Let's Connect
Follow Us
Watch Us
(+385) 1 2380 262
journal.prometfpz.unizg.hr
Promet - Traffic&Transportation journal

Accelerating Discoveries in Traffic Science

Accelerating Discoveries in Traffic Science

PUBLISHED
20.06.2024
LICENSE
Copyright (c) 2024 Yin Han, Bo Ning, Shidong Liang

An Alternative Optimal Design of Dynamic Straight-Right Lane Control for T-Shaped Intersections

Authors:Yin Han, Bo Ning, Shidong Liang

Abstract

A novel control method called dynamic straight-right lane (DSRL) control design is proposed for signalised intersections. This design aims to utilise the resources of the right-turn lane to increase the capacity for straight-through traffic while minimising the impact on right-turn vehicles. In this paper, an alternative approach to DSRL control design for T-shaped intersections is proposed. By redesigning the spatial and temporal allocation at the entrance, this design ensures the safety of lane change manoeuvres and reduces the design threshold for T-shaped intersections. To facilitate the implementation of the DSRL control design, a cellular automata model is constructed. Additionally, a case study is conducted, leading to the identification of the optimal design parameters for DSRL control. The proposed DSRL control design is compared with two conventional control designs, namely dedicated right-turn lane control design and static straight-right lane control design, in various geometric and traffic demand scenarios. The findings reveal that the T-shaped intersection, when equipped with a dedicated right-turn lane control design, can achieve a maximum delay optimisation rate of 91% by adopting the DSRL control design. Similarly, the T-shaped intersection, with a static straight-right lane control design, can attain a maximum delay optimisation rate of 84% when employing the DSRL control design.

Keywords:T-shaped intersections, dynamic control, cellular automata, traffic optimisation

