Volume 23 Issue 2
Apr.  2023
Turn off MathJax
Article Contents
HUANG Wei, HU Yang. Cell transmission model considering queuing characteristics of channelized zone at intersections[J]. Journal of Traffic and Transportation Engineering, 2023, 23(2): 212-224. doi: 10.19818/j.cnki.1671-1637.2023.02.015
Citation: HUANG Wei, HU Yang. Cell transmission model considering queuing characteristics of channelized zone at intersections[J]. Journal of Traffic and Transportation Engineering, 2023, 23(2): 212-224. doi: 10.19818/j.cnki.1671-1637.2023.02.015

Cell transmission model considering queuing characteristics of channelized zone at intersections

doi: 10.19818/j.cnki.1671-1637.2023.02.015
Funds:

National Natural Science Foundation of China 52102401

Guangdong Basic and Applied Basic Research Foundation 2019A1515111083

More Information
  • Author Bio:

    HUANG Wei(1986-), female, associate professor, PhD, huangwei5@mail.sysu.edu.cn

  • Received Date: 2022-10-05
    Available Online: 2023-05-09
  • Publish Date: 2023-04-25
  • In order to describe the evolution law of traffic flows at urban intersections more accurately, the signalized intersection with entrance widening areas and shared lanes was taken as the research object, and the cell transmission model (CTM) was improved by considering four practical factors: queue discharge process, divergence process, optional lane changing, and shared lanes. According to the geometric characteristics of the intersection, a method to divide cells at road sections was proposed based on lane groups. On this basis, the cell sending capacity function was adjusted to reflect and model the queue discharge process. The blocking factors were introduced in the divergence process modeling to describe the interaction of spatial queuing among different lane groups. The optional lane changing behavior in the transition zone was modeled with the goal of balancing the spatial queuing of adjacent lane groups, and the conflict effect of traffic flows with different directions was considered in the modeling of shared lanes. On the basis of an actual intersection, the maximum queue length of the lane group cycle was selected as the evaluation index to verify the effectiveness of the improved CTM. Test results show that the improved CTM can simultaneously estimate the queue lengths of different lane groups. With the increase in the proportion of through traffic flows, the estimation error of the improved CTM decreases. The mean absolute error (MAE), root mean square error (RMSE), and weighted mean absolute percentage error (WMAPE) of the maximum queue length at road sections are less than 16.43, 21.36 m, and 13.51%, respectively, under different traffic scenarios. Compared with the benchmark method, the improved CTM can reduce the MAE by 15.31%-90.03% for the maximum queue length at road sections under different scenarios, and the estimation accuracy under high-traffic scenarios improves more obviously. Thus, it can be seen that the improved CTM can more accurately describe the operational characteristics of traffic flow at intersections and improve the estimation accuracy of queue length, which can be used as an important basis for the traffic management and control.

     

  • loading
  • [1]
    GUO Qiang-qiang, LI Li, BAN X J. Urban traffic signal control with connected and automated vehicles: a survey[J]. Transportation Research Part C: Emerging Technologies, 2019, 101: 313-334. doi: 10.1016/j.trc.2019.01.026
    [2]
    李素兰, 张谢东, 施俊庆, 等. 信号控制交叉口交通流建模与通行能力分析[J]. 公路交通科技, 2017, 34(12): 108-114. https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK201712017.htm

    LI Su-lan, ZHANG Xie-dong, SHI Jun-qing, et al. Traffic flow modeling and capacity analysis of signalized intersection[J]. Journal of Highway and Transportation Research and Development, 2017, 34(12): 108-114. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK201712017.htm
    [3]
    LIGHTHILL M J, WHITHAM G B. On kinematic waves. Ⅱ. A theory of traffic flow on long crowded roads[J]. Proceedings of the Royal Society of London Series A, Mathematical and Physical Sciences, 1955, 229(1178): 317-345.
    [4]
    RICHARDS P I. Shock waves on the highway[J]. Operations Research, 1956, 4(1): 42-51. doi: 10.1287/opre.4.1.42
    [5]
    DAGANZO C F. The cell transmission model: a dynamic representation of highway traffic consistent with the hydrodynamic theory[J]. Transportation Research Part B: Methodological, 1994, 28(4): 269-287. doi: 10.1016/0191-2615(94)90002-7
    [6]
    DAGANZO C F. The cell transmission model, Part Ⅱ: network traffic[J]. Transportation Research Part B: Methodological, 1995, 29(2): 79-93. doi: 10.1016/0191-2615(94)00022-R
    [7]
    孙剑, 殷炬元, 黎淘宁. 快速路入口匝道瓶颈宏观交通流模型[J]. 交通运输工程学报, 2019, 19(3): 122-133. doi: 10.3969/j.issn.1671-1637.2019.03.013

