AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (4.5 MB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Open Access

Theoretical Analysis of Cooperative Driving at Idealized Unsignalized Intersections

Department of Civil Engineering, Tsinghua University, Beijing 100084, China
Department of Automation, Tsinghua University, Beijing 100084, China
Shenzhen Urban Transport Planning Center Co., Ltd., Shenzhen 518000, China
Show Author Information

Abstract

Cooperative driving is widely viewed as a promising method to better utilize limited road resources and alleviate traffic congestion. In recent years, several cooperative driving approaches for idealized traffic scenarios (i.e., uniform vehicle arrivals, lengths, and speeds) have been proposed. However, theoretical analyses and comparisons of these approaches are lacking. In this study, we propose a unified group-by-group zipper-style movement model to describe different approaches synthetically and evaluate their performance. We derive the maximum throughput for cooperative driving plans of idealized unsignalized intersections and discuss how to minimize the delay of vehicles. The obtained conclusions shed light on future cooperative driving studies.

References

[1]
L. Li, D. Wen, and D. Y. Yao, A survey of traffic control with vehicular communications, IEEE Trans. Intell. Transport. Syst., vol. 15, no. 1, pp. 425432, 2014.
[2]
Q. Guo, L. Li, and X. Ban, Urban traffic signal control with connected and automated vehicles: A survey, Transp. Res. Part C: Emerg. Technol., vol. 101, pp. 313334, 2019.
[3]
J. Zhang, C. Chang, H. Pei, X. Peng, Y. Guo, R. Lian, Z. Chen, and L. Li, CAVSim: A microscope traffic simulator for connected and automated vehicles environment, in Proc. 2022 IEEE 25th Int. Conf. Intelligent Transportation Systems (ITSC), Macau, China, 2022, pp. 37193724.
[4]
C. Chang, K. Zhang, J. Zhang, S. Li, and L. Li, Driving safety monitoring and warning for connected and automated vehicles via edge computing, in Proc. of the 2022 IEEE 25th Int. Conf. Intelligent Transportation Systems (ITSC), Macau, China, 2022, pp. 39403947.
[5]
S. Chen, J. Hu, Y. Shi, L. Zhao, and W. Li, A vision of C-V2X: Technologies, field testing, and challenges with Chinese development, IEEE Internet of Things J., vol. 7, no. 5, pp. 38723881, 2020.
[6]
H. Zhou, W. Xu, J. Chen, and W. Wang, Evolutionary V2X technologies toward the internet of vehicles: Challenges and opportunities, in Proc. IEEE, vol. 108, no. 2, pp. 308323, 2020.
[7]
J. Zhang, C. Chang, X. Zeng, and L. Li, Multi-agent DRL-based lane change with right-of-way collaboration awareness, IEEE Trans. Intell. Transport. Syst., vol. 24, no. 1, pp. 854869, 2023.
[8]
L. Li and F. Y. Wang, Cooperative driving at blind crossings using intervehicle communication, IEEE Trans. Veh. Technol., vol. 55, no. 6, pp. 17121724, 2006.
[9]
K. Dresner and P. Stone, A multiagent approach to autonomous intersection management, J. Artif. Intell. Res., vol. 31, no. 1, pp. 591656, 2008.
[10]
Y. Meng, L. Li, F. Y. Wang, K. Li, and Z. Li, Analysis of cooperative driving strategies for nonsignalized intersections, IEEE Trans. Veh. Technol., vol. 67, no. 4, pp. 29002911, 2018.
[11]
