oct. 2020, vol. 12133 LNCS, pp. 426–435, doi: 10.1007/978-3-030-47679-3_36.[11] P. J. Vidal and A. C. Olivera, “Management of urban traffic flow based on traffic lights scheduling optimization,” IEEE Lat. Am. Trans., vol. 17, no. 1, pp. 102–110, Jan. 2019, doi: 10.1109/TLA.2019.8826701.[12] M. Lima, M. de Alcantara, A. Rosenthal, and R. Deliza, “Effectiveness of traffic light system on Brazilian consumers perception of food healthfulness,” Food Sci. Hum. Wellness, vol. 8, no. 4, pp. 368–374, Dec. 2019, doi: 10.1016/j.fshw.2019.10.001.[13] R. Li, C. Zheng, and W. Li, “Optimization Model of Transit Signal Priority Control for Intersection and Downstream Bus Stop,” Math. Probl. Eng., vol. 2016, 2016, doi: 10.1155/2016/9487190.[14] L. Ramírez-Polo, F. D. J. Medoza Mola, A. Parody, F. Gonzalez Solano, L. J. Castro Bolaño, and M. A. Jimenez Barros, “Simulation model to find the slack time for schedule of the transit operations in off-peak time on the main terminal of massive transport system,” Espacios, vol. 38, no. 13, 2017.553548198SimulationOptimizationTraffic light schedulingPublicationORIGINAL1-s2.0-S1877050921025230-main.pdf1-s2.0-S1877050921025230-main.pdfapplication/pdf754755https://repositorio.cuc.edu.co/bitstreams/ae8affbc-77a6-405f-a976-d76294a7fa81/download24b3a8176163683c15bd1de7a2d0c320MD51LICENSElicense.txtlicense.txttext/plain; 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