Research article

Mixed traffic flow of human-driven vehicles and connected autonomous vehicles: String stability and fundamental diagram


  • Received: 08 September 2022 Revised: 12 November 2022 Accepted: 13 November 2022 Published: 17 November 2022
  • The introduction of connected autonomous vehicles (CAVs) gives rise to mixed traffic flow on the roadway, and the coexistence of human-driven vehicles (HVs) and CAVs may last for several decades. CAVs are expected to improve the efficiency of mixed traffic flow. In this paper, the car-following behavior of HVs is modeled by the intelligent driver model (IDM) based on actual trajectory data. The cooperative adaptive cruise control (CACC) model from the PATH laboratory is adopted for the car-following model of CAVs. The string stability of mixed traffic flow is analyzed for different market penetration rates of CAVs, showing that CAVs can effectively prevent stop-and-go waves from forming and propagating. In addition, the fundamental diagram is obtained from the equilibrium state, and the flow-density chart indicates that CAVs can improve the capacity of mixed traffic flow. Furthermore, the periodic boundary condition is designed for numerical simulation according to the infinite length platoon assumption in the analytical approach. The simulation results are consistent with the analytical solutions, suggesting the validity of the string stability and fundamental diagram analysis of mixed traffic flow.

    Citation: Lijing Ma, Shiru Qu, Jie Ren, Xiangzhou Zhang. Mixed traffic flow of human-driven vehicles and connected autonomous vehicles: String stability and fundamental diagram[J]. Mathematical Biosciences and Engineering, 2023, 20(2): 2280-2295. doi: 10.3934/mbe.2023107

    Related Papers:

  • The introduction of connected autonomous vehicles (CAVs) gives rise to mixed traffic flow on the roadway, and the coexistence of human-driven vehicles (HVs) and CAVs may last for several decades. CAVs are expected to improve the efficiency of mixed traffic flow. In this paper, the car-following behavior of HVs is modeled by the intelligent driver model (IDM) based on actual trajectory data. The cooperative adaptive cruise control (CACC) model from the PATH laboratory is adopted for the car-following model of CAVs. The string stability of mixed traffic flow is analyzed for different market penetration rates of CAVs, showing that CAVs can effectively prevent stop-and-go waves from forming and propagating. In addition, the fundamental diagram is obtained from the equilibrium state, and the flow-density chart indicates that CAVs can improve the capacity of mixed traffic flow. Furthermore, the periodic boundary condition is designed for numerical simulation according to the infinite length platoon assumption in the analytical approach. The simulation results are consistent with the analytical solutions, suggesting the validity of the string stability and fundamental diagram analysis of mixed traffic flow.



