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Yaya Geçitlerinde Dinamik Trafik Sinyali Bölünmüş Kontrol Yöntemi

Year 2022, , 21 - 26, 31.12.2022
https://doi.org/10.31590/ejosat.1216804

Abstract

Karayollarında araç trafiğinin güvenliğini sağlamak ve kolaylaştırmak için trafik kontrolü çok önemlidir. Karayolu trafiğini kolaylaştırmak amacıyla trafik ışıklarının kontrol parametrelerinin etkin bir şekilde nasıl değiştirilebileceğine dair birçok çalışma mevcuttur, ancak bu tür araştırmaların gözlem hedeflerinin temelini araçlaroluşturmaktadır. Kentsel alanlarda trafik sıkışıklığı ciddi bir sorun olmakla birlikte, otomobiller ve yayalar arasındaki müdahale gerçek trafiği oluşturarak yayaların da dikkate alınmasını gerektiren hayati bir unsur haline gelir. Bu çalışmada, hem araç hem de yaya trafiğini hesaba katarak yaya trafiğini artıracak parametre tabanlı trafik sinyali ayrım kontrolü için bir strateji önerilmiştir.

References

  • Akyol, G., Silgu, M. A., & Celikoglu, H. B. (2019). Pedestrian-friendly traffic signal control using Eclipse SUMO. In Proceedings of the SUMO User Conference (pp. 101-106).
  • Alegre, L. N., Ziemke, T., & Bazzan, A. L. (2021). Using reinforcement learning to control traffic signals in a real-world scenario: an approach based on linear function approximation. IEEE Transactions on Intelligent Transportation Systems.
  • Artal-Villa, L., & Olaverri-Monreal, C. (2019, April). Vehicle-pedestrian interaction in SUMO and unity3D. In World Conference on Information Systems and Technologies (pp. 198-207). Springer, Cham.
  • Han, G., Zheng, Q., Liao, L., Tang, P., Li, Z., & Zhu, Y. (2022). Deep Reinforcement Learning for Intersection Signal Control Considering Pedestrian Behavior. Electronics, 11(21), 3519.
  • Koti, R. B., & Kakkasageri, M. S. (2021). Multi Agent Assisted Safety Information Dissemination Scheme for V2V Communication in VANETs: Intelligent Agent Approach. International Journal of Intelligent Systems and Applications (IJISA), 13(4), 49-62.
  • Malena, K., Link, C., Bußemas, L., Gausemeier, S., & Trächtler, A. (2022). Traffic Estimation and MPC-Based Traffic Light System Control in Realistic Real-Time Traffic Environments. In International Conference on Vehicle Technology and Intelligent Transport Systems, International Conference on Smart Cities and Green ICT Systems (pp. 232-254). Springer, Cham.
  • Mathiane, M., Tu, C., Owola, P. A., & Nawej, M. C. (2022). A SUMO Simulation Study on VANET-Based Adaptive Traffic Light Control System. In Advances in Electrical and Computer Technologies (pp. 225-237). Springer, Singapore.
  • Qu, D., Li, H., Liu, H., Wang, S., & Zhang, K. (2022). Crosswalk safety warning system for pedestrians to cross the street intelligently. Sustainability, 14(16), 10223.
  • Sun, Q., He, C., Wang, Y., Liu, H., Ma, F., & Wei, X. (2022). Reducing violation behaviors of pedestrians considering group interests of travelers at signalized crosswalk. Physica A: Statistical Mechanics and its Applications, 594, 127023.
  • Tomar, I., Sreedevi, I., & Pandey, N. (2022). State-of-Art Review of Traffic Light Synchronization for Intelligent Vehicles: Current Status, Challenges, and Emerging Trends. Electronics, 11(3), 465.
  • Trächtler, A. (2022). Traffic Estimation and MPC-Based Traffic Light System Control in Realistic Real-Time Traffic Environments. In Smart Cities, Green Technologies, and Intelligent Transport Systems: 10th International Conference, SMARTGREENS 2021, and 7th International Conference, VEHITS 2021, Virtual Event, April 28-30, 2021, Revised Selected Papers (p. 232). Springer Nature.
  • Wang, T., Cao, J., & Hussain, A. (2021). Adaptive Traffic Signal Control for large-scale scenario with Cooperative Group-based Multi-agent reinforcement learning. Transportation research part C: emerging technologies, 125, 103046.

