Volume 41 Issue 5
Oct.  2023
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GAO Jinyong, LUO Sheng, WANG Xinyuan, ZHOU Cheng, AN Lianhua. A Control Method for Mixed Traffic Flows with CAVs and HDVs on Freeways[J]. Journal of Transport Information and Safety, 2023, 41(5): 74-82. doi: 10.3963/j.jssn.1674-4861.2023.05.008
Citation: GAO Jinyong, LUO Sheng, WANG Xinyuan, ZHOU Cheng, AN Lianhua. A Control Method for Mixed Traffic Flows with CAVs and HDVs on Freeways[J]. Journal of Transport Information and Safety, 2023, 41(5): 74-82. doi: 10.3963/j.jssn.1674-4861.2023.05.008

A Control Method for Mixed Traffic Flows with CAVs and HDVs on Freeways

doi: 10.3963/j.jssn.1674-4861.2023.05.008
  • Received Date: 2022-03-29
    Available Online: 2024-01-18
  • The mixed traffic with connected and automated vehicles (CAVs) and human-driven vehicles (HDVs) is an ongoing trend. Improving traffic control capabilities through CAVs' precision and control advantages is a key focus area. By regulating the desired cruising speed of CAVs on the upstream segment, it indirectly influences HD-Vs'speeds, enabling fine-tuning control of traffic demand upstream. Considering the time-varying nature of traffic flow and the need for comfortable driving, a model predictive control approach is used. This model uses CAVs' speed as the controlling factor, creating a traffic control model. It aims to minimize deviations in flow control and changes in CAVs' speeds for optimized control processes. A distributed solution algorithm for the control model is designed. The solution algorithm enhances the model's speed of resolution. The effectiveness of the proposed control model is verified through VISSIM simulation. It shows that the control accuracy exceeds 80% across different CAVs penetration rates, demand levels, target demand drop rates, and update time intervals. The control strategy has a solu-tion time of less than 0.1 seconds. It enables real-time control requirements for CAVs, thereby efficiently reducing traffic flow towards the target to avoid congestion downstream. The model can potentially decrease the upstream de-mand flow by up to 40%, enabling it to effectively manage significant fluctuations in highway demand and reduce highway bottleneck congestion. This method has reference significance for preventing highway congestion and im-proving traffic efficiency. It also provides a reference for the development of active traffic control methods based on CAVs.

     

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  • [1]
    HU J, SCHROEDER B J, ROUPHAIL N M. Rationale for incorporating queue discharge flow into highway capacity manual procedure for analysis of freeway facilities[J]. Transportation Research Record Journal of the Transportation Research Board, 2012(1): 76-83.
    [2]
    CARLSON R C, PAPAMICHAIL I, PAPGEORGIOU M. Local feedback-based mainstream traffic flow control on motorways using variable speed limits[J]. IEEE Transactions on Intelligent Transportation Systems, 2011, 12(4): 1261-1276. doi: 10.1109/TITS.2011.2156792
    [3]
    庞俊恒. 高速公路主线瓶颈区可变限控制研究[D]. 成都: 西南交通大学, 2017.

    PANG J H. Study of variable speed limit control at bottlenecks of freeway mainline[D]. Chengdu: Southwest Jiaotong University, 2017. (in Chinese)
    [4]
    LI D, RANJITKAR P, CEDER A. A logic tree based algorithm for variable speed limit controllers to manage recurrently congested bottlenecks[C]. Transportation Research Board 93rd Annual Meeting, Washington D C, America: Transportation Research Board, 2014.
    [5]
    HELLINGA B, MANDELZYS M. Impact of driver compliance on the safety and operational impacts of freeway variable speed limit systems[J]. Journal of Transportation Engineering, 2011, 137(4): 260-268. doi: 10.1061/(ASCE)TE.1943-5436.0000214
    [6]
    王艳丽, 李晓庆, 王忠宇, 等. 面向出口匝道拥挤的快速路速度协调控制模型[J]. 同济大学学报(自然科学版), 2018, 46 (7): 905-912.

    WANG Y L, LI X Q, WANG Z Y, et al. Speed harmonization model for off-ramp bottlenecks on urban expressway[J]. Journal of Tongji University(Natural Science), 2018, 46(7): 905-912. (in Chinese)
    [7]
    MA J, LI X, SHLADOVER S, et al. Freeway speed harmonization[J]. IEEE Transactions on Intelligent Vehicles, 2016 (1): 78-89.
    [8]
    胡笳, 安连华, 李欣. 面向新型混合交通流的快速路合流区通行能力建模[J]. 交通信息与安全, 2021, 39(1): 137-144. doi: 10.3963/j.jssn.1674-4861.2021.01.016

    HU J, AN L H, LI X. A capacity model of freeway merging areas with partially connected automated traffic[J]. Journal of TransportInformation and Safety, 2021, 39(1): 137-144. (in Chinese) doi: 10.3963/j.jssn.1674-4861.2021.01.016
    [9]
    WANG M, DAAMEN W, HOOGENDOORN S P, et al. Connected variable speed limits control and car-following control with vehicle-infrastructure communication to resolve stop-and-go waves[J]. Journal of Intelligent Transportation Systems, 20(6): 559-572. doi: 10.1080/15472450.2016.1157022
    [10]
    YU M, FAN W D. Optimal variable speed limit control in connected autonomous vehicle environment for relieving freeway congestion[J]. Journal of Transportation Engineering, Part A: Systems, 2019, 145(4): 04019007. doi: 10.1061/JTEPBS.0000227
    [11]
    GOULET N, AYALEW B. Impacts of distributed speed harmonization and optimal maneuver planning on multi-lane roads[C]. 2020 IEEE Conference on Control Technology and Applications(CCTA), Trieste, Italy: IEEE, 2020.
    [12]
    庞宇成. 混合车流下高速公路车道变窄区限速控制研究[D]. 重庆: 重庆大学, 2021.

