Traffic Optimization Through Waiting Prediction and Evolutive Algorithms

• García, Francisco ^[1] ; Hernández, Helena ^[1] ; Moreno-García, María N. ^[1] ; de Paz Santana, Juan F. ^[1] ; F. López, Vivian ^[1] ; Bajo, Javier ^[2]
  1. [1] Universidad de Salamanca

     Universidad de Salamanca

     Salamanca, España

     
  2. [2] Universidad Politécnica de Madrid

     Universidad Politécnica de Madrid

     Madrid, España

     
• Localización: IJIMAI, ISSN-e 1989-1660, Vol. 9, Nº. 3, 2025, págs. 96-103
• Idioma: inglés
• DOI: 10.9781/ijimai.2023.12.001
• Enlaces
  • Texto completo
• Resumen

  • Traffic optimization systems require optimization procedures to optimize traffic light timing settings in order to improve pedestrian and vehicle mobility. Traffic simulators allow obtaining accurate estimates of traffic behavior by applying different timing configurations, but require considerable computational time to perform validation tests. For this reason, this project proposes the development of traffic optimizations based on the estimation of vehicle waiting times through the use of different prediction techniques and the use of this estimation to subsequently apply evolutionary algorithms that allow the optimizations to be carried out. The combination of these two techniques leads to a considerable reduction in calculation time, which makes it possible to apply this system at runtime. The tests have been carried out on a real traffic junction on which different traffic volumes have been applied to analyze the performance of the system.

