Hierarchical and Distributed Control Optimization for
Urban Network Traffic Signals

doi:10.16097/j.cnki.1009-6744.2023.04.012

Abstract

Abstract: The control structure of network-wide traffic signal control is of great significance to improve the efficiency of urban traffic systems. Considering both the control performance and computational efficiency, this paper proposes an efficient hierarchical network signal control strategy. At the upper level, the cycle length optimization is conducted by using the Webster method. The lower level addresses the green split optimization with the objective function of minimizing the total time spent, which is formulated as a model predictive control (MPC). To decompose the network into intersections while mainlining optimal performance, a Benders decomposition method is introduced to decompose the problem into a Primal problem and a Master problem. The Primal problem solves the isolated intersection optimization independently while the Master problem tackles the flow interaction between adjacent intersections. For the solution approach, a Benders decomposition-based two-layer distributed signal control optimization algorithm is designed. To verify the performance of the proposed hierarchical control method, comparative experiments are set up for the two control levels on two test networks. The results show that the optimal solutions derived from the Benders Decomposition-based distributed MPC method are close to the global optimal solutions derived from the centralized control method. The errors of the network total time spent between the two methods are less than 3.26% . While maintaining the overall performance, the distributed MPC method can greatly improve computational efficiency; Compared with the centralized control method, the calculation time can be reduced up to 42.24% . In addition, the proposed distributed method outperforms the fixed-time control method. The reductions in the total travel time spent under different traffic conditions are about 9.40% to 20.57%. Moreover, by introducing the cycle optimization method at the upper level, the hierarchical distributed control method can further improve overall control performance.

Key words: traffic engineering, hierarchical and distributed control, Benders decomposition, network-wide traffic signal control, model predictive control

摘要： 合理的路网信号控制结构对提高城市交通系统运行效率具有重要意义。本文综合考虑控制性能和计算效率，提出路网交通信号分层分布式控制策略。在控制结构的上层，引入Webster方法实时更新周期时长；在下层，采用模型预测控制方法对交叉口信号控制问题进行建模，以最小化路网总行程时间为目标，优化信号绿信比，并利用Benders分解思路将原问题分解为独立求解单个交叉口信号配时方案的Primal问题和协调优化相邻交叉口间交通流交互作用的Master问题，提出一种基于Benders分解的双层分布式信号协调控制优化算法。通过两个实际路网算例，验证分层分布式控制方法的有效性，并针对上下层的控制方法设置对比实验。结果表明：基于Benders分解的分布式模型预测控制方法能求得接近集中式控制的整体优化解(路网总行程时间差在3.26%以下)，在兼顾控制性能的同时大幅提升优化求解的计算效率，相较于集中式控制，计算时间减少的幅度可达42.24%；在不同实验场景下，分布式控制方法的控制效果均优于定时控制方法，路网总行程时间约减少9.40%~20.57%。此外，在上层加入周期优化层后，分层控制方法能根据实时交通状态调整周期时长，进一步提高交通系统的运行效率。

CLC Number:

U491

HUANG Wei, HU Jing, HUANG Guo-yu, ZHOU Shao-rui. Hierarchical and Distributed Control Optimization for Urban Network Traffic Signals[J]. Journal of Transportation Systems Engineering and Information Technology, 2023, 23(4): 111-123.

黄玮, 胡晶, 黄国煜, 周少锐. 城市路网交通信号分层分布式控制优化方法[J]. 交通运输系统工程与信息, 2023, 23(4): 111-123.

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URL: http://www.tseit.org.cn/EN/10.16097/j.cnki.1009-6744.2023.04.012

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References

[1] 路婷, 贝晓旭, 刘桂云. 基于交叉口重要度深度搜索的区域信号协调控制方法[J]. 交通运输系统工程与信息, 2018, 18(2): 80-86. [LU T, BEI X X, LIU G Y. An area-wide traffic signal coordination method based on the deep first search of intersection's importance[J]. Journal of Transportation Systems Engineering and Information Technology, 2018, 18(2): 80-86.]

[2] HUNT P B, ROBERTSON D I, BRETHERTON R D, et al. The SCOOT on-line traffic signal optimisation technique[J]. Traffic Engineering & Control, 1982, 23(4): 190-192.

[3] LOWRIE P. The sydney coordinated adaptive traffic system: Principles, methodology, algorithms[C]. London, United Kingdom: IEEE, 1982.

[4] ABOUDOLAS K, PAPAGEORGIOU M, KOUVELAS A, et al. A rolling-horizon quadratic-programming approach to the signal control problem in large-scale congested urban road networks[J]. Transportation Research Part C: Emerging Technologies, 2010, 18(5): 680-694.

[5] LIN S, DE SCHUTTER B, XI Y, et al. Model predictive control for urban traffic networks via MILP[C]. United States: IEEE, 2010.

[6] YE B L, WU W, GAO H, et al. Stochastic model predictive control for urban traffic networks[J]. Applied Sciences, 2017, 7(6): 588.

[7] 江竹, 林豪, 李树彬, 等. 城市快速路分层分布式优化控制方法研究[J]. 交通运输系统工程与信息, 2020, 20(2): 101-106. [JIANG Z, LIN H, LI S B, et al. Hierarchical and distributed optimal control research on urban freeway network[J]. Journal of Transportation Systems Engineering and Information Technology, 2020, 20(2): 101-106.]

[8] DE OLIVEIRA L B, CAMPONOGARA E. Multi-agent model predictive control of signaling split in urban traffic networks[J]. Transportation Research Part C: Emerging Technologies, 2010, 18(1): 120-139.

[9] TIMOTHEOU S, PANAYIOTOU C G, POLYCARPOU M M. Distributed traffic signal control using the cell transmission model via the alternating direction method of multipliers[J]. IEEE Transactions on Intelligent Transportation Systems, 2014, 16(2): 919-933.

[10] YE B L, WU W, LI L, et al. A hierarchical model predictive control approach for signal splits optimization in large-scale urban road networks[J]. IEEE Transactions on Intelligent Transportation Systems, 2016, 17(8): 2182- 2192.

[11] 裴华鑫, 杨敬轩, 胡坚明, 等. 大规模路网中分布式车辆群体协同决策方法[J]. 交通运输工程学报, 2022, 22(3): 174-183. [PEI H X, YANG J X, HU J M, et al. Distributed cooperative decision-making method for vehicle swarms in large-scale road networks[J]. Journal of Traffic and Transportation Engineering, 2022, 22(3): 174-183.]

[12] 江雨星, 牛惠民. 需求响应的集装箱班列时刻表优化及 Benders 分解算法[J]. 交通运输系统工程与信息, 2020, 20(5): 191-198. [JIANG Y X, NIU H M. Optimization of demand-response container train timetables and benders decomposition[J]. Journal of Transportation Systems Engineering and Information Technology, 2020, 20(5): 191-198.]

[13] NGUYEN S, DUPUIS C. An efficient method for computing traffic equilibria in networks with asymmetric transportation costs[J]. Transportation Science, 1984, 18 (2): 185-202.

[14] 李水友, 刘智勇. 城市交通感应控制综述[J]. 城市交通, 2006, 4(6): 64-69. [LI S Y, LIU Z Y. A general description of urban traffic inductive-loop signal control [J]. Urban Transport of China, 2006, 4(6): 64-69.]

[15] WEBSTER F V. Traffic signal settings[R]. London: Road Research Laboratory, 1958.

Hierarchical and Distributed Control Optimization for Urban Network Traffic Signals

城市路网交通信号分层分布式控制优化方法

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