H. Pei, J. Zhang, Y. Zhang, X. Pei, S. Feng, and L. Li, Fault-tolerant cooperative driving at signal-free intersections, IEEE Trans. Intell. Veh., vol. 8, no. 1, pp. 121134, 2023.
[12]
H. Xu, Y. Zhang, L. Li, and W. Li, Cooperative driving at unsignalized intersections using tree search, IEEE Trans. Intell. Transport. Syst., vol. 21, no. 11, pp. 45634571, 2020.
[13]
H. Xu, C. G. Cassandras, L. Li, and Y. Zhang, Comparison of cooperative driving strategies for CAVs at signal-free intersections, IEEE Trans. Intell. Transport. Syst., vol. 23, no. 7, pp. 76147627, 2022.
[14]
J. Zhang, H. Pei, X. Ban, and L. Li, Analysis of cooperative driving strategies at road network level with macroscopic fundamental diagram, Transp. Res. Part C: Emerg. Technol., vol. 135, p. 103503, 2022.
[15]
S. Ilgin Guler, M. Menendez, and L. Meier, Using connected vehicle technology to improve the efficiency of intersections, Transp. Res. Part C: Emerg. Technol., vol. 46, pp. 121131, 2014.
[16]
B. Xu, S. E. Li, Y. Bian, S. Li, X. J. Ban, J. Wang, and K. Li, Distributed conflict-free cooperation for multiple connected vehicles at unsignalized intersections, Transp. Res. Part C: Emerg. Technol., vol. 93, pp. 322334, 2018.
[17]
H. Xu, Y. Zhang, C. G. Cassandras, L. Li, and S. Feng, A bi-level cooperative driving strategy allowing Lane changes, Transp. Res. Part C: Emerg. Technol., vol. 120, p. 102773, 2020.
[18]
J. Zhang, Z. Li, L. Li, Y. Li, and H. Dong, A bi-level cooperative operation approach for AGV based automated valet parking, Transp. Res. Part C: Emerg. Technol., vol. 128, p. 103140, 2021.
[19]
L. Chen and C. Englund, Cooperative intersection management: A survey, IEEE Trans. Intell. Transport. Syst., vol. 17, no. 2, pp. 570586, 2016.
[20]
Z. He, L. Zheng, L. Lu, and W. Guan, Erasing lane changes from roads: A design of future road intersections, IEEE Trans. Intell. Veh., vol. 3, no. 2, pp. 173184, 2018.
[21]
Z. Chen and X. Li, Designing corridor systems with modular autonomous vehicles enabling station-wise docking: Discrete modeling method, Transp. Res. Part E: Logist. Transp. Rev., vol. 152, p. 102388, 2021.
[22]
X. Lin, M. Li, Z. J. M. Shen, Y. Yin, and F. He, Rhythmic control of automated traffic-part II: Grid network rhythm and online routing, Transp. Sci., vol. 55, no. 5, pp. 9881009, 2021.
[23]
X. Shi and X. Li, Operations design of modular vehicles on an oversaturated corridor with first-in, first-out passenger queueing, Transp. Sci., vol. 55, no. 5, pp. 11871205, 2021.
[24]
Q. He, K. L. Head, and J. Ding, PAMSCOD: Platoon-based arterial multi-modal signal control with online data, Procedia Soc. and Behav. Sci., vol. 17, pp. 462489, 2011.
[25]
X. F. Xie, S. F. Smith, L. Lu, and G. J. Barlow, Schedule-driven intersection control, Transp. Res. Part C: Emerg. Technol., vol. 24, pp. 168189, 2012.
[26]
H. Liu, X. Y. Lu, and S. E. Shladover, Traffic signal control by leveraging Cooperative Adaptive Cruise Control (CACC) vehicle platooning capabilities, Transp. Res. Part C: Emerg. Technol., vol. 104, pp. 390407, 2019.
[27]
H. Xu, S. Feng, Y. Zhang, and L. Li, A grouping-based cooperative driving strategy for CAVs merging problems, IEEE Trans. Veh. Technol., vol. 68, no. 6, pp. 61256136, 2019.
[28]
G. Lu, Z. Shen, X. Liu, M. Nie, and Z. Xiong, Are autonomous vehicles better off without signals at intersections? A comparative computational study, Transp. Res. Part B: Methodol., vol. 155, pp. 2646, 2022.
[29]
Q. Ge, Q. Sun, Z. Wang, S. E. Li, Z. Gu, S. Zheng, and L. Liao, Real-time coordination of connected vehicles at intersections using graphical mixed integer optimization, IET Intell. Trans. Syst., vol. 15, no. 6, pp. 795807, 2021.
[30]
M. W. Levin, S. D. Boyles, and R. Patel, Paradoxes of reservation-based intersection controls in traffic networks, Transp. Res. Part A: Policy Pract., vol. 90, pp. 1425, 2016.
[31]
M. W. Levin and D. Rey, Conflict-point formulation of intersection control for autonomous vehicles, Transp. Res. Part C: Emerg. Technol., vol. 85, pp. 528547, 2017.
[32]
Y. Wu, H. Chen, and F. Zhu, DCL-AIM: Decentralized coordination learning of autonomous intersection management for connected and automated vehicles, Transp. Res. Part C: Emerg. Technol., vol. 103, pp. 246260, 2019.
[33]
E. Lukose, M. W. Levin, and S. D. Boyles, Incorporating insights from signal optimization into reservation-based intersection controls, J. Intell. Transp. Syst., vol. 23, no. 3, pp. 250264, 2019.
[34]
A. Stevanovic and N. Mitrovic, Combined alternate-direction lane assignment and reservation-based intersection control, in Proc. 2018 21st Int. Conf. Intelligent Transportation Systems (ITSC), Maui, HI, USA, 2018, pp. 1419.
[35]
R. Tachet, P. Santi, S. Sobolevsky, L. I. Reyes-Castro, E. Frazzoli, D. Helbing, and C. Ratti, Revisiting street intersections using slot-based systems, PLoS ONE, vol. 11, no. 3, p. e0149607, 2016.
[36]
S. Li, K. Shu, Y. Zhou, D. Cao, and B. Ran, Cooperative critical turning point-based decision-making and planning for CAVH intersection management system, IEEE Trans. Intell. Transport. Syst., vol. 23, no. 8, pp. 1106211072, 2022.
[37]
L. Chai, B. Cai, W. Shangguan, J. Wang, and H. Wang, Connected and autonomous vehicles coordinating approach at intersection based on space-time slot, Transportmetrica A: Transport Science, vol. 14, no. 10, pp. 929951, 2018.
[38]
X. Chen, M. Li, X. Lin, Y. Yin, and F. He, Rhythmic control of automated traffic-part I: Concept and properties at isolated intersections, Transp. Sci., vol. 55, no. 5, pp. 969987, 2021.
[39]
W. Zhao, D. Ngoduy, S. Shepherd, R. Liu, and M. Papageorgiou, A platoon based cooperative eco-driving model for mixed automated and human-driven vehicles at a signalised intersection, Transp. Res. Part C: Emerg. Technol., vol. 95, pp. 802821, 2018.
[40]
C. Chen, J. Wang, Q. Xu, J. Wang, and K. Li, Mixed platoon control of automated and human-driven vehicles at a signalized intersection: Dynamical analysis and optimal control, Transp. Res. Part C: Emerg. Technol., vol. 127, p. 103138, 2021.
[41]
Y. Yin, Robust optimal traffic signal timing, Transp. Res. Part B: Methodol., vol. 42, no. 10, pp. 911924, 2008.
[42]
Z. Li, Q. Wu, H. Yu, C. Chen, G. Zhang, Z. Z. Tian, and P. D. Prevedouros, Temporal-spatial dimension extension-based intersection control formulation for connected and autonomous vehicle systems, Transp. Res. Part C: Emerg. Technol., vol. 104, pp. 234248, 2019.
[43]
C. Yu, W. Ma, and X. Yang, A time-slot based signal scheme model for fixed-time control at isolated intersections, Transp. Res. Part B: Methodol., vol. 140, pp. 176192, 2020.