    SUN Jian, YIN Ju-yuan, LI Tao-ning. Macroscopic traffic flow model of expressway on-ramp bottlenecks[J]. Journal of Traffic and Transportation Engineering, 2019, 19(3): 122-133. (in Chinese) doi: 10.3969/j.issn.1671-1637.2019.03.013
    [8]
    WANG Yi-bing, ZHAO Ming-ming, YU Xiang-hua, et al. Real-time joint traffic state and model parameter estimation on freeways with fixed sensors and connected vehicles: state-of-the-art overview, methods, and case studies[J]. Transportation Research Part C: Emerging Technologies, 2022, 134: 103444. doi: 10.1016/j.trc.2021.103444
    [9]
    ADACHER L, TIRIOLO M. A macroscopic model with the advantages of microscopic model: a review of cell transmission model's extensions for urban traffic networks[J]. Simulation Modelling Practice and Theory, 2018, 86: 102-119. doi: 10.1016/j.simpat.2018.05.003
    [10]
    SRIVASTAVA A, JIN Wen-long, LEBACQUE J P. A modified cell transmission model with realistic queue discharge features at signalized intersections[J]. Transportation Research Part B: Methodological, 2015, 81: 302-315. doi: 10.1016/j.trb.2015.05.013
    [11]
    RONCOLI C, PAPAGEORGIOU M, PAPAMICHAIL I. Traffic flow optimisation in presence of vehicle automation and communication systems—Part I: a first-order multi-lane model for motorway traffic[J]. Transportation Research Part C: Emerging Technologies, 2015, 57: 241-259. doi: 10.1016/j.trc.2015.06.014
    [12]
    HAN Yu, YUAN Yu-fei, HEGYI A, et al. New extended discrete first-order model to reproduce propagation of jam waves[J]. Transportation Research Record, 2016, 2560(1): 108-118. doi: 10.3141/2560-12
    [13]
    HAN Yu, HEGYI A, YUAN Yu-fei, et al. Resolving freeway jam waves by discrete first-order model-based predictive control of variable speed limits[J]. Transportation Research Part C: Emerging Technologies, 2017, 77: 405-420. doi: 10.1016/j.trc.2017.02.009
    [14]
    YUAN Kai, KNOOP V L, HOOGENDOORN S P. A kinematic wave model in Lagrangian coordinates incorporating capacity drop: application to homogeneous road stretches and discontinuities[J]. Physica A: Statistical Mechanics and Its Applications, 2017, 465: 472-485. doi: 10.1016/j.physa.2016.08.060
    [15]
    KONTORINAKI M, SPILIOPOULOU A, RONCOLI C, et al. First-order traffic flow models incorporating capacity drop: overview and real-data validation[J]. Transportation Research Part B: Methodological, 2017, 106: 52-75. doi: 10.1016/j.trb.2017.10.014
    [16]
    SHIRKE C, BHASKAR A, CHUNG E. Macroscopic modelling of arterial traffic: an extension to the cell transmission model[J]. Transportation Research Part C: Emerging Technologies, 2019, 105: 54-80. doi: 10.1016/j.trc.2019.05.033
    [17]
    龙建成. 城市道路交通拥堵传播规律及消散控制策略研究[D]. 北京: 北京交通大学, 2009.