Dynamic Traffic Signal Split Control Method at Pedestrian Crossings

Year 2022, , 21 - 26, 31.12.2022
https://doi.org/10.31590/ejosat.1216804

Abstract

In order to facilitate and guarantee the safety of vehicular traffic on roadways, traffic control is crucial. Currently, there is a lot of study on how to effectively alter the control parameters of traffic lights for the aim of facilitating road traffic, but the observation targets of such research are restricted to vehicles. Traffic congestion in urban areas is a severe issue. However, the interference between automobiles and pedestrians creates the actual traffic, making pedestrians a vital aspect to take into account. In this article, we suggest a strategy for parameter-based traffic signal split control that will increase pedestrian traffic by taking both vehicle and pedestrian traffic into account.

References

  • Akyol, G., Silgu, M. A., & Celikoglu, H. B. (2019). Pedestrian-friendly traffic signal control using Eclipse SUMO. In Proceedings of the SUMO User Conference (pp. 101-106).
  • Alegre, L. N., Ziemke, T., & Bazzan, A. L. (2021). Using reinforcement learning to control traffic signals in a real-world scenario: an approach based on linear function approximation. IEEE Transactions on Intelligent Transportation Systems.
  • Artal-Villa, L., & Olaverri-Monreal, C. (2019, April). Vehicle-pedestrian interaction in SUMO and unity3D. In World Conference on Information Systems and Technologies (pp. 198-207). Springer, Cham.
  • Han, G., Zheng, Q., Liao, L., Tang, P., Li, Z., & Zhu, Y. (2022). Deep Reinforcement Learning for Intersection Signal Control Considering Pedestrian Behavior. Electronics, 11(21), 3519.
  • Koti, R. B., & Kakkasageri, M. S. (2021). Multi Agent Assisted Safety Information Dissemination Scheme for V2V Communication in VANETs: Intelligent Agent Approach. International Journal of Intelligent Systems and Applications (IJISA), 13(4), 49-62.
  • Malena, K., Link, C., Bußemas, L., Gausemeier, S., & Trächtler, A. (2022). Traffic Estimation and MPC-Based Traffic Light System Control in Realistic Real-Time Traffic Environments. In International Conference on Vehicle Technology and Intelligent Transport Systems, International Conference on Smart Cities and Green ICT Systems (pp. 232-254). Springer, Cham.
  • Mathiane, M., Tu, C., Owola, P. A., & Nawej, M. C. (2022). A SUMO Simulation Study on VANET-Based Adaptive Traffic Light Control System. In Advances in Electrical and Computer Technologies (pp. 225-237). Springer, Singapore.
  • Qu, D., Li, H., Liu, H., Wang, S., & Zhang, K. (2022). Crosswalk safety warning system for pedestrians to cross the street intelligently. Sustainability, 14(16), 10223.
  • Sun, Q., He, C., Wang, Y., Liu, H., Ma, F., & Wei, X. (2022). Reducing violation behaviors of pedestrians considering group interests of travelers at signalized crosswalk. Physica A: Statistical Mechanics and its Applications, 594, 127023.
  • Tomar, I., Sreedevi, I., & Pandey, N. (2022). State-of-Art Review of Traffic Light Synchronization for Intelligent Vehicles: Current Status, Challenges, and Emerging Trends. Electronics, 11(3), 465.
  • Trächtler, A. (2022). Traffic Estimation and MPC-Based Traffic Light System Control in Realistic Real-Time Traffic Environments. In Smart Cities, Green Technologies, and Intelligent Transport Systems: 10th International Conference, SMARTGREENS 2021, and 7th International Conference, VEHITS 2021, Virtual Event, April 28-30, 2021, Revised Selected Papers (p. 232). Springer Nature.
  • Wang, T., Cao, J., & Hussain, A. (2021). Adaptive Traffic Signal Control for large-scale scenario with Cooperative Group-based Multi-agent reinforcement learning. Transportation research part C: emerging technologies, 125, 103046.
There are 12 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Articles
Authors

Serap Ergün 0000-0003-2504-5101

Publication Date December 31, 2022
Published in Issue Year 2022

Cite

APA Ergün, S. (2022). Dynamic Traffic Signal Split Control Method at Pedestrian Crossings. Avrupa Bilim Ve Teknoloji Dergisi(44), 21-26. https://doi.org/10.31590/ejosat.1216804