[44]
S. E. Shladover, D. Su, and X. Y. Lu, Impacts of cooperative adaptive cruise control on freeway traffic flow, Transp. Res. Rec., vol. 2324, no. 1, pp. 6370, 2012.
[45]
H. Yu, R. Jiang, Z. He, Z. Zheng, L. Li, R. Liu, and X. Chen, Automated vehicle-involved traffic flow studies: A survey of assumptions, models, speculations, and perspectives, Transp. Res. Part C: Emerg. Technol., vol. 127, p. 103101, 2021.
[46]
V. Milanés, S. E. Shladover, J. Spring, C. Nowakowski, H. Kawazoe, and M. Nakamura, Cooperative adaptive cruise control in real traffic situations, IEEE Trans. Intell. Transport. Syst., vol. 15, no. 1, pp. 296305, 2014.
[47]
A. Uno, T. Sakaguchi, and S. Tsugawa, A merging control algorithm based on inter-vehicle communication, in Proc. 199 IEEE/IEEJ/JSAI Int. Conf. Intelligent Transportation Systems, Tokyo, Japan, 1999, pp. 783787.
[48]
T. Sakaguchi, A. Uno, S. Kato, and S. Tsugawa, Cooperative driving of automated vehicles with inter-vehicle communications, in Proc. IEEE Intelligent Vehicles Symp. 2000, Dearborn, MI, USA, 2000, pp. 516521.
[49]
L. Zhang and D. Levinson, Balancing efficiency and equity of ramp meters, J. Transp. Eng., vol. 131, no. 6, pp. 477481, 2005.
[50]
L. Zhang and D. Levinson, Ramp metering and freeway bottleneck capacity, Transp. Res. Part A: Policy Pract., vol. 44, no. 4, pp. 218235, 2010.
[51]
Q. Tian, H. J. Huang, H. Yang, and Z. Gao, Efficiency and equity of ramp control and capacity allocation mechanisms in a freeway corridor, Procedia Soc. Behav. Sci., vol. 17, pp. 509531, 2011.
[52]
X. Liang, S. I. Guler, and V. V. Gayah, An equitable traffic signal control scheme at isolated signalized intersections using connected vehicle technology, Transp. Res. Part C: Emerg. Technol., vol. 110, pp. 8197, 2020.
[53]
H. Pei, S. Feng, Y. Zhang, and D. Yao, A cooperative driving strategy for merging at on-ramps based on dynamic programming, IEEE Trans. Veh. Technol., vol. 68, no. 12, pp. 1164611656, 2019.
[54]
J. Ding, H. Peng, Y. Zhang, and L. Li, Penetration effect of connected and automated vehicles on cooperative on-ramp merging, IET Intell. Transp. Syst., vol. 14, no. 1, pp. 5664, 2020.
[55]
S. Feng, Z. Song, Z. Li, Y. Zhang, and L. Li, Robust platoon control in mixed traffic flow based on tube model predictive control, IEEE Trans. Intell. Veh., vol. 6, no. 4, pp. 711722, 2021.
[56]
J. Ge, H. Xu, J. Zhang, Y. Zhang, D. Yao, and L. Li, Heterogeneous driver modeling and corner scenarios sampling for automated vehicles testing, J. Adv. Transp., vol. 2022, p. 8655514, 2022.
[57]
J. Zhang, S. Li, and L. Li, Coordinating CAV swarms at intersections with a deep learning model, IEEE Trans. Intell. Transport. Syst., .
Tsinghua Science and Technology
Pages 257-270
Cite this article:
Li S, Zhang J, Chen Z, et al. Theoretical Analysis of Cooperative Driving at Idealized Unsignalized Intersections. Tsinghua Science and Technology, 2024, 29(1): 257-270. https://doi.org/10.26599/TST.2022.9010069

415

Views

25

Downloads

2

Crossref

2

Web of Science

2

Scopus

0

CSCD

Altmetrics

Received: 08 September 2022
Revised: 09 November 2022
Accepted: 29 December 2022
Published: 21 August 2023
© The author(s) 2024.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).

Return