Volume 24 Issue 2
Apr.  2024
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Article Navigation >  Journal of Traffic and Transportation Engineering  > 2024  >  24(2): 207-220
MA Qing-lu, WANG Xin-yu, ZHANG Shu, DUAN Xue-feng. Self-organizing method for traffic coupling between adjacent ramps in intelligent and connected environments[J]. Journal of Traffic and Transportation Engineering, 2024, 24(2): 207-220. doi: 10.19818/j.cnki.1671-1637.2024.02.014
Citation: MA Qing-lu, WANG Xin-yu, ZHANG Shu, DUAN Xue-feng. Self-organizing method for traffic coupling between adjacent ramps in intelligent and connected environments[J]. Journal of Traffic and Transportation Engineering, 2024, 24(2): 207-220. doi: 10.19818/j.cnki.1671-1637.2024.02.014
shu

Self-organizing method for traffic coupling between adjacent ramps in intelligent and connected environments

doi: 10.19818/j.cnki.1671-1637.2024.02.014
  • 1.

    College of Traffic and Transportation, Chongqing Jiaotong University, Chongqing 400074, China

  • 2.

    Chongqing Key Laboratory of Intelligent Integrated Three-Dimensional Transportation, Chongqing Jiaotong University, Chongqing 400074, China

  • 3.

    Ningxia Jiaotou Expressway Management Co., Ltd., Yinchuan 750000, Ningxia, China

Funds:

National Natural Science Foundation of China 52072054

Technology Innovation and Application Development Program of Chongqing CSTB2022TIAD-STX0003

Science and Technology Project of Department of Transportation of Ningxia Hui Autonomous Region NJGF(2020)0301

Graduate Research Innovation Project of Chongqing Jiaotong University CYB23256

More Information
  • Author Bio:

    MA Qing-lu(1980-), male, professor, PhD, qlm@cqjtu.edu.cn

  • Received Date: 2023-05-20
    Available Online: 2024-05-16
  • Publish Date: 2024-04-30
    Abstract
  • A self-organizing method for traffic coupling between adjacent ramps was proposed to improve traffic safety and efficiency in on-ramp merging areas in intelligent and connected environments. By establishing an optimal matching model between the mainline traffic flow gap and on-ramp vehicle speed, the overall headway of the outermost lane of the mainline was optimized and adjusted. On the premise of ensuring the safe merging of on-ramp vehicles, the traffic efficiency of vehicles between adjacent ramps was improved. Two adjacent ramps near the Donghuan overpass on the inner ring expressway in Chongqing were selected as the research prototype. Online map combined with drone aerial photography, fixed-point photography, and other data acquisition methods were used to conduct field investigations on the testing sections. In intelligent and connected environments, cooperative adaptive cruise control (CACC) and traffic coupling self-organizing (TCS) method were applied respectively, and Python, SUMO, and TraCI were used for co-simulation of vehicle operation on the test road. Research results show that compared with CACC, the lane changing number in TCS decreases by 19.87% from 65.52 to 52.64, which effectively alleviates the traffic conflict between adjacent ramps. The average delay decreases by 70.38% from 24.53 s to 14.39 s. To be specific, the average delay decreases by 77.71% in the off-peak period and 34.50% in the peak period, respectively. Compared with the peak period, the efficiency in the off-peak period is greatly improved. The time occupancy decreases by 53.86% from 18.70% to 8.63%. The time occupancy difference between different lanes decreases to 6.00%, that is, vehicles are more evenly distributed across different lanes. The average speed increases by 3.06% from 78.31 km·h-1 to 80.78 km·h-1, which effectively alleviates the deceleration near the on-ramp merging and off-ramp diverging areas.

     

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    • References(31)
  • [1]
    MA Q L, WANG X Y, ZHANG S, et al. Distributed self-organizing control of CAVs between multiple adjacent-ramps[J]. IEEE Transactions on Intelligent Transportation Systems, 2023, 24(5): 5430-5441. doi: 10.1109/TITS.2023.3244185
    [2]
    杨澜, 赵祥模, 吴国垣, 等. 智能网联汽车协同生态驾驶策略综述[J]. 交通运输工程学报, 2020, 20(5): 58-72. doi: 10.19818/j.cnki.1671-1637.2020.05.004

    YANG Lan, ZHAO Xiang-mo, WU Guo-yuan, et al. Review on connected and automated vehicles based cooperative eco-driving strategies[J]. Journal of Traffic and Transportation Engineering, 2020, 20(5): 58-72. (in Chinese) doi: 10.19818/j.cnki.1671-1637.2020.05.004
    [3]
    MEHR G, ESKANDARIAN A. Sentinel: an onboard lane change advisory system for intelligent vehicles to reduce traffic delay during freeway incidents[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(7): 8906-8917. doi: 10.1109/TITS.2021.3087578
    [4]
    吴文静, 战勇斌, 杨丽丽, 等. 考虑安全间距的合流区可变限速协调控制方法[J]. 吉林大学学报(工学版), 2022, 52(6): 1315-1323. https://www.cnki.com.cn/Article/CJFDTOTAL-JLGY202206009.htm