    加载中


    [1] A. Talebpour, H. S. Mahmassani, Influence of connected and autonomous vehicles on traffic flow stability and throughput, Transp. Res. C Emerg. Tech., 71 (2016), 143–163. https://doi.org/10.1016/j.trc.2016.07.007 doi: 10.1016/j.trc.2016.07.007
    [2] P. Bansal, K. M. Kockelman, Forecasting americans' long-term adoption of connected and autonomous vehicle technologies, Transp. Res. A Pol., 95 (2017), 49–63. https://doi.org/10.1016/j.tra.2016.10.013 doi: 10.1016/j.tra.2016.10.013
    [3] G. N. Bifulco, L. Pariota, F. Simonelli, R. Di Pace, Development and testing of a fully adaptive cruise control system, Transp. Res. C Emerg. Tech., 29 (2013), 156–170. https://doi.org/10.1016/j.trc.2011.07.001 doi: 10.1016/j.trc.2011.07.001
    [4] J. Rios-Torres, A. A. Malikopoulos, A survey on the coordination of connected and automated vehicles at intersections and merging at highway on-ramps, IEEE Trans. Intell. Transp. Syst., 18 (2016), 1066–1077. https://doi.org/10.1109/TITS.2016.2600504 doi: 10.1109/TITS.2016.2600504
    [5] D. Milakis, B. Van Arem, B. Van Wee, Policy and society related implications of automated driving: A review of literature and directions for future research, J. Intell. Transp. Syst., 21 (2017), 324–348. https://doi.org/10.1080/15472450.2017.1291351 doi: 10.1080/15472450.2017.1291351
    [6] K. C. Dey, L. Yan, X. Wang, Y. Wang, H. Shen, M. Chowdhury, et al., A review of communication, driver characteristics, and controls aspects of cooperative adaptive cruise control (CACC), IEEE Trans. Intell. Transp. Syst., 17 (2015), 491–509. https://doi.org/10.1109/TITS.2015.2483063 doi: 10.1109/TITS.2015.2483063
    [7] Z. Wang, G. Wu, M. J. Barth, A review on cooperative adaptive cruise control (CACC) systems: Architectures, controls, and applications, in 2018 21st International Conference on Intelligent Transportation Systems (ITSC), IEEE, (2018), 2884–2891. https://doi.org/10.1109/ITSC.2018.8569947
    [8] A. Kesting, M. Treiber, M. Schönhof, D. Helbing, Adaptive cruise control design for active congestion avoidance, Transp. Res. C Emerg. Tech., 16 (2008), 668–683. https://doi.org/10.1016/j.trc.2007.12.004 doi: 10.1016/j.trc.2007.12.004
    [9] D. Ngoduy, Analytical studies on the instabilities of heterogeneous intelligent traffic flow, Commun. Nonlinear Sci. Numer. Simul., 18 (2013), 2699–2706. https://doi.org/10.1016/j.cnsns.2013.02.018 doi: 10.1016/j.cnsns.2013.02.018
    [10] J. A. Ward, Heterogeneity, Lane-changing and Instability in Traffic: A Mathematical Approach, Ph.D thesis, University of Bristol Bristol, 2009.
    [11] I. A. Ntousakis, I. K. Nikolos, M. Papageorgiou, On microscopic modelling of adaptive cruise control systems, Transp. Res. Procedia, 6 (2015), 111–127. https://doi.org/10.1016/j.trpro.2015.03.010 doi: 10.1016/j.trpro.2015.03.010
    [12] D. Chen, S. Ahn, M. Chitturi, D. A. Noyce, Towards vehicle automation: Roadway capacity formulation for traffic mixed with regular and automated vehicles, Transp. Res. B, 100 (2017), 196–221. https://doi.org/10.1016/j.trb.2017.01.017 doi: 10.1016/j.trb.2017.01.017
    [13] H. Liu, X. D. Kan, S. E. Shladover, X. Y. Lu, R. E. Ferlis, Modeling impacts of cooperative adaptive cruise control on mixed traffic flow in multi-lane freeway facilities, Transp. Res. C Emerg. Tech., 95 (2018), 261–279. https://doi.org/10.1016/j.trc.2018.07.027 doi: 10.1016/j.trc.2018.07.027
    [14] D. F. Xie, X. M. Zhao, Z. He, Heterogeneous traffic mixing regular and connected vehicles: Modeling and stabilization, IEEE Trans. Intell. Transp. Syst., 20 (2018), 2060–2071. https://doi.org/10.1109/TITS.2018.2857465 doi: 10.1109/TITS.2018.2857465
    [15] H. Wang, Y. Qin, W. Wang, J. Chen, Stability of CACC-manual heterogeneous vehicular flow with partial CACC performance degrading, Transp. B Transp. Dyn., 7 (2019), 788–813. https://doi.org/10.1080/21680566.2018.1517058 doi: 10.1080/21680566.2018.1517058