References

  1. [1] Liu P, et al. Capacity of U-turn movement at median openings on multilane highways. Journal of Transportation Engineering. 2008;134(4):147–154. DOI: 10.1061/(ASCE)0733-947X(2008)134:4(147).
  2. [2] Combinido JSL, Lim MT. Modeling U-turn traffic flow. Physica A: Statistical Mechanics and its Applications. 2010;389(17):3640–3647. DOI: 10.1016/j.physa.2010.04.009.
  3. [3] Zhao J, Yu J and Zhou X. Saturation flow models of exit lanes for left-turn intersections. Journal of Transportation Engineering, Part A: Systems. 2019;145(3). DOI: 10.1061/jtepbs.0000204.
  4. [4] Guo R, et al. Signal timing and geometric design at contraflow left-turn lane intersections. International Journal of Transportation Science and Technology. 2022;11(3):619–635. DOI: 10.1016/j.ijtst.2021.08.003.
  5. [5] Ding C, et al. Collaborative control of traffic signal and variable guiding lane for isolated intersection under connected and automated vehicle environment. Computer-Aided Civil and Infrastructure Engineering. 2021;37(15):2052–2069. DOI: 10.1111/mice.12780.
  6. [6] Fang Z, et al. Multivariate analysis of traffic flow using copula-based model at an isolated road intersection. Physica A: Statistical Mechanics and its Applications. 2022;599(127431). DOI: 10.1016/j.physa.2022.127431.
  7. [7] Liang S, et al. Optimization design and evaluation analysis of dynamic straight-right lane at signalized intersection. Journal of Highway and Transportation Research and Development (English edition). 2022;16(1):82–91. DOI: 10.1061/JHTRCQ.0000814.
  8. [8] Liang S, et al. Signalized intersection dynamic straight-right lane design and evaluation. Physica A: Statistical Mechanics and its Applications. 2023;128771. DOI: 10.1016/j.physa.2023.128771.
  9. [9] Ghanbarikarekani M, Sohrabi S, Vefghi A. Optimization of signal timing of intersections by internal metering of queue time ratio of vehicles in network scale. Promet – Traffic&Transportation. 2016;28(3):205–214. DOI:10.7307/ptt.v28i3.1729.
  10. [10] Yang Q, et al. Modeling the permissive-only left-turn queue at signals. Physica A: Statistical Mechanics and its Applications. 2019;525:315–325. DOI:10.1016/j.physa.2019.03.070.
  11. [11] Yang Q, Shi Z. The queue dynamics of protected/permissive left turns at pre-timed signalized intersections. Physica A: Statistical Mechanics and its Applications. 2021;562(125406). DOI: 10.1016/j.physa.2020.125406.
  12. [12] Yang Q, et al. Characterizing the dynamics and uncertainty of queues at signalized intersections with left-turn bay. Physica A: Statistical Mechanics and its Applications. 2022;599(127439). DOI: 10.1016/j.physa.2022.127439.
  13. [13] Yang Q, He Y. Right-turn-on-red queueing process at signalized intersections with a short right-turn lane. Physica A: Statistical Mechanics and its Applications. 2022;598(127395). DOI: 10.1016/j.physa.2022.127395.
  14. [14] Zhao J, et al. Increasing the capacity of signalized intersections with dynamic use of exit lanes for left-turn traffic. Transportation Research Record: Journal of the Transportation Research Board. 2013;2355(1):49–59. DOI: 10.3141/2355-06.
  15. [15] Xuan Y, Daganzo CF, Cassidy MJ. Increasing the capacity of signalized intersections with separate left turn phases. Transportation Research Part B: Methodological. 2011;45(5):769–781. DOI: 10.1016/j.trb.2011.02.009.
  16. [16] Chen Q, Yi J, Wu Y. Cellular automaton simulation of vehicles in the contraflow left-turn lane at signalised intersections. IET Intelligent Transport Systems. 2019;13(7):1164–1172. DOI: 10.1049/iet-its.2018.5451.
  17. [17] Liu P, et al. Estimating queue length for contraflow left-turn lane design at signalized intersections. Journal of Transportation Engineering, Part A: Systems. 2019;145(6). DOI: 10.1061/jtepbs.0000240.
  18. [18] Zhao J, Ma W. An alternative design for the intersections with limited traffic lanes and queuing space. IEEE Transactions on Intelligent Transportation Systems. 2021;22(3):1473–1483. DOI: 10.1109/tits.2020.2971353.
  19. [19] Wu J, et al. Developing an actuated signal control strategy to improve the operations of contraflow left-turn lane design at signalized intersections. Transportation Research Part C: Emerging Technologies. 2019;104:53–65. DOI: 10.1016/j.trc.2019.04.028.
  20. [20] Wu J, et al. Operational analysis of the contraflow left-turn lane design at signalized intersections in China. Transportation Research Part C: Emerging Technologies. 2016;69:228–241. DOI: 10.1016/j.trc.2016.06.011.
  21. [21] Chen X, Jia Y. Sustainable traffic management and control system for arterial with contraflow left-turn lanes. Journal of Cleaner Production. 2021;280(124256). DOI: 10.1016/j.jclepro.2020.124256.
