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Promet - Traffic&Transportation journal

Accelerating Discoveries in Traffic Science

Accelerating Discoveries in Traffic Science

PUBLISHED
25.04.2023
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Copyright (c) 2024 Hong Ki An, Gimik Bae, Dong Sun Kim

Study of Full Controlled Green Time Roundabouts – An Intelligent Approach

Authors:Hong Ki An, Gimik Bae, Dong Sun Kim

Abstract

When roundabouts face congestion problems, the transition to signalised roundabouts is considered a solution to the problem. The majority of studies have concentrated on how to calculate the optimal cycle length and signal timing to minimise congestion at roundabouts. To date, intelligence algorithms with multi-objectives such as queue length, number of stops, delay time, capacity and so on are widely used for calculating signal timing. Although roundabout congestion can be generated by the weaving zone reducing roundabout capacity, there have been minimal studies which take into account the density in the weaving zone. This study proposed a hybrid gravitational search algorithm – ABFO random forest regression with the following objectives: density, delay time and capacity to find the optimal cycle length and green time in each phase of Changwon city hall roundabout in South Korea as a case study. The optimal cycle length and green time were calculated in MATLAB and microscopic simulation VISSIM sought the effectiveness of a signalised roundabout. The result of the analysis demonstrated that signalised roundabouts with 102 seconds cycle length (phase 1 – 65 seconds of green time and phase 2 – 37 seconds of green time) can reduce density by 46.1%, delays by 32.8% and increase roundabout capacity by 14.8%.

Keywords:signalized roundabout, green time, optimization, VISSIM, hybrid GSA-ABFO algorithm