    LONG Jian-cheng. Studies on congestion propagation properties and dissipation control strategies of urban road traffic[D]. Beijing: Beijing Jiaotong University, 2009. (in Chinese)
    [18]
    姚凯斌, 林培群. 一种考虑交叉口因素的改进元胞传输模型[J]. 交通运输系统工程与信息, 2017, 17(3): 105-111. https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT201703016.htm

    YAO Kai-bin, LIN Pei-qun. An improved cell transmission model considering intersection factor[J]. Journal of Transportation Systems Engineering and Information Technology, 2017, 17(3): 105-111. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT201703016.htm
    [19]
    胡晓健, 王炜, 盛慧. 基于可变元胞传输模型的城市道路交通流估计方法[J]. 交通运输系统工程与信息, 2010, 10(4): 73-78. doi: 10.3969/j.issn.1009-6744.2010.04.011

    HU Xiao-jian, WANG Wei, SHENG Hui. Urban traffic flow prediction with variable cell transmission model[J]. Journal of Transportation Systems Engineering and Information Technology, 2010, 10(4): 73-78. (in Chinese) doi: 10.3969/j.issn.1009-6744.2010.04.011
    [20]
    刘昊翔. 基于元胞传输模型的交叉口交通控制与优化研究[D]. 北京: 北京交通大学, 2011.

    LIU Hao-xiang. Traffic controlling and optimizing at an intersection based on the cell transmission model[D]. Beijing: Beijing Jiaotong University, 2011. (in Chinese)
    [21]
    LI Zi-chuan. Modeling arterial signal optimization with enhanced cell transmission formulations[J]. Journal of Transportation Engineering, 2011, 137(7): 445-454. doi: 10.1061/(ASCE)TE.1943-5436.0000232
    [22]
    LIU Yue, CHANG G L. An arterial signal optimization model for intersections experiencing queue spillback and lane blockage[J]. Transportation Research Part C: Emerging Technologies, 2011, 19(1): 130-144. doi: 10.1016/j.trc.2010.04.005
    [23]
    TIRIOLO M, ADACHER L, CIPRIANI E. An urban traffic flow model to capture complex flow interactions among lane groups for signalized intersections[J]. Procedia—Social and Behavioral Sciences, 2014, 111: 839-848. doi: 10.1016/j.sbspro.2014.01.118
    [24]
    CAREY M, BALIJEPALLI C, WATLING D. Extending the cell transmission model to multiple lanes and lane-changing[J]. Networks and Spatial Economics, 2015, 15(3): 507-535. doi: 10.1007/s11067-013-9193-7
    [25]
    KIM Y, CHOI S, YEO H. Extended urban cell transmission model using agent-based modeling[J]. Procedia Computer Science, 2020, 170: 354-361. doi: 10.1016/j.procs.2020.03.058
    [26]
    KIM Y, CHOI S, PARK J, et al. Agent-based mesoscopic urban traffic simulation based on multi-lane cell transmission model[J]. Procedia Computer Science, 2019, 151: 240-247. doi: 10.1016/j.procs.2019.04.035
    [27]
    SUBRAVETI H H S N, KNOOP V L, VAN AREM B. First order multi-lane traffic flow model—an incentive based macroscopic model to represent lane change dynamics[J]. Transportmetrica B: Transport Dynamics, 2019, 7(1): 1758-1779. doi: 10.1080/21680566.2019.1700846
    [28]
    秦严严, 张健, 陈凌志, 等. 手动-自动驾驶混合交通流元胞传输模型[J]. 交通运输工程学报, 2020, 20(2): 229-238. https://www.cnki.com.cn/Article/CJFDTOTAL-JYGC202002019.htm

    QIN Yan-yan, ZHANG Jian, CHEN Ling-zhi, et al. Cell transmission model of mixed traffic flow of manual-automated driving[J]. Journal of Traffic and Transportation Engineering, 2020, 20(2): 229-238. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JYGC202002019.htm
    [29]
    HAO Zhen-zhen, BOEL R, LI Zhi-wu. Model based urban traffic control, Part Ⅰ: local model and local model predictive controllers[J]. Transportation Research Part C: Emerging Technologies, 2018, 97: 61-81. doi: 10.1016/j.trc.2018.09.026
    [30]
    WU Ning. Modelling blockage probability and capacity of shared lanes at signalized intersections[J]. Procedia—Social and Behavioral Sciences, 2011, 16: 481-491. doi: 10.1016/j.sbspro.2011.04.469
    [31]
    ZHAO Shu-zhi, LIANG Shi-dong, LIU Hua-sheng, et al. CTM based real-time queue length estimation at signalized intersection[J]. Mathematical Problems in Engineering, 2015, 2015: 328712.
    [32]
    LONG Jian-cheng, GAO Zi-you, ZHAO Xiao-mei, et al. Urban traffic jam simulation based on the cell transmission model[J]. Networks and Spatial Economics, 2011, 11(1): 43-64.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (443) PDF downloads(113) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return