• Referencias bibliográficas
  • S.M. Khan, M. Rahman, A. Apon, M. Chowdhury, “Chapter 1 - Characteristics of Intelligent Transportation Systems and Its Relationship With...
  • C. Zato, A. de Luis, J. Bajo, J.F. de Paz, J.M. Corchado, “Dynamic model of distribution and organization of activities in multi-agent systems”,...
  • D.A. Menasce, “Trade-offs in designing web clusters”, IEEE Internet Computing, vol. 6, no. 5, pp. 76-80, 2002.
  • P. Alvarez Lopez, M. Behrisch, L. Bieker-Walz, J. Erdmann, Y.P. Flötteröd, R. Hilbrich, Leonhard Lücken, J. Rummel, P. Wagner, Evamarie Wießner,...
  • D. Krajzewicz, G. Hertkorn and P. Wagner, Christian Rössel, “SUMO (Simulation of Urban MObility) An open-source traffic simulation”, in MESM2002...
  • Y. Zhang, R. Su, “An optimization model and traffic light control scheme for heterogeneous traffic systems”, Transportation Research Part...
  • C. Karakuzu, O. Demirci, “Fuzzy logic based smart traffic light simulator design and hardware implementation”, Applied Soft Computing, vol....
  • X. Zhengxing, J. Qing, N. Zhe, W. Rujing, Z. Zhengyong, H. He, S. Bingyu, W. Liusan, W. Yuanyuan, “Research on intelligent traffic light control system...
  • S.A.Celtek, A. Durdu, M.E.M. Alı, “Real-time traffic signal control with swarm optimization methods”, Measurement, vol. 166, 108206, 2020.
  • M. Greguri´c, M. Vuji´c, “Charalampos Alexopoulos and Mladen Mileti. Application of Deep Reinforcement Learning in Traffic Signal Control: An...
  • S.M. Odeh, A.M. Mora, M.N. Moreno, J.J.Merelo, “A Hybrid Fuzzy Genetic Algorithm for an Adaptive Traffic Signal System”, Advances in Fuzzy Systems,...
  • A. Ikidid, A. El Fazziki, M. Sadgal, “Multi-Agent and Fuzzy Inference- Based Framework for Traffic Light Optimization”, International Journal of...
  • C. Pappis, E. Mamdani, “A fuzzy logic controller for a traffic junction," IEEE transactions on Systems, Man and Cybernetics, SMC-7/10,...
  • M. Nakatsuyama, H. Nagahashi, N. Nishizuka, “Fuzzy logic phase controller for traffic functions in the one-way arterial road”, IFAC 9th Triennial...
  • J. Favilla, A. Machion, F. Gomide “Fuzzy traffic control: adaptive strategies” Second IEEE International Conference on Fuzzy Systems II, pp. 506-511,...
  • S. Komsiyah, E. Desvania, “Traffic Lights Analysis and Simulation Using Fuzzy Inference System of Mamdani on Three-Signaled Intersections”, Procedia...
  • C. H. Chou, J. C.Teng, “A fuzzy logic controller for traffic junction signals”, Information Sciences, vol. 143, no. 1–4, pp. 73-97, 2002.
  • X. Fan, Y. Liu, “Alterable-Phase Fuzzy Control Based on Neutral Network”, Journal of Transportation Systems Engineering and Information Technology,...
  • A. S. Tomar, M. Singh, G. Sharma, K. V. Arya, “Traffic Management using Logistic Regression with Fuzzy Logic”, Procedia Computer Science,...
  • T.S. Tamir, G. Xiong, Z. Li, H. Tao, Z. Shen, B. Hu, H.M. Menkir, “Traffic Congestion Prediction using Decision Tree”, Logistic Regression...
  • M. Bai, Y. Lin, M. Ma, P. Wang, L- Duan, PrePCT: “Traffic congestion prediction in smart cities with relative position congestion tensor”, Neurocomputing,...
  • A. Sfyridis, P. Agnolucci, “Annual average daily traffic estimation in England and Wales: An application of clustering and regression modelling”,...
  • X. Bao, D. Jiang, X. Yang, H. Wang, “An improved deep belief network for traffic prediction considering weather factors”, Alexandria Engineering Journal,...
  • S. Lu, Q, Zhang, G. Chen, D. Seng, “A combined method for short-term traffic flow prediction based on recurrent neural network”, Alexandria Engineering...
  • L. Qu, J. Lyu, W. Li, D. Ma, H. Fan, “Features injected recurrent neural networks for short-term traffic speed prediction”, Neurocomputing,...
  • S. Narmadha, V. Vijayakumar, “Spatio-Temporal vehicle traffic flow prediction using multivariate CNN and LSTM model”, Materials Today: Proceedings,...
  • M. Aslani, S. Seipel, M.S. Mesgari, M. Wiering, “Traffic signal optimization through discrete and continuous reinforcement learning with robustness analysis...
  • M. Abdoos, A.L.C. Bazzan, “Hierarchical traffic signal optimization using reinforcement learning and traffic prediction with long short term memory”,...
  • M. Essa, T. Sayed, “Self-learning adaptive traffic signal control for real- time safety optimization”, Accident Analysis & Prevention,...
  • H. Joo, S.H. Ahmed, Y. Lim, “Traffic signal control for smart cities using reinforcement learning”, Computer Communications, vol. 154, pp....
  • E. Walraven, M.T.J. Spaan, B. Bakker, “Traffic flow optimization: A reinforcement learning approach”, Engineering Applications of Artificial Intelligence,...
  • T.M. Aljohani, A. Ebrahim, O. Mohammed, “Real-Time metadata- driven routing optimization for electric vehicle energy consumption minimization...
  • S. Koh, B. Zhou, H. Fang, P. Yang, Z. Yang, Q. Yang, L. Guan, Z. Ji, “Real- time deep reinforcement learning based vehicle navigation”, Applied...
  • Y. Gong, M. Abdel-Aty, J. Yuan, Q. Cai, “Multi-Objective reinforcement learning approach for improving safety at intersections with adaptive traffic...
  • H. Maske, T. Chu, U. Kalabić, “Control of traffic light timing using decentralized deep reinforcement learning”, IFAC-PapersOnLine, vol. 53, no....
  • Z. Li, H. Yu, G. Zhang, S. Dong, C.Z. Xu, “Network-wide traffic signal control optimzation using a multi-agent deep reinforcement learning”, Transportation...
  • M. Essa, T. Sayed, “Self-learning adaptive traffic signal control for real- time safety optimization”, Accident Analysis & Prevention,...
  • J. Sun, H. Liu, Z. Ma, “Modelling and simulation of highly mixed traffic flow on two-lane two-way urban streets”, Simulation Modelling Practice and...
  • A. Kondyli, I. Soria, A. Duret, L. Elefteriadou, “Sensitivity analysis of CORSIM with respect to the process of freeway flow breakdown at bottleneck...
  • L. Wiene, A. Liaw, M. Wiener “Classification and regression by randomForest”, R News, 2/3, pp. 18-22, 2002.
  • Y. Freund, R. E. Schapire, “A decision-theoretic generalization of on-line learning and an application to boosting”, Journal of Computer and...
  • D. Hernández-Lobato, G. Martínez-Muñoz, A. Suárez, “Empirical analysis and evaluation of approximate techniques for pruning regression bagging ensembles”,...
  • P. Geurts, D. Ernst, I. Wehenkel, “Extremely randomized trees”, Machine Learning, vol. 63, no. 1, pp. 3-42, 2006.
  • F. García Encinas, H. Hernández Payo, J.F. de Paz Santana, M.N. Moreno García, J. Bajo Pérez, “Estimating Time Lost on Semaphores with Deep Learning”....
  • S. Krauss, P. Wagner, C. Gawron “Metastable States in a Microscopic Model of Traffic Flow”, Physical Review E, vol. 55, no. 5, pp. 5597–602, 1997,...
  • S. Krauss, “Microscopic modeling of traffic flow: Investigation of collision free vehicle dynamics”, 1998.