Traffic Congestion Mitigation on Highways by using the Feedback Strategy
Article Sidebar
Main Article Content
Abstract
The design of highways in urban areas aims to reduce congestion. When congestion occurs on a highway, it presents a problem that must be solved. The Al-Dawrah Expressway experienced severe congestion, particularly at its entrance, negatively impacting traffic flow. Data was collected via cameras installed along the highway. After calibrating and verifying the data, the ALINE algorithm was used to control traffic flow at highway entrances (Ramp Metering) to congestion mitigation by control of three parameters(flow, occupancy and speed). The results were significant, with four scenarios performed at different time points. The fourth scenario, lasting 10 seconds, showed the highest improvement rate of 20.1%, encompassing increased traffic flow, reduced congestion, decreased critical occupancy and increased speed.
Article Details
Section
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Licensed under a CC-BY license: https://creativecommons.org/licenses/by-nc-sa/4.0/
How to Cite
References
[1] Papageorgiou, M., Kosmatopoulos, E., & Papamichail, I., “Effects of variable speed limits on motorway traffic flow, Transportation Research Record, 2047(1), 37-48, 2008.
[2] Gregurić, M., Kušić, K., & Ivanjko, E., “Impact of deep reinforcement learning on variable speed limit strategies in connected vehicles environments”, Engineering applications of artificial intelligence, 112, 104850, 2022.
[3] Wu, Y., Tan, H., & Ran, B., “Differential variable speed limits control for freeway recurrent bottlenecks via deep reinforcement learning”, arXiv preprint arXiv:1810.10952, 2018.
[4] Belletti, F., Haziza, D., Gomes, G., & Bayen, A. M.,” Expert level control of ramp metering based on multi-task deep reinforcement earning”. IEEE Transactions on Intelligent Transportation Systems, 19(4), 1198-1207,2017.
[5] Lee, S. F., Teng, Y. W., & Wang, W. J.,2000, May),” Highway ramp control via fuzzy logic”,In Ninth IEEE International Conference on Fuzzy Systems. FUZZ-IEEE 2000 (Cat. No. 00CH37063) , may,2000. Vol. 1, pp. 274-278. IEEE.
[6] Papageorgiou, M., Hadj-Salem, H., & Blosseville, J. M, “ALINEA: A local feedback control law for on-ramp etering”, Transportation research record, 1320(1), 58-67, 1991.
[7] 7. Wang, Y., Kosmatopoulos, E. B., Papageorgiou, M., & Papamichail, I.” Local ramp metering in the presence of a distant downstream bottleneck: Theoretical analysis and simulation study”, IEEE Transactions on Intelligent Transportation Systems, 15(5), 2024-2039, 2014.
[8] Di, Y., Zhang, W., Ding, H., Zheng, X., & Bai, H, “Integrated control for mixed CAV and CV traffic flow in expressway merge zones combined with variable speed limit, ramp metering, and lane changing”, Journal of transportation engineering, Part A: Systems, 149(2), 04022140, 2023.
[9] Shaaban, K., Khan, M. A., & Hamila, R., “Literature review of advancements in adaptive ramp metering”, Procedia Computer Science, 83, 203-211, 2016.
[10] Vrbanić, F., Ivanjko, E., Kušić, K., & Čakija, D., “Variable speed limit and ramp metering for mixed traffic flows: A review and open questions”. Applied Sciences, 11(6), 2574, 2021.
[11] Trubia, S., Curto, S., Barberi, S., Severino, A., Arena, F., & Pau, G, “Analysis and evaluation of ramp metering: From historical evolution to the application of new algorithms and engineering principles”, Sustainability, 13(2), 850, 2021.
[12] Aydos, J. C., & O'Brien, A, , “SCATS ramp metering: strategies, arterial integration and results”, In 17th international IEEE conference on intelligent transportation systems (ITSC), October, 2014, (pp. 2194-2201). IEEE.
[13] Papageorgiou, M., Hadj-Salem, H., & Blosseville, J. M, “ALINEA: A local feedback control law for on-ramp metering”, Transportation research record, 1320(1), 58-67, 1991.
[14] Neudorff, L. G., Randall, J., Reiss, R. A., & Gordon, R. L, “Freeway management and operations handbook”,2003.
[15] Ma, Y., Zhang, Y., Qin, X., Xie, Y., & Li, T, “An on-ramp metering control strategy considering freeway moving bottlenecks in intelligent and connected transportation systems”, International Journal of Intelligent Transportation Systems Research, 23(2), 1242-1256, 2025.
[16] Wei, Z., Zhou, Y., Zhang, Y., & Kulkarni, M, „Coordinated ramp metering control based on scalable nonlinear traffic dynamics model discovery in a large network”. arXiv preprint arXiv:2503.06767, 2025.
[17] Yang, Y., Yu, S., Ding, F., & Han, Y, “Learning–Based Ramp Metering Strategy Considering Queue Management” Journal of Advanced Transportation, 2025(1), 2838943, 2025.
[18] Chavoshi, K., Ferrara, A., & Kouvelas, A, “A feedback linearization approach for coordinated traffic flow management in highway systems”. Control Engineering Practice, 139, 105615,2023.
[19] Neudorff, L.G., Randall, J.E., Reiss, R., Gordon, R, “Freeway Management and Operations Handbook”, Publication FHWAOP-04-003, 2003. FHWA, U.S. Department of Transportation. September, 2003.
[20] Mirchandani, P., Zou, N, “Analytical Modeling of Meter Systems”, Proceedings of the IEEE ITSC 2006, Toronto, Canada, September 17- 20, 2006.
[21] Masher, D.P., Ross, D., Wong, P., Tuan, P, Zeidler, H., and Petracek, S, “Guidelines for design and operation of ramp control systems”, 1975.
[22] Cheng, J., Ye, C., Wang, N., Yao, Y., Zhao, H., Dai, X., ... & Lv, Y, “ A deep reinforcement learning based ramp metering control method considering ramp outflow”. IFAC-PapersOnLine, 58(10), 200-205, 2024.
[23] Fan, T., Chen, J., & Chung, E, “Integrating micro and macro traffic control for mixed autonomy traffic”, Communications in Transportation Research, 5, 100188, 2025.
[24] Zhou, J., Zhu, F, “Modeling the fundamental diagram of mixed human-driven and connected automated vehicles”, Transport. Res. C Emerg. Technol. 115, 102614, 2020.
[25] Karim, H. K, “Exploratory analysis of ramp metering on efficiency, and safety of freeways using microsimulation”,2015.
[26] Chu, L., Liu, H.X., Recker, W., Zhang, H.M, “Performance evaluation of adaptive ramp-metering algorithms using microscopic traffic simulation model”. Journal of Transportation Engineering 130 (3), 330–338, 2004.
[27] Chu, L., Recker, W., Yu, G, “Integrated Ramp Metering Design and Evaluation Platform with Paramics”, California Path Research Report, Institute of Transportation Studies, University of California, Berkeley, 2009.
[28] Chu, L., Yang, X, “Optimization of the ALINEA ramp metering control using genetic algorithm with micro-simulation”, Transportation Research Board 82nd Annual Meeting, Washington, DC, 2003.
[29] Fan, T., Chen, J., & Chung, E, "Integrating micro and macro traffic control for mixed autonomy traffic” Communications in Transportation Research, 5, 100188, 2025.
[30] Trapp, R, “A local non-restrictive Ramp Metering strategy based on stochasticity of capacity”. Transportation Research Procedia, 15, 594-606, 2016.