    PANG Y C. Research on variable speed control in lane drop of expressway for mixed traffic[D]. Chongqing: Chongqing University, 2021. (in Chinese)
    [13]
    GHIASI A, LI X, MA J. A mixed traffic speed harmonization model with connected autonomous vehicles[J]. Transportation Research Part C: Emerging Technologies, 2019, 104: 210-233. doi: 10.1016/j.trc.2019.05.005
    [14]
    ARD T, DOLLAR R A, VAHIDI A, et al. Microsimulation of energy and flow effects from optimal automated driving in mixed traffic[J]. Transportation Research Part C: Emerging Technologies, 2020, 120: 102806. doi: 10.1016/j.trc.2020.102806
    [15]
    宋晓晨, 曲大义, 贾彦峰, 等. 网联环境下混合车流的速度协调优化方法研究[J]. 广西大学学报(自然科学版), 2022, 47(3): 804-812.

    SONG X C, QU D Y, JIAY F, et al. Research on speed coordination and optimization method of mixed traffic flow in networked environment[J]. Journal of Guangxi University(Natural Science Edition), 2022, 47(3): 804-812. (in Chinese)
    [16]
    YANG G, AHMED M, GAWEESH S, et al. Connected vehicle real-time traveler information messages for freeway speed harmonization under adverse weather conditions: trajectory level analysis using driving simulator[J]. Accident Analysis & Prevention, 2020, 146: 105707.
    [17]
    AN L, LAI J, YANG X, et al. Speed harmonization for partially connected and automated traffic[C]. 2021 IEEE Intelligent Vehicles Symposium(IV), Nagoya, Japan: IEEE, 2021.
    [18]
    AN L, YANG X, HU J. Modeling system dynamics of mixed traffic with partial connected and automated vehicles[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(9): 15755-15764. doi: 10.1109/TITS.2022.3145395
    [19]
    STELLATO B, BANJAC G, GOULART P, et al. OSQP: An operator splitting solver for quadratic programs[J]. Mathematical Programming Computation, 2020, 12(4): 637-672. doi: 10.1007/s12532-020-00179-2
    [20]
    DOWLING R, NEVERS B, JIAA, et al. Performance benefits of connected vehicles for implementing speed harmonization[J]. Transportation Research Procedia, 2016, 15: 459-470. doi: 10.1016/j.trpro.2016.06.039
    [21]
    MAILKOPOULOS A A, HONG S, PARK B B, et al. Optimal control for speed harmonization of automated vehicles[J]. IEEE Transactions on Intelligent Transportation Systems, 2018, 20(7): 2405-2417.
    [22]
    CUI L, HU J, PARK B B, et al. Development of a simulation platform for safety impact analysis considering vehicle dynamics, sensor errors, and communication latencies: Assessing cooperative adaptive cruise control under cyber attack[J]. Transportation Research Part C: Emerging Technologies, 2018, 97: 1-22. doi: 10.1016/j.trc.2018.10.005
    [23]
    LAI J, HU J, CUI L, et al. A generic simulation platform for cooperative adaptive cruise control under partially connected and automated environment[J]. Transportation Research Part C: Emerging Technologies, 2020, 121: 102874. doi: 10.1016/j.trc.2020.102874
    [24]
    赵杭, 赵敏, 孙棣华, 等. 面向快速路交通瓶颈的混合交通群体节流控制策略[J]. 交通运输工程学报, 2022, 22(3): 162-173.

    ZHAO H, ZHAO M, SUN D H, et al. Mixed traffic group throttling control strategy for traffic bottleneck of expressway[J]. Journal of Traffic and Transportation Engineering, 2022, 22(3): 162-173. (in Chinese)
    [25]
    徐建闽, 杨招波, 马莹莹. 面向移动瓶颈的高速公路流量控制模型研究[J]. 广西师范大学学报(自然科学版), 2020, 38 (3): 1-10.

    XU J M, YANG Z B, MA Y Y, et al. Research on freeway flow control model moving bottleneck[J]. Journal of Guangxi Normal University (Natural Science Edition), 2020, 38(3): 1-10. (in Chinese)
    [26]
    TALEBPOUR A, MAHMASSANI H S, HAMDAR S H. Speed harmonization: Evaluation of effectiveness under congested conditions[J]. Transportation research record, 2013, 2391(1): 69-79. doi: 10.3141/2391-07
    [27]
    HAN Y, WANG M, HE Z, et al. A linear Lagrangian model predictive controller of macro-and micro-variable speed limits to eliminate freeway jam waves[J]. Transportation Research Part C: Emerging Technologies, 2021, 128: 103121.
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