    [16] Z. Yao, R. Hu, Y. Wang, Y. Jiang, B. Ran, Y. Chen, Stability analysis and the fundamental diagram for mixed connected automated and human-driven vehicles, Phys. A Stat. Mech. Its Appl., 533 (2019), 121931. https://doi.org/10.1016/j.physa.2019.121931 doi: 10.1016/j.physa.2019.121931
    [17] Z. Yao, R. Hu, Y. Jiang, T. Xu, Stability and safety evaluation of mixed traffic flow with connected automated vehicles on expressways, J. Saf. Res., 75 (2020), 262–274. https://doi.org/10.1016/j.jsr.2020.09.012 doi: 10.1016/j.jsr.2020.09.012
    [18] M. Shang, R. E. Stern, Impacts of commercially available adaptive cruise control vehicles on highway stability and throughput, Transp. Res. C Emerg. Tech., 122 (2021), 102897. https://doi.org/10.1016/j.trc.2020.102897 doi: 10.1016/j.trc.2020.102897
    [19] Z. Yao, T. Xu, Y. Jiang, R. Hu, Linear stability analysis of heterogeneous traffic flow considering degradations of connected automated vehicles and reaction time, Phys. A Stat. Mech. Its Appl., 561 (2021), 125218. https://doi.org/10.1016/j.physa.2020.125218 doi: 10.1016/j.physa.2020.125218
    [20] R. Luo, Q. Gu, T. Xu, H. Hao, Z. Yao, Analysis of linear internal stability for mixed traffic flow of connected and automated vehicles considering multiple influencing factors, Phys. A Stat. Mech. Its Appl., 597 (2022), 127211. https://doi.org/10.1016/j.physa.2022.127211 doi: 10.1016/j.physa.2022.127211
    [21] Y. C. Hung, K. Zhang, Impact of cooperative adaptive cruise control on traffic stability, Trans. Res. Rec., 2022 (2022). https://doi.org/10.1177/03611981221094822 doi: 10.1177/03611981221094822
    [22] D. Liu, B. Besselink, S. Baldi, W. Yu, H. L. Trentelman, Output-feedback design of longitudinal platooning with adaptive disturbance decoupling, IEEE Control Syst. Lett., 6 (2022), 3104–3109. https://doi.org/10.1109/LCSYS.2022.3181002 doi: 10.1109/LCSYS.2022.3181002
    [23] D. Liu, B. Besselink, S. Baldi, W. Yu, H. L. Trentelman, On structural and safety properties of head-to-tail string stability in mixed platoons, IEEE Trans. Intell. Transp. Syst., 2022 (2022), 1–13. https://doi.org/10.1109/TITS.2022.3151929 doi: 10.1109/TITS.2022.3151929
    [24] Z. Yao, Q. Gu, Y. Jiang, B. Ran, Fundamental diagram and stability of mixed traffic flow considering platoon size and intensity of connected automated vehicles, Phys. A Stat. Mech. Its Appl., 604 (2022), 127857. https://doi.org/10.1016/j.physa.2022.127857 doi: 10.1016/j.physa.2022.127857
    [25] FHWA, The next generation simulation (NGSIM), 2008. Available from: http://www.ngsim.fhwa.dot.gov/
    [26] V. Punzo, M. T. Borzacchiello, B. Ciuffo, On the assessment of vehicle trajectory data accuracy and application to the next generation simulation (NGSIM) program data, Transp. Res. C Emerg. Tech., 19 (2011), 1243–1262. https://doi.org/10.1016/j.trc.2010.12.007 doi: 10.1016/j.trc.2010.12.007
    [27] M. Montanino, V. Punzo, Reconstructed NGSIM I80-1. COST ACTION TU0903 - MULTITUDE, 2013. Available from: http://www.multitude-project.eu/exchange/101.html
    [28] M. Montanino, V. Punzo, Trajectory data reconstruction and simulation-based validation against macroscopic traffic patterns, Transp. Res. B, 80 (2015), 82–106. https://doi.org/10.1016/j.trb.2015.06.010 doi: 10.1016/j.trb.2015.06.010
    [29] M. Saifuzzaman, Z. Zheng, Incorporating human-factors in car-following models: A review of recent developments and research needs, Transp. Res. C Emerg. Tech., 48 (2014), 379–403. https://doi.org/10.1016/j.trc.2014.09.008 doi: 10.1016/j.trc.2014.09.008
    [30] V. Milanés, S. E. Shladover, J. Spring, C. Nowakowski, H. Kawazoe, M. Nakamura, Cooperative adaptive cruise control in real traffic situations, IEEE Trans. Intell. Transp. Syst., 15 (2013), 296–305. https://doi.org/10.1109/TITS.2013.2278494 doi: 10.1109/TITS.2013.2278494