    WU Wen-jing, ZHAN Yong-bin, YANG Li-li, et al. Coordinated control method of variable speed limit in on-ramp area considering safety distance[J]. Journal of Jilin University (Engineering and Technology Edition), 2022, 52(6): 1315-1323. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JLGY202206009.htm
    [5]
    ALI SILGU M, ERDAĞI İ, GÖKSU G, et al. Combined control of freeway traffic involving cooperative adaptive cruise controlled and human driven vehicles using feedback control through SUMO[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(8): 11011-11025. doi: 10.1109/TITS.2021.3098640
    [6]
    LIU J Q, ZHAO W Z, XU C. An efficient on-ramp merging strategy for connected and automated vehicles in multi-lane traffic[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(6): 5056-5067. doi: 10.1109/TITS.2020.3046643
    [7]
    马庆禄, 乔娅, 冯敏. 变道约束下近邻交织区交通均衡组织方法[J]. 交通运输系统工程与信息, 2019, 19(4): 164-171. https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT201904024.htm

    MA Qing-lu, QIAO Ya, FENG Min. Traffic equilibrium organization method for neighbor weaving sections based on lane-changing constraints[J]. Journal of Transportation Systems Engineering and Information Technology, 2019, 19(4): 164-171. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT201904024.htm
    [8]
    JING S C, HUI F, ZHAO X M, et al. Cooperative game approach to optimal merging sequence and on-ramp merging control of connected and automated vehicles[J]. IEEE Transactions on Intelligent Transportation Systems, 2019, 20(11): 4234-4244. doi: 10.1109/TITS.2019.2925871
    [9]
    李巧茹, 王少航, 陈亮. 高速公路合流区可变限速和换道协同控制研究[J]. 重庆交通大学学报(自然科学版), 2022, 41(2): 35-43. doi: 10.3969/j.issn.1674-0696.2022.02.06

    LI Qiao-ru, WANG Shao-hang, CHEN Liang. Cooperative control of variable speed limit and lane change in expressway confluence area[J]. Journal of Chongqing Jiaotong University (Natural Science Edition), 2022, 41(2): 35-43. (in Chinese) doi: 10.3969/j.issn.1674-0696.2022.02.06
    [10]
    WANG S H, ZHAO M, SUN D H, et al. On-ramp merging strategy with two-stage optimization based on fully proactive and cooperative merging of vehicles[J]. Journal of Transportation Engineering, Part A: Systems, 2023, 149(4): 04023005. doi: 10.1061/JTEPBS.TEENG-7194
    [11]
    NTOUSAKIS I A, NIKOLOS I K, PAPAGEORGIOU M. Optimal vehicle trajectory planning in the context of cooperative merging on highways[J]. Transportation Research Part C: Emerging Technologies, 2016, 71: 464-488. doi: 10.1016/j.trc.2016.08.007
    [12]
    DING Heng, DI Yun-ran, ZHENG Xiao-yan, et al. Automated cooperative control of multilane freeway merging areas in connected and autonomous vehicle environments[J]. Transportmetrica B: Transport Dynamics, 2021, 9(1): 437-455. doi: 10.1080/21680566.2021.1887774
    [13]
    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
    [14]
    邹祥莉, 徐建闽, 于洁涵, 等. 基于分层递阶结构和S模型预测控制的快速路多匝道协同控制模型研究[J]. 公路工程, 2019, 44(5): 105-109, 161. https://www.cnki.com.cn/Article/CJFDTOTAL-ZNGL201905021.htm

