Cooperative Control of Highway On-Ramp with Connected and Automated Vehicles as Platoons Based on Improved Variable Time Headway
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 148, Issue 7
Abstract
This work investigated the cooperative control of a highway on-ramp under a connected and automated vehicles (CAVs) environment based on improved variable time headway (IVTH). A mainline section with a connected on-ramp and off-ramp of an intelligent highway were used as research objects. An IVTH model was developed and its stability was proved. The traffic flow model of the section was established and then verified in experiments. A cooperative control strategy of highway on-off-ramps is proposed. The cooperative merging control model (CMCM) based on IVTH (CMCM-IVTH) was constructed in which the influence of off-ramp separation is considered. The model predictive control method based on particle swarm optimization is used to obtain the acceleration and deceleration of platoon leaders with CMCM-IVTH and the time headway of the following vehicles with the traffic flow model based on IVTH. The control effects were determined via simulation experiments. The results indicate that the acceleration and deceleration times of vehicles, fuel consumption, and collision possibility decreased significantly using the proposed method. Under a 20% diverging rate, the maximum number of slow-moving vehicles was reduced by as much as 75.0% and 33.3%, total delay time was reduced by as much as 72.9% and 18.9%, the average traveling velocity was increased by as much as 21.9% and 2.1%, compared with the no-optimization-control method and a method with only cooperative merging control, respectively. The operating efficiency and safety level can be enhanced.
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Data Availability Statement
All data, models, and code generated or used during the study appear in the published article.
Acknowledgments
The work described in this paper was supported by the National Natural Science Foundation of China (50478088), and the Science and Technology Project of Hebei Education Department, China (ZD2021028). The authors gratefully acknowledge the editor’s comments and the referees of the paper who helped to clarify and improve the presentation.
References
Berktas, E. S., and S. Tanyel. 2020. “Effect of autonomous vehicles on performance of signalized intersections.” J. Transp. Eng. Part A Syst. 146 (2): 04019061. https://doi.org/10.1061/JTEPBS.0000297.
Chen, R., T. Zhang, and M. W. Levin. 2020. “Effects of variable speed limit on energy consumption with autonomous vehicles on urban roads using modified cell-transmission model.” J. Transp. Eng. Part A Syst. 146 (7): 04020049. https://doi.org/10.1061/JTEPBS.0000379.
Dong, C., H. Wang, Y. Li, W. Wang, and Z. Zhang. 2019. “Route control strategies for autonomous vehicles exiting to off-ramps.” IEEE Trans. Intell. Transp. Syst. 99 (Sep): 1–13. https://doi.org/10.1109/TITS.2019.2925319.
Hu, X., and J. Sun. 2019. “Trajectory optimization of connected and autonomous vehicles at a multilane freeway merging area.” Transp. Res. Part C 101 (2): 111–125. https://doi.org/10.1016/j.trc.2019.02.016.
Jing, S., F. Hui, X. Zhao, J. Rios-Torres, and A. J. Khattak. 2019. “Cooperative game approach to optimal merging sequence and on-ramp merging control of connected and automated vehicles.” IEEE Trans. Intell. Transp. Syst. 20 (11): 1–11. https://doi.org/10.1109/TITS.2019.2925871.
Khondaker, B., and L. Kattan. 2015. “Variable speed limit: A microscopic analysis in a connected vehicle environment.” Transp. Res. Part C 58 (Mar): 146–159. https://doi.org/10.1016/j.trc.2015.07.014.
Letter, C., and L. Elefteriadou. 2017. “Efficient control of fully automated connected vehicles at freeway merge segments.” Transp. Res. Part C 80 (Mar): 190–205. https://doi.org/10.1016/j.trc.2017.04.015.
Luo, L.-H., Y.-E. Ge, J.-H. Chen, and F.-W. Zhang. 2016. “Real-time routing control design for traffic networks with multi-route choices.” J. Central South Univ. 23 (7): 1807–1816. https://doi.org/10.1007/s11771-016-3234-6.
Pang, M. B., and M. Q. Yang. 2020. “Coordinated control of urban expressway integrating adjacent signalized intersections based on pinning synchronization of complex networks.” Transp. Res. Part C 116 (2): 102645. https://doi.org/10.1016/j.trc.2020.102645.
Roncoli, C., M. Papageorgiou, and I. Papamichail. 2015. “Traffic flow optimisation in presence of vehicle automation and communication systems—Part II: Optimal control for multi-lane motorways.” Transp. Res. Part C 57 (8): 260275. https://doi.org/10.1016/j.trc.2015.05.011.
Seraj, M., J. Li, and Z. Qiu. 2018. “Modeling microscopic car following strategy of mixed traffic to identify optimal platoon configurations for multiobjective decision-making.” J. Adv. Transp. 5 (Sep): 7835010. https://doi.org/10.1155/2018/7835010.
Wang, Q., X. T. Yang, Z. Huang, and Y. Yuan. 2020. “Multi-vehicle trajectory design during cooperative adaptive cruise control platoon formation.” Transp. Res. Rec. 2674 (4): 30–41. https://doi.org/10.1177/0361198120913290.
Wiedemann, R. 1974. Simulation des strassenverkehrsflusses. Karlsruhe, Germany: Univ. Karlsruhe.
Xie, Y., H. Zhang, N. H. Gartner, and T. Arsava. 2017. “Collaborative merging strategy for freeway ramp operations in a connected and autonomous vehicles environment.” J. Intell. Transp. Syst. 21 (2): 136–147. https://doi.org/10.1080/15472450.2016.1248288.
Xu, L., J. Lu, B. Ran, F. Yang, and J. Zhang. 2019. “Cooperative merging strategy for connected vehicles at highway on-ramps.” J. Transp. Eng. Part A Syst. 145 (6): 04019022. https://doi.org/10.1061/JTEPBS.0000243.
Yang, L., J. Mao, K. Liu, J. Du, and J. Liu. 2020. “An adaptive cruise control method based on improved variable time headway strategy and particle swarm optimization algorithm.” IEEE Access 7 (Apr): 1–12. https://doi.org/10.1109/ACCESS.2020.3023179.
Yu, M., and W. D. Fan. 2019. “Optimal variable speed limit control in connected autonomous vehicle environment for relieving freeway congestion.” J. Transp. Eng. Part A Syst. 145 (4): 04019007. https://doi.org/10.1061/JTEPBS.0000227.
Zhang, T., J. Zhang, M. Lu, W. Lin, and Z. Cong. 2018. “The collaborative control between CAVs under highway entrance ramp and exit ramp environment.” In Proc., 2018 3rd Int. Conf. on Smart City and Systems Engineering (ICSCSE), 547–551. New York: IEEE. https://doi.org/10.1109/ICSCSE.2018.00117.
Zhou, Y., E. Chung, A. Bhaskar, and M. E. Cholette. 2019. “A state-constrained optimal control based trajectory planning strategy for cooperative freeway mainline facilitating and on-ramp merging maneuvers under congested traffic.” Transp. Res. Part C 109 (3): 321–342. https://doi.org/10.1016/j.trc.2019.10.017.
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© 2022 American Society of Civil Engineers.
History
Received: Jun 29, 2021
Accepted: Feb 7, 2022
Published online: Apr 18, 2022
Published in print: Jul 1, 2022
Discussion open until: Sep 18, 2022
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