  22. [22] Wu J, et al. Stationary condition based performance analysis of the contraflow left-turn lane design considering the influence of the upstream intersection. Transportation Research Part C: Emerging Technologies. 2021;122(102919). DOI: 10.1016/j.trc.2020.102919.
  23. [23] Wolshon B, Lambert L. Reversible lane systems: Synthesis of practice. Journal of Transportation Engineering. 2006;132(12):933–944. DOI: 10.1061/(ASCE)0733-947X(2006)132:12(933).
  24. [24] Di Z, Yang L. Reversible lane network design for maximizing the coupling measure between demand structure and network structure. Transportation Research Part E: Logistics and Transportation Review. 2020;141(102021). DOI: 10.1016/j.tre.2020.102021.
  25. [25] Zhao J, et al. Operational efficiency evaluation of intersections with dynamic lane assignment using field data. Journal of Advanced Transportation. 2017;2017:1–13. DOI: 10.1155/2017/2130385.
  26. [26] Karoonsoontawong A, Lin DY. Time-varying lane-based capacity reversibility for traffic management. Computer-Aided Civil and Infrastructure Engineering. 2011;26(8):632–646. DOI: 10.1111/j.1467-8667.2011.00722.x.
  27. [27] Frejo JRD, et al. Macroscopic modeling and control of reversible lanes on freeways. IEEE Transactions on Intelligent Transportation Systems. 2016;17(4):948–959. DOI: 10.1109/tits.2015.2493127.
  28. [28] Zhang L, Wu G. Dynamic lane grouping at isolated intersections: Problem formulation and performance analysis. Transportation Research Record: Journal of the Transportation Research Board. 2012;2311(1):152–166. DOI: 10.3141/2311-15.
  29. [29] Zhao J, Liu Y, Yang X. Operation of signalized diamond interchanges with frontage roads using dynamic reversible lane control. Transportation Research Part C: Emerging Technologies. 2015;51:196–209. DOI: 10.1016/j.trc.2014.11.010.
  30. [30] Xie C, Turnquist MA. Lane-based evacuation network optimization: An integrated Lagrangian relaxation and tabu search approach. Transportation Research Part C: Emerging Technologies. 2011;19(1):40–63. DOI: 10.1016/j.trc.2010.03.007.
  31. [31] Kotagi PB, Asaithambi G. Microsimulation approach for evaluation of reversible lane operation on urban undivided roads in mixed traffic. Transportmetrica A: Transport Science. 2019;15(2):1613–1636. DOI: 10.1080/23249935.2019.1632387.
  32. [32] Hao Y, et al. Increasing capacity of intersections with transit priority. Promet – Traffic&Transportation. 2016;28(6):627–637. DOI: 10.7307/ptt.v28i6.1999.
  33. [33] Huang J, et al. Effect of pre-signals in a Manhattan-like urban traffic network. Physica A: Statistical Mechanics and its Applications. 2018;503:71–85. DOI: 10.1016/j.physa.2018.02.170.
  34. [34] Gu W, et al. An integrated intersection design for promoting bus and car traffic. Transportation Research Part C: Emerging Technologies. 2021;128(103211). DOI: 10.1016/j.trc.2021.103211.
  35. [35] Liu M, et al. An adaptive timing mechanism for urban traffic pre-signal based on hybrid exploration strategy to improve double deep Q network. Complex & Intelligent Systems. 2022;9(2):2129–2145. DOI: 10.1007/s40747-022-00903-6.
  36. [36] Nagel K, Schreckenberg M. A cellular automaton model for freeway traffic. Journal de Physique I. 1992;2(12):2221–2229. DOI: 10.1051/jp1:1992277.
  37. [37] Rickert M, et al. Two lane traffic simulations using cellular automata. Physica A: Statistical Mechanics and its Applications. 1996;231(4):534–550. DOI: 10.1016/0378-4371(95)00442-4.
  38. [38] El Dessouki WM, Fathi Y, Rouphail N. Meta-optimization using cellular automata with application to the combined trip distribution and assignment system optimal problem. Computer-Aided Civil and Infrastructure Engineering. 2002;16(6):384–398. DOI: 10.1111/0885-9507.00241.
  39. [39] Li XG, et al. A realistic two-lane cellular automata traffic model considering aggressive lane-changing behavior of fast vehicle. Physica A: Statistical Mechanics and its Applications. 2006;367:479–486. DOI: 10.1016/j.physa.2005.11.016.
  40. [40] Wang J, et al. A multi-agent based cellular automata model for intersection traffic control simulation. Physica A: Statistical Mechanics and its Applications. 2021;584(126356). DOI: 10.1016/j.physa.2021.126356.
  41. [41] Liu S, Kong D, Sun L. Cellular automata model for traffic flow with optimised stochastic noise parameter. Promet – Traffic&Transportation. 2022;34(4):567–580. DOI: 10.7307/ptt.v34i4.4049.
Show more


Accelerating Discoveries in Traffic Science |
2024 © Promet - Traffic&Transportation journal