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A Study of Traffic Signal Timing Optimization Based on PSO-BFO Algorithm

PSO-BFO 알고리즘을 통한 교통 신호 최적화 연구

  • Hong Ki An (Fac. of Civil Engineering & Technology, Universiti Malaysia Perlis) ;
  • Gimok Bae (Dept. of Smart-city Engineering, Daejin University)
  • 안홍기 (퍼를리스 대학교 토목공학과) ;
  • 배기목 (대진대학교 스마트건설환경공학부)
  • Received : 2023.10.15
  • Accepted : 2023.11.09
  • Published : 2023.12.31

Abstract

Recently, research on traffic signal control using artificial intelligence algorithms has been receiving attention, and many traffic signal control models are being studied. However, most studies either focused on independent intersections or are theoretical studies that calculate signal cycle length according to changes in traffic volume. Therefore, this study was conducted on a signalized intersection - roundabout in Gajwa-ro. The Particle Swarm Optimization - Bacterial Foraging Optimization (PSO-BFO) algorithm was proposed, which is developed from the GA and PSO algorithms for minimizing congestion at two intersections. As a result, optimum cycle length was determined to be 158 seconds. The Verkehr In Stadten - SIMulationsmodell (VISSIM) results showed that there was 3.4% increased capacity, 8.2% reduced delay and 8.3% reduced number of stops at the Gajwa-ro signalized intersection. Additionally, at the roundabout, a 9.2% increase in capacity, a 7.1% reduction in delay, and a 27.2% decrease in the number of stops was observed.

최근 인공지능 알고리즘을 활용한 교통 신호 제어에 관한 관심 증대와 함께, 관련 모델구축 연구가 활발히 진행되고 있다. 그러나 대부분의 연구는 독립 교차로를 대상으로, 교통량 변화에 연동되는 신호 주기 산정을 위한 이론 전개가 주를 이루고 있다. 본 연구에서는 신호제어 알고리즘 구축을 위한 실증 분석을 통해, 신호운영과 회전교차 방식의 실제 교차로를 대상으로 분석을 진행하였다. 기존 연구에서 많이 활용되는 GA와 PSO 알고리즘을 개선한 PSO-BFO 알고리즘을 제시하여 두 교차로의 운영 효과 증진을 위한 신호제어 방안을 강구 하였다. 그 결과, 158초의 신호 주기하에 신호 교차로의 경우, 용량 증대 3.4%, 지체도 및 정지횟수 감소는 각각 8.2%, 8.3%의 효과가 발생하고, 회전교차로에서는 용량증대 9.2%, 지체도 및 정지횟수 감소가 각각 7.1%, 27.2%에 이르는 효과가 발생하는 것으로 나타났다.

Keywords

References

  1. An, H. K., Liu, Y. and Kim, D. S.(2022), "Operational optimization at signalized metering roundabouts using cuckoo search/local search algorithm", Measurement & Control, vol. 55, pp.1110-1123. https://doi.org/10.1177/00202940221101895
  2. An, H. K., Yue, W. L. and Stazic, B.(2016), "An Analysis of a Partially Signalized Roundabout using SIDRA 6 Software", Asian Transport Studies, vol. 4, pp.314-329.
  3. Arel, L., Liu, C., Urbanik, T. and Kohls, A. G.(2010), "Reinforcement learning-based multi-agent system for network traffic signal control", IET Intelligent Transport Systems, vol. 4, pp.128-135. https://doi.org/10.1049/iet-its.2009.0070
  4. Chen, H., Zhu, Y. and Hu, K.(2011), "Adaptive bacterial foraging optimization", Abstract and Applied Analysis, vol. 2011, pp.1-27. https://doi.org/10.1155/2011/108269
  5. Cracknell, J. A.(2000), Experience in urban traffic management and demand management in developing countries, No. Final Report 2000.
  6. Han, E., Park, S. M., Jeong, H. Lee, C. and Yun, I.(2016), "The Development of an Algorithm for the Optimal Signal Control for Isolated Intersection under V2X Communication Environment", The Journal of The Korea Institute of Intelligent Transport Systems, vol. 15, pp.90-101. https://doi.org/10.12815/kits.2016.15.6.090
  7. Han, E., Yun, I., Lee, S. S., Jang, K. and Park, B.(2018), "Development of Real-time Traffic Signal Control Strategy for Coordinated Signalized Intersections under V2I Communication Environment", The Journal of the Korea Institute of Intelligent Transport Systems, vol. 17, pp.59-71. https://doi.org/10.12815/kits.2018.17.3.59
  8. Hymel, K. M., Small, K. S. and Dender, K. V.(2010), "Induced demand and rebound effects in road transport", Transportation Research Part B: Methodological, vol. 44, pp.1220-1241. https://doi.org/10.1016/j.trb.2010.02.007
  9. Jabbarpour, M. R., Zarrabi, H., Khokhar, R. H., Shamshirband, S. and Choo, K. K. R.(2018), "Applications of computational intelligence in vehicle traffic congestion problem: A survey", Soft Computing, vol. 22, pp.2299-2320.
  10. Jia, H., Lin, Y., Luo, Q., Li, Y. and Miao, Y.(2019), "Multi-objective optimization of urban road intersection signal timing based on particle swarm optimization algorithm", Advances in Mechanical Engineering, vol. 11, pp.1-9. https://doi.org/10.1177/1687814019842498
  11. Khadhir, A., Vanajakshi, L. D. and Bhaskar, A.(2020), "A Microsimulation-Based Stochastic Optimization Approach for Optimal Traffic Signal Design", Transportation in Developing Economies, vol. 6, p.19. https://doi.org/10.1007/s40890-020-00108-x
  12. Kim, D. H. and Jeong, O. R.(2019), "A Study on Cooperative Traffic Signal Control at multi-intersection", Journal of Institute of Korean Electrical and Electronics Engineers, vol. 23, pp.1380-1386.
  13. Qadri, S. S. S. M., Gokce, M. A. and Oner, E.(2020), "State-of-art review of traffic signal control methods: Challenges and opportunities", European Transport Research Review, vol. 2020, pp.1-23.
  14. Rahman, I., Vasant, P. M., Singh, B. S. M. and Abdullah-Al-Wadud, M.(2016), "On the performance of accelerated particle swarm optimization for charging plug-in hybrid electric vehicles", Alexandria Engineering Journal, vol. 55, pp.419-426. https://doi.org/10.1016/j.aej.2015.11.002
  15. Sun, L., Tao, J., Li, C., Wang, S. and Tong, Z.(2018), "Microscopic Simulation and Optimization of Signal Timing based on Multi-Agent: A Case Study of the Intersection in Tianjin", Korea Journal of Civil Engineering, vol. 22, pp.3373-3382. https://doi.org/10.1007/s12205-018-0528-2
  16. Webster, F. V.(1958), "Traffic signal settings", Road Research Technical Paper, pp.1-44.