References

  1. [1] Flannery A, Elefteriadou L, Koza P, Mcfadden J. Safety, delay, and capacity of single-lane roundabouts in the United States. Transportation Research Record Journal of the Transportation Research Board. 1998;1646:63-70. DOI: 10.3141/1646-08.
  2. [2] An HK, Yue WL, Stazic B. An analysis of partially signalized roundabout using SIDRA6 software. Asian Transport Studies. 2015;4(2):314-237. DOI: 10.11175/eastsats.4.314.
  3. [3] Akçelik R, Chung E, Besley M. Performance of roundabouts under heavy demand conditions. Road & Transport Research. 1996;5:36-57.
  4. [4] Qian HB, Li KB, Sun J. The development and enlightenment of signalized roundabout. 2008 International Conference on Intelligent Computation Technology and Automation (ICICTA), IEEE Computer Society, 20–22 Oct. 2008, Changsha, Hunan, China. 2008. p. 538-542.
  5. [5] Azhar AM, Svante B. Signal control of roundabouts. Procedia - Social and Behavioral Sciences. 2011;16:729-738. DOI: 10.1016/j.sbspro.2011.04.492.
  6. [6] Akçelik R. Roundabout metering signals: Capacity, performance and timing. Procedia - Social and Behavioral Sciences. 2011;16(16):686-696. DOI: 10.1016/j.sbspro.2011.04.488.
  7. [7] Jalil K, Xia Y, Zahid MN, Kamal MAS. Two stop-line method for modern T-shape roundabout: Evaluation of capacity and optimal signal cycle. Journal of Advanced Transportation. 2022;2:1-14. DOI: 10.1155/2022/7679496.
  8. [8] Fortuijn LGH. Turbo roundabouts: Estimation of capacity. Transportation Research Record: Journal of the Transportation Research Board. 2009;2130:83-92. DOI: 10.3141/2130-11.
  9. [9] Hallworth MS. Signalling roundabouts, 1. Circular arguments. Traffic Engineering & Control. 1992;33(6):354-363.
  10. [10] Džambas T, Ahac S, Dragčević V. Geometric design of turbo roundabouts. Tehnički vjesnik. 2017;24(1):309-318. DOI: 10.17559/TV-20151012162141.
  11. [11] Guo R, Lin B. Traffic operation performances at roundabout weaving sections. Journal of Transportation System Engineering and Information Technology. 2010;10(3):29-34. DOI: 10.1016/S1570-6672(09)60042-8.
  12. [12] Mohamed AIZ, Ci Y, Tan Y. A novel methodology for estimating the capacity and level of service for the new mega elliptical roundabout intersection. Journal of Advanced Transportation. 2020;2020. DOI: 10.1155/2020/8467152.
  13. [13] Akçelik R. Analysis of roundabout metering signals. 25th AITPM 2006 National Conference, 3–4 Aug. 2006, Melbourne, Australia. 2006.
  14. [14] Vlahos E, et al. Evaluating the conversion of all-way stop-controlled intersections into roundabouts. Transportation Research Record: Journal of the Transportation Research Board. 2008;2078(2078): 80-89. DOI: 10.3141/2078-11.
  15. [15] Ma W, Li X, Xue K. A new traffic-signal control for modern roundabouts: Method and application. IEEE Transactions on Intelligent Transportation Systems. 2005;5(4):282-287. DOI: 10.1109/TITS.2004.838181.
  16. [16] Hatami H, Aghayan I. Traffic efficiency evaluation on elliptical roundabout compared with modern and turbo roundabouts considering traffic signal control. Promet – Traffic&Transportation. 2017;29(1):1-11. DOI: 10.7307/ptt.v29i1.2053.
  17. [17] Afezolli A, Shehu E. The analysis of performance and capacity at a roundabout with metering signals. 3rd International Balkans Conference on Challenges of Civil Engineering, 19-21 May 2016, Epoka University, Tirana, Albania; 2016.
  18. [18] An HK, Yue WL, Stazic B. Dual signal roundabout evaluation in Adelaide using SIDRA and AIMSUN. Road & Transport Research. 2017;26(2):36-49.
  19. [19] Akçelik R. An investigation of the performance of roundabouts with metering signals. TRB National Roundabout Conferences, 18-21 May 2008, Kansas, Mo, USA; 2008.
  20. [20] Martin-Gasulla M, Garcia A, Moreno AT, Llorca C. Capacity and operational improvements of metering roundabouts in Spain. Transportation Research Procedia. 2016;15:295-307. DOI: 10.1016/j.trpro.2016.06.025.
  21. [21] Hummer J, Milazzo J, Schroeder B, Salamati K. Potential for metering to help roundabouts manage peak period demands in the United States. Transportation Research Record: Journal of the Transportation Research Board. 2014;2402:56-66. DOI: 10.3141/2402-07.
  22. [22] An HK, Yue WL, Stazic B. Estimation of vehicle queuing lengths at metering roundabout. Journal of Traffic and Transportation Engineering (English Edition). 2017;4(6):545-554. DOI: 10.1016/j.jtte.2017.04.002.
  23. [23] An HK, Abdalla AN. Prediction of queuing length at metering roundabout using adaptive neuro fuzzy inference system. Measurement and Control. 2019;52(5-6):432-440. DOI: 10.1177/0020294019839415.
  24. [24] Yu B, Xue K, Yang K. Optimization of roundabout control method based on dissymmetry. 2007 IEEE Intelligent Transportation Systems Conference, 30 Sep. – 3 Oct. 2007, Washington, USA; 2007. DOI: 10.1109/ITSC.2007.4357681.
  25. [25] Jiang ZH, et al. Investigation on two-stop-line signalized roundabout: Capacity and optimal cycle length. Journal of Advanced Transportation. 2019;1:1-9. DOI: 10.1155/2019/5720290.
  26. [26] Ma WJ, et al. Signal timing optimization model based on dual-ring phase scheme for roundabout. Journal of Central South University. 2013;20:563-571. DOI: 10.1007/s11771-013-1519-6.
  27. [27] Bie Y, Mao C, Yang M. Development of vehicle delay and queue length models for adaptive traffic control at signalized roundabout. Procedia Engineering. 2016;137:141-150. DOI: 10.1016/j.proeng.2016.01.244.
  28. [28] Bie Y, et al. Stop-line setback at a signalized roundabout: A novel concept for traffic operations. Journal of Transportation Engineering. 2016;142(3):05016001. DOI: 10.1061/%28ASCE%29TE.1943-5436.0000829.
  29. [29] Murat YS, Cakici Z, Tian Z. A signal timing assignment proposal for urban multi lane staged controlled signalised roundabouts. Građevinar. 2019;71(2):113-124. DOI: 10.14256/JCE.2323.2018.
  30. [30] Qadri SSSM, Gokce MA, Oner E. Traffic signal timing optimization for signalized roundabout using GA. International Journal of Advanced Research in Engineering and Technology (IJARET). 2020;11(11):1888-1897. DOI: 10.34218/IJARET.11.11.2020.176.
  31. [31] Transportation Research Board of the National Research Council. Highway Capacity Manual. Washington D.C; 2010.
  32. [32] Webster FV. Traffic signal settings. Road Research Laboratory. Road Research Technique Paper number: 39, 1958.
  33. [33] Chen H, Zhu Y, Hu K. Adaptive bacterial foraging optimization. Abstract and Applied Analysis. 2011;2011(4):1-27. DOI: 10.1155/2011/108269.
  34. [34] Majhi R, Panda G, Majhi B, Sahoo G. Efficient prediction of stock market indices using adaptive bacterial foraging optimization (ABFO) and BFO based techniques. Expert Systems with Applications An International Journal. 2009;36(6):10097-10104. DOI: 10.1016/j.eswa.2009.01.012.
  35. [35] Moghadam MS, Nezamabadi-Pour H, Farsangi MM. A quantum behaved gravitational search algorithm. Intelligent Information Management. 2012;4(6):390-395. DOI: 10.1109/IranianCEE.2012.6292446.
  36. [36] Rashedi E, Nezamabadi-Pour H, Saryazdi S. Filter modeling using gravitational search algorithm. Engineering Applications of Artificial Intelligence. 2011;24(1):117-122. DOI: 10.1016/j.engappai.2010.05.007.
  37. [37] Vasconcelos L, Silva AB, Seco A, Silva JP. Estimating the parameters of Cowan’s M3 headway distribution for roundabout analyses. Baltic Journal of Road and Bridge Engineering. 2012;7(4):261-268. DOI: 10.3846/bjrbe.2012.35.
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