Research review on cooperative decision-making for vehicle swarms in vehicle-infrastructure cooperative environment

被引:0
|
作者
Zhang Y. [1 ,2 ,3 ,4 ]
Pei H.-X. [1 ,2 ]
Yao D.-Y. [1 ,2 ,4 ]
机构
[1] School of Information Science and Technology, Tsinghua University, Beijing
[2] Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing
[3] Tsinghua-Berkeley Shenzhen Institute (TBSI), Guangdong, Shenzhen
[4] Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Jiangsu, Nanjing
关键词
centralized mechanism; cooperative decision-making; demonstration scenario; distributed mechanism; intelligent transportation; intelligent vehicle-infrastructure cooperative system; right of way assignment; vehicle swarm;
D O I
10.19818/j.cnki.1671-1637.2022.03.001
中图分类号
学科分类号
摘要
The research status of cooperative decision-making of vehicle swarms at home and abroad was analyzed from the aspects of mechanisms, methods, and typical application scenarios of cooperative decision-making for vehicle swarms in vehicle-infrastructure cooperative environments. Considering the different cooperative decision-making mechanisms of vehicle swarms, the research on two kinds of decision-making mechanisms, namely the centralized one and the distributed one, was systematically sorted out. Regarding the diversity of cooperative decision-making methods for vehicle swarms, the advantages and disadvantages of different decision-making methods were comparatively analyzed with the optimization-based and heuristics-based decision-making methods as the thread. As for the different application scenarios of cooperative decision-making for vehicle swarms, the theories and research on the cooperative decision-making for vehicle swarms were comprehensively analyzed in various application scenarios, such as ramps, intersections, road sections, and road networks, Concerning the progress of typical projects on the cooperative decision-making for vehicles at home and abroad, the tasks, construction, and implementation of representative projects on the cooperative decision-making for vehicle swarms in China, the United States, Japan, and Europe were sorted out, respectively. The future development trend of cooperative decision-making for vehicle swarms in vehicle-infrastructure cooperative environments was proposed from the three aspects of system structure, universal model, and demonstration scenarios. Research results show that the centralized cooperative decision-making mechanism for vehicle swarms can be employed to improve the vehicle traffic performance in local areas, whereas the distributed cooperative decision-making mechanism for vehicle swarms is conducive to promoting the global traffic operation. The optimization-based cooperative decision-making method for vehicle swarms can maximize the decision-making effect in specific scenarios, while feasible decision-making effects can be obtained by the heuristics-based cooperative decision-making method for vehicle swarms in most scenarios. Due to the different complexities of the cooperative decision-making problem for vehicle swarms in different scenarios, targeted modeling under a unified framework is required. The research results can provide a reference for the management and control of new hybrid traffic systems in vehicle-infrastructure cooperative environments. 6 tabs, 9 figs, 50 refs. © 2022 Chang'an University. All rights reserved.
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页码:1 / 18
页数:17
相关论文
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  • [1] ZHANG Yi, YAO Dan-ya, LI Li, Et al., Technologies and applications for intelligent vehicle-infrastructure cooperation systems, Journal of Transportation Systems Engineering and Information Technology, 21, 5, pp. 40-51, (2021)
  • [2] RIOS-TORRES J, MALIKOPOULOS A A., A survey on the coordination of connected and automated vehicles at intersections and merging at highway on-ramps, IEEE Transactions on Intelligent Transportation Systems, 18, 5, pp. 1066-1077, (2017)
  • [3] KACHROOP, LI Zhi-jun, Vehicle merging control design for an automated highway system [C] II IEEE, Proceedings of Conference on Intelligent Transportation Systems, pp. 224-229, (1997)
  • [4] AWAL T, KULIK L, RAMAMOHANRAO K., Optimal traffic-merging strategy for communication- and sensor-enabled vehicles, 16th International IEEE Conference on Intelligent Transportation Systems, pp. 1468-1474, (2013)
  • [5] MULLER E R, CARLSON R C, JUNIOR W K., Intersection control for automated vehicles with MI LP, IFAC-PapersOnLine, 49, 3, pp. 37-42, (2016)
  • [6] AHN H, DEL VECCHIO D., Safety verification and control for collision avoidance at road intersections, IEEE Transactions on Automatic Control, 63, 3, pp. 630-642, (2018)
  • [7] LI Li, WANG Fei-yue, Cooperative driving at blind crossings using intervehicle communication, IEEE Transactions on Vehicular Technology, 55, 6, pp. 1712-1724, (2006)
  • [8] ASHTIANI F, FAYAZI S A, VAHIDI A., Multi-intersection traffic management for autonomous vehicles via distributed mixed integer linear programming, 2018 Annual American Control Conference (ACC), pp. 6341-6346, (2018)
  • [9] CHALAKI B, MALIKOPOULOS A A., An optimal coordination framework for connected and automated vehicles in two interconnected intersections, 2019 IEEE Conference on Control Technology and Applications (CCTA), pp. 888-893, (2019)
  • [10] CHALAKI B, MALIKOPOULOS A A., Optimal control of connected and automated vehicles at multiple adjacent intersections, IEEE Transactions on Control Systems Technology, 30, 3, pp. 972-984, (2022)