    ZOU Xiang-li, XU Jian-min, YU Jie-han, et al. Research on expressway multi-ramp collaborative control model based on hierarchical structure and S-model predictive control[J]. Highway Engineering, 2019, 44(5): 105-109, 161. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZNGL201905021.htm
    [15]
    HAN Y, WANG M, LI L H, et al. A physics-informed reinforcement learning-based strategy for local and coordinated ramp metering[J]. Transportation Research Part C: Emerging Technologies, 2022, 137: 103584. doi: 10.1016/j.trc.2022.103584
    [16]
    MEGAT JOHARI M U, MEGAT JOHARI N, SAVOLAINEN P T, et al. Safety evaluation of freeway exit ramps with advisory speed reductions[J]. Transportation Research Record, 2023, 2677(1): 503-512. doi: 10.1177/03611981221099908
    [17]
    GU C Y, WU C Z, WU Y H, et al. Distributionally robust ramp metering under traffic demand uncertainty[J]. Transportmetrica B: Transport Dynamics, 2022, 10(1): 652-666. doi: 10.1080/21680566.2022.2025952
    [18]
    POOLADSANJ M, SAVLA K, IOANNOU P A. Ramp metering to maximize freeway throughput under vehicle safety constraints[J]. Transportation Research Part C: Emerging Technologies, 2023, 154: 104267. doi: 10.1016/j.trc.2023.104267
    [19]
    PENG C, XU C C. A coordinated ramp metering framework based on heterogeneous causal inference[J]. Computer-Aided Civil and Infrastructure Engineering, 2023, 38: 1365-1380. doi: 10.1111/mice.12994
    [20]
    GU C Y, ZHOU T, WU C Z. Deep Koopman traffic modeling for freeway ramp metering[J]. IEEE Transactions on Intelligent Transportation Systems, 2023, 24(6): 6001-6013. doi: 10.1109/TITS.2023.3248649
    [21]
    ZHANG C, MA W, ZHAO J, et al. Destination-aware coordinated ramp metering for preventing off-ramp queue spillover and mainstream congestion[J]. IEEE Intelligent Transportation Systems Magazine, 2024, 16(1): 40-61. doi: 10.1109/MITS.2023.3323029
    [22]
    KUSUMA A, LIU R H, CHOUDHURY C, Modelling lane-changing mechanisms on motorway weaving sections[J]. Transportmetrica B: Transport Dynamics, 2020, 8(1): 1-21. doi: 10.1080/21680566.2019.1703840
    [23]
    TIAN H Q, WEI C, JIANG C Y, et al. Personalized lane change planning and control by imitation learning from drivers[J]. IEEE Transactions on Industrial Electronics, 2023, 70(4): 3995-4006. doi: 10.1109/TIE.2022.3177788
    [24]
    BAGHERI M, BARTIN B, OZBAY K. Implementing artificial neural network-based gap acceptance models in the simulation model of a traffic circle in SUMO[J]. Transportation Research Record, 2023, 2677(12): 227-239. doi: 10.1177/03611981231167420
    [25]
    MONTEIRO F V, IOANNOU P. Safe autonomous lane changes and impact on traffic flow in a connected vehicle environment[J]. Transportation Research Part C: Emerging Technologies, 2023, 151: 104138. doi: 10.1016/j.trc.2023.104138
    [26]
    CHEN J M, ZHOU Y, CHUNG E. An integrated approach to optimal merging sequence generation and trajectory planning of connected automated vehicles for freeway on-ramp merging sections[J]. IEEE Transactions on Intelligent Transportation Systems, 2024, 25(2): 1897-1912. doi: 10.1109/TITS.2023.3315650
    [27]
    王正武, 潘军良, 陈涛, 等. 单向三车道高速公路合流区智能网联车辆协同汇入控制[J]. 交通运输工程学报, 2023, 23(6): 270-282. doi: 10.19818/j.cnki.1671-1637.2023.06.018

    WANG Zheng-wu, PAN Jun-liang, CHEN Tao, et al. Cooperative merging control of connected and automated vehicles in merging area for one-way three-lane freeway[J]. Journal of Traffic and Transportation Engineering, 2023, 23(6): 270-282. (in Chinese) doi: 10.19818/j.cnki.1671-1637.2023.06.018
    [28]
    马艳丽, 祁首铭, 吴昊天, 等. 基于PET算法的匝道合流区交通冲突识别模型[J]. 交通运输系统工程与信息, 2018, 18(2): 142-148. https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT201802022.htm

    MA Yan-li, QI Shou-ming, WU Hao-tian, et al. Traffic conflict identification model based on post encroachment time algorithm in ramp merging area[J]. Journal of Transportation Systems Engineering and Information Technology, 2018, 18(2): 142-148. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT201802022.htm
    [29]
    谢光强, 赵俊伟, 李杨, 等. 基于多集群系统的车辆协同换道控制[J]. 广东工业大学学报, 2021, 38(5): 1-9. doi: 10.12052/gdutxb.210050

    XIE Guang-qiang, ZHAO Jun-wei, LI Yang, et al. Cooperative lane-changing based on multi-cluster system[J]. Journal of Guangdong University of Technology, 2021, 38(5): 1-9. (in Chinese) doi: 10.12052/gdutxb.210050
    [30]
    常玉林, 张成祥, 张鹏, 等. 车联网环境下基于间隙优化的无信号交叉口车速控制方法[J]. 重庆理工大学学报(自然科学), 2021, 35(3): 10-17, 60. https://www.cnki.com.cn/Article/CJFDTOTAL-CGGL202103003.htm

    CHANG Yu-lin, ZHANG Cheng-xiang, ZHANG Peng, et al. A speed control method of non-signalized intersection based on gap optimization under connected vehicle environment[J]. Journal of Chongqing University of Technology (Natural Science), 2021, 35(3): 10-17, 60. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-CGGL202103003.htm
    [31]
    刘伟, 陈科全, 田宗忠, 等. 基于密度熵的道路交通事故影响范围分区模型[J]. 交通运输工程学报, 2019, 19(6): 163-170. doi: 10.19818/j.cnki.1671-1637.2019.06.015

    LIU Wei, CHEN Ke-quan, TIAN Zong-zhong, et al. Partition model of road traffic accident influence area based on density entropy[J]. Journal of Traffic and Transportation Engineering, 2019, 19(6): 163-170. (in Chinese) doi: 10.19818/j.cnki.1671-1637.2019.06.015
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