    [31] V. Milanés, S. E. Shladover, Modeling cooperative and autonomous adaptive cruise control dynamic responses using experimental data, Transp. Res. C Emerg. Tech., 48 (2014), 285–300. https://doi.org/10.1016/j.trc.2014.09.001 doi: 10.1016/j.trc.2014.09.001
    [32] C. Wu, A. Kreidieh, K. Parvate, E. Vinitsky, A. M. Bayen, Flow: Architecture and benchmarking for reinforcement learning in traffic control, preprint, arXiv: 1710.05465.
    [33] M. Zhu, X. Wang, Y. Wang, Human-like autonomous car-following model with deep reinforcement learning, Transp. Res. C Emerg. Tech., 97 (2018), 348–368. https://doi.org/10.1016/j.trc.2018.10.024 doi: 10.1016/j.trc.2018.10.024
    [34] M. Treiber, A. Hennecke, D. Helbing, Congested traffic states in empirical observations and microscopic simulations, Phys. Rev. E, 62 (2000), 1805–1824. https://doi.org/10.1103/PhysRevE.62.1805 doi: 10.1103/PhysRevE.62.1805
    [35] M. Mitchell, An Introduction to Genetic Algorithms, MIT Press, 1998.
    [36] A. Kesting, M. Treiber, Calibrating car-following models by using trajectory data: Methodological study, Transp. Res. Rec., 2088 (2008), 148–156. https://doi.org/10.3141/2088-16 doi: 10.3141/2088-16
    [37] M. Treiber, A. Kesting, D. Helbing, Delays, inaccuracies and anticipation in microscopic traffic models, Phys. A Stat. Mech. Its Appl., 360 (2006), 71–88. https://doi.org/10.1016/j.physa.2005.05.001 doi: 10.1016/j.physa.2005.05.001
    [38] A. Kesting, M. Treiber, D. Helbing, Enhanced intelligent driver model to access the impact of driving strategies on traffic capacity, Philos. Trans. R. Soc. A, 368 (2010), 4585–4605. https://doi.org/10.1098/rsta.2010.0084 doi: 10.1098/rsta.2010.0084
    [39] M. Saifuzzaman, Z. Zheng, M. M. Haque, S. Washington, Revisiting the task–capability interface model for incorporating human factors into car-following models, Transp. Res. B, 82 (2015), 1–19. https://doi.org/10.1016/j.trb.2015.09.011 doi: 10.1016/j.trb.2015.09.011
    [40] S. E. Shladover, D. Su, X. Y. Lu, Impacts of cooperative adaptive cruise control on freeway traffic flow, Transp. Res. Rec., 2324 (2012), 63–70. https://doi.org/10.3141/2324-08 doi: 10.3141/2324-08
    [41] R. E. Wilson, J. A. Ward, Car-following models: Fifty years of linear stability analysis—A mathematical perspective, Transp. Plan. Technol., 34 (2011), 3–18. https://doi.org/10.1080/03081060.2011.530826 doi: 10.1080/03081060.2011.530826
    [42] M. Treiber, A. Kesting, Traffic flow dynamics, in Traffic Flow Dynamics: Data, Models and Simulation, Springer-Verlag, Berlin Heidelberg, 2013,983–1000.
    [43] X. Zhang, D. F. Jarrett, Stability analysis of the classical car-following model, Transp. Res. Part B Methodol., 31 (1997), 441–462. https://doi.org/10.1016/S0191-2615(97)00006-4 doi: 10.1016/S0191-2615(97)00006-4
    [44] G. Orosz, R. E. Wilson, G. Stépán, Traffic jams: dynamics and control, Phil. Trans. R. Soc. A, 368 (2010), 4455–4479. https://doi.org/10.1098/rsta.2010.0205 doi: 10.1098/rsta.2010.0205
    [45] P. Y. Li, A. Shrivastava, Traffic flow stability induced by constant time headway policy for adaptive cruise control vehicles, Transp. Res. C Emerg. Tech., 10 (2002), 275–301. https://doi.org/10.1016/S0968-090X(02)00004-9 doi: 10.1016/S0968-090X(02)00004-9
    [46] A. R. Kreidieh, C. Wu, A. M. Bayen, Dissipating stop-and-go waves in closed and open networks via deep reinforcement learning, in 2018 21st International Conference on Intelligent Transportation Systems (ITSC), IEEE, (2018), 1475–1480. https://doi.org/10.1109/ITSC.2018.8569485
  • Reader Comments
  • © 2023 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
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

Metrics

Article views(2040) PDF downloads(194) Cited by(11)

Article outline

Figures and Tables

Figures(6)  /  Tables(2)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog