PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Genetic algorithm application for optimizing traffic signal timing reflecting vehicle emission intensity

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Urbanization has created continuous growth in transportation demand, leading to serious issues, including infrastructure overload, disrupted traffic flow, and associated vehicular emissions. As a result, resolving these problems has become one of the primary missions of governments worldwide. The optimization of the traffic signal timing system is considered a promising approach to overcoming the negative consequences of increasing vehicle volume. In metropolises, oversaturated intersections, where the traffic density and vehicle exhaust emission levels are significant, have been considered as the priority to target. Several scientists have attempted to design traffic lights with the most appropriate timing. However, the majority of previous studies have not formed a comprehensive evaluation of essential factors, especially regarding the appropriate weighting of vehicle emission parameters. By assessing the all-inclusive relationship of critical elements with an emphasis on vehicle exhaust emissions, a performance index model using a genetic algorithm (GA) is established in this paper, demonstrated by data from a case study in Taiwan.
Czasopismo
Rocznik
Strony
5--16
Opis fizyczny
Bibliogr. 43 poz.
Twórcy
  • Hanoi Architectural University; Km 10 Nguyen Trai Road, Thanh Xuan District, Ha Noi City, Vietnam
autor
  • University of Transport and Communications; No.3 Cau Giay Street, Lang Thuong ward, Dong Da District, Hanoi, Vietnam
  • Hanoi Architectural University; Km 10 Nguyen Trai Road, Thanh Xuan District, Ha Noi City, Vietnam
Bibliografia
  • 1. Lin, L.T. & Huang, H.J. An effective interval of traffic signal coordination under safety and efficiency considerations. Journal of the Chinese Institute of Engineers. 2010. Vol. 33(2). P. 271-285.
  • 2. Kwasnicka, H. & Stanek, M. Genetic approach to optimize traffic flow by timing plan manipulation. In: Sixth International Conference on Intelligent Systems Design and Applications. 2006. P. 1-6.
  • 3. Gao, Y.-F. & et al. Multi-objective optimization and simulation for urban road intersection group traffic signal control. China Journal of Highway and Transport. 2012. Vol. 25(6). P. 129-135.
  • 4. Guo, J. & et al. A model and genetic algorithm for area-wide intersection signal optimization under user equilibrium traffic. Mathematics and Computers in Simulation. 2019. Vol. 155. P. 92-104.
  • 5. Li, X. &. et al. Signal timing of intersections using integrated optimization of traffic quality, emissions and fuel consumption: a note. Transportation Research Part D: Transport and Environment. 2004. Vol. 9(5). P. 401-407.
  • 6. Do, V.M. & Ho, T.L.H. & Dinh, T.H. Evaluating the effectiveness of eco-driving courses based on car-GPS tracking data in the itinerary tracking device to reduce fuel consumption of vehicles in urban areas. In: E3S Web of Conferences. 2021. EDP Sciences.
  • 7. Khalighi, F. & Christofa, E. Emission-based signal timing optimization for isolated intersections. Transportation Research Record. 2015. Vol. 2487(1). P. 1-14.
  • 8. Lin, C. & Gong, B. & Qu, X. Low emissions and delay optimization for an isolated signalized intersection based on vehicular trajectories. PloS one. 2015. Vol. 10(12). No. e0146018.
  • 9. Yu, D. & et al. Signal timing optimization based on fuzzy compromise programming for isolated signalized intersection. Mathematical Problems in Engineering. 2016. Article ID 1682394.
  • 10. Kou, W. & et al. Multiobjective optimization model of intersection signal timing considering emissions based on field data: A case study of Beijing. Journal of the Air & Waste Management Association. 2018. Vol. 68(8). P. 836-848.
  • 11. Ding, S. & et al. Arterial offset optimization considering the delay and emission of Platoon: A case study in Beijing. Sustainability. 2019. Vol. 11(14). No. 3882. P. 1-19.
  • 12. Zhao, H. & et al. Research on unregulated emissions from motor vehicles at intersection based on the optimized traffic signal timing. In: IOP Conference Series: Earth and Environmental Science. 2020. IOP Publishing.
  • 13. Du, Y. & ShangGuan, W. & Chai, L. A coupled vehicle-signal control method at signalized intersections in mixed traffic environment. IEEE Transactions on Vehicular Technology. 2021. Vol. 70(3). P. 2089-2100.
  • 14. Zakariya, A.Y. & Rabia, S.I. Estimating the minimum delay optimal cycle length based on a time-dependent delay formula. Alexandria Engineering Journal. 2016. Vol. 55(3). P. 2509-2514.
  • 15. Gao, Y.-F. & et al. Multi-objective optimization and simulation for urban road intersection group traffic signal control. Zhongguo Gonglu Xuebao (China Journal of Highway and Transport). 2012. Vol. 25(6). P. 129-135.
  • 16. Yu, D. & et al. Signal timing optimization based on fuzzy compromise programming for isolated signalized intersection. Mathematical Problems in Engineering. 2016. Article ID 1682394.
  • 17. Shen, Y. An optimization model of signal timing plan and traffic emission at intersection based on Synchro. IOP Conference Series: Earth and Environmental Science. 2018. Vol. 189(6). No. 062002.
  • 18. Qian, R. & et al. A Traffic Emission-saving Signal Timing Model for Urban Isolated Intersections. Procedia - Social and Behavioral Sciences. 2013. Vol. 96. P. 2404-2413.
  • 19. Jia, H. & et al. Multi-objective optimization of urban road intersection signal timing based on particle swarm optimization algorithm. Advances in Mechanical Engineering. 2019. Vol. 11(4). No. 168781401984249.
  • 20. Bai, K. & et al. Dynamic crosswalk signal timing optimization model considering vehicle and pedestrian delays and fuel consumption cost. Sustainability. 2020. Vol. 12(2). No. 689. P. 1-9.
  • 21. Liu, H. & et al. Evaluating impacts of intelligent transit priority on intersection energy and emissions. Transportation Research Part D: Transport and Environment. 2020. Vol. 86. No. 102416.
  • 22. Chehouri, A. & et al. A constraint-handling technique for genetic algorithms using a violation factor. Journal of Computer Science. 2016. Vol. 12(7). P. 350-362.
  • 23. Foy, M.D. & Benekohal, R.F. & Goldberg, D.E. Signal timing determination using genetic algorithms. Transportation Research Record. 1992. No. 1365. P. 108-115.
  • 24. Zhang, L.-G. & et al. PSO-based optimization for isolated intersections signal timings and simulation. In: 2008 International Conference on Machine Learning and Cybernetics. 2008. IEEE.
  • 25. Li, Z. & Schonfeld, P. Hybrid simulated annealing and genetic algorithm for optimizing arterial signal timings under oversaturated traffic conditions. Journal of advanced transportation. 2015. Vol. 49(1). P. 153-170.
  • 26. Roger, P. Roess & Elena S. Prassas & William R. McShane. Traffic Engineering. 3rd Edition. 2004. Pearson Education International.
  • 27. Fred L Mannering & Scott S. Washburn. Principles of highway engineering and traffic analysis. 2013. John Wiley & Sons, Inc.
  • 28. HCM 2010: highway capacity manual. 2010. Fifth edition. Washington, D.C.: Transportation Research Board.
  • 29. Wang, H. & et al. Design on optimization of phase for urban traffic coordinated control. 2017. IEE. 10th International Symposium on Computational Intelligence and Design (ISCID). P. 178-182.
  • 30. Manh, D.V. & et al. Multiple objective genetic algorithms for solving traffic signal optimization issue at a complex intersection: a case study in Taichung City, Taiwan. The Open Civil Engineering Journal. 2020. Vol. 14(1).
  • 31. Chaudhry, M.S. & Ranjitkar, P. Delay estimation at signalized intersections with variable queue discharge rate. Journal of the Eastern Asia Society for Transportation Studies. 2013. Vol. 10. P. 1764-1775.
  • 32. Černický, Ľ. & Kalašová, A. & Kapusta, J. Signal controlled junctions calculations in traffic -capacity assessment - Aimsun, OmniTrans, Webster and Tp 10/2010 results comparison. Transport Problems. 2016. Vol. 11. No. 1. P. 121-130.
  • 33. Chen, X.-F. & Z.-k. Shi. Real-coded genetic algorithm for signal timing optimization of a single intersection. In: Proceedings. International Conference on Machine Learning and Cybernetics. 2002. IEEE.
  • 34. Kwasnicka, H. & Stanek, M. Genetic approach to optimize traffic flow by timing plan manipulation. In: Sixth International Conference on Intelligent Systems Design and Applications. 2006. IEEE.
  • 35. Royani, T. & Haddadnia, J. & Alipoor, M. Traffic signal control for isolated intersections based on fuzzy neural network and genetic algorithm. In: Proceedings of the 10th WSEAS international conference on signal processing, computational geometry and artificial vision. 2010.
  • 36. Chiroma, H. & et al. Correlation study of genetic algorithm operators: crossover and mutation probabilities. In: Proceedings of the International Symposium on Mathematical Sciences and Computing Research. 2013.
  • 37. Ma, X. & Jin, J. & Lei, W. Multi-criteria analysis of optimal signal plans using microscopic traffic models. Transportation Research Part D: Transport and Environment. 2014. Vol. 32. P. 1-14.
  • 38. Rahbari, D. Help the genetic algorithm to minimize the urban traffic on intersections. International Journal of Research in Computer Science. 2014. Vol. 4(4). P. 1-9.
  • 39. Patil, V. & Pawar, D. The optimal crossover or mutation rates in genetic algorithm: a review. International Journal of Applied Engineering and Technology. 2015. Vol. 5(3). P. 38-41.
  • 40. Roeva, O. & Fidanova, S. & Paprzycki, M. Population size influence on the genetic and ant algorithms performance in case of cultivation process modeling. In: Recent advances in computational optimization. 2015. Springer. P. 107-120.
  • 41. Tan, M.K. & et al. Genetic algorithm based signal optimizer for oversaturated urban signalized intersection. In: 2016 IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia).
  • 2016. IEEE.
  • 42. Xinwu, Y. & et al. A coordinated signal control method for arterial road of adjacent intersections based on the improved genetic algorithm. Optik. 2016. Vol. 127(16). P. 6625-6640.
  • 43. Tharwat, A. & et al. MOGOA algorithm for constrained and unconstrained multi-objective optimization problems. Applied Intelligence. 2018. Vol. 48(8). P. 2268-2283.
Uwagi
PL
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-23cd2bd2-ca64-46b8-8411-607f3da91b82
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.