[1] YAO Han-dong, CUI Jian-xun, LI Xiao-peng, et al. A trajectory smoothing method at signalized intersection based on individualized variable speed limits with location optimization[J]. Transportation Research Part D: Transport and Environment, 2018, 62: 456-473.
[2] AIISLAM S M A B, HAJBABAIE A. Distributed coordinated signal timing optimization in connected transportation networks[J]. Transportation Research Part C: Emerging Technologies, 2017, 80: 272-285.
[3] BEAK B, HEAD K L, FENG Yi-heng. Adaptive coordination based on connected vehicle technology[J]. Journal of the Transportation Research Board, 2017, 2619(1): 1-12.
[4] LITTLE J D C, KELSON M D, GARTNER N H. MAXBAND: a program for setting signals on arteries and triangular networks[J]. Journal of the Transportation Research Board, 1981, 795: 40-46.
[5] GARTNER N H, ASSMAN S F, LASAGA F, et al. A multi-band approach to arterial traffic signal optimization[J]. Transportation Research Part B: Methodological, 1991, 25(1): 55-74.
[6] 曲大义,万孟飞,王兹林,等.干线协调控制优化及其应用[J].交通运输工程学报,2016,16(5):112-121.
QU Da-yi, WAN Meng-fei, WANG Zi-lin, et al. Arterial coordination control optimization and application[J]. Journal of Traffic and Transportation Engineering, 2016, 16(5): 112-121.(in Chinese)
[7] YAN Hui-min, HE Fang, LIN Xi, et al. Network-level multiband signal coordination scheme based on vehicle trajectory data[J]. Transportation Research Part C: Emerging Technologies, 2019, 107: 266-286.
[8] 刘 芹,徐建闽.交通区域协调控制模型[J].交通运输工程学报,2012,12(3):108-112.
LIU Qin, XU Jian-min. Coordinated control model of regional traffic signals[J]. Journal of Traffic and Transportation Engineering, 2012, 12(3): 108-112.(in Chinese)
[9] LI P F, MIRCHANDANI P, ZHOU X S. Solving simultaneous route guidance and traffic signal optimization problem using space-phase-time hypernetwork[J]. Transportation Research Part B: Methodological, 2015, 81: 103-130.
[10] WADA K,USUI K,TAKIGAWA T, et al. An optimization modeling of coordinated traffic signal control based on the variational theory and its stochastic extension[J]. Transportation Research Part B: Methodological, 2018, 117: 907-925.
[11] WANG P R, LI P F, CHOWDHURY F R, et al. A mixed integer programming formulation and scalable solution algorithms for traffic control coordination across multiple intersections based on vehicle space-time trajectories[J]. Transportation Research Part B: Methodological, 2020, 134: 266-304.
[12] LEE S, WONG S C. Group-based approach to predictive delay model based on incremental queue accumulations for adaptive traffic control systems[J]. Transportation Research Part B: Methodological, 2017, 98: 1-20.
[13] 李 冰.基于随机交通需求预测的主动分布式信号控制研究[D].昆明:昆明理工大学,2019.
LI Bing. Research on proactive distributed signal control based on stochastic traffic demand prediction[D]. Kunming: Kunming University of Science and Technology, 2019.(in Chinese)
[14] GOKULAN B P, SRINIVASAN D. Distributed geometric fuzzy multiagent urban traffic signal control[J]. IEEE Transactions on Intelligent Transportation Systems, 2010, 11(3): 714-727.
[15] EL-TANTAWY S, ABDULHAI B, ABDELGAWAD H. Multiagent reinforcement learning for integrated network of adaptive traffic signal controllers(MARLIN-ATSC): methodology and large-scale application on downtown Toronto[J]. IEEE Transactions on Intelligent Transportation Systems, 2013, 14(3): 1140-1150.
[16] ZHU F, AZIZ H M A, QIAN X W, et al. A junction-tree based learning algorithm to optimize network wide traffic control: a coordinated multi-agent framework[J]. Transportation Research Part C: Emerging Technologies, 2015, 58: 487-501.
[17] CHU Tian-shu, WANG Jie, LARA C, et al. Multi-agent deep reinforcement learning for large-scale traffic signal control[J]. IEEE Transactions on Intelligent Transportation Systems, 2020, 21(3): 1086-1095.
[18] WANG Xing-min, YIN Ya-feng, FENG Yi-heng, et al. Learning the max pressure control for urban traffic networks considering the phase switching loss[J]. Transportation Research Part C: Emerging Technologies, 2022, 140: 103670.
[19] 杨文臣,张 轮,ZHU Feng.多智能体强化学习在城市交通网络信号控制方法中的应用综述[J].计算机应用研究,2018,35(6):1613-1618.
YANG Wen-chen, ZHANG Lun, ZHU Feng. Multi-agent reinforcement learning based traffic signal control for integrated urban network: survey of state of art[J]. Application Research of Computers, 2018, 35(6): 1613-1618.(in Chinese)
[20] LI Zhen-ning, YU Hao, ZHANG Guo-hui, et al. Network-wide traffic signal control optimization using a multi-agent deep reinforcement learning[J]. Transportation Research Part C: Emerging Technologies, 2021, 125: 103059.
[21] LE T, KOVÁCS P, WALTON N, et al. Decentralized signal control for urban road networks[J]. Transportation Research Part C: Emerging Technologies, 2015, 58: 431-450.
[22] UKKUSURI S, DOAN K, AZIZ H M A. A bi-level formulation for the combined dynamic equilibrium based traffic signal control[J]. Procedia—Social and Behavioral Sciences, 2013, 80: 729-752.
[23] FENG Yi-heng, HEAD K L, KHOSHMAGAHAM S, et al. A real-time adaptive signal control in a connected vehicle environment[J]. Transportation Research Part C: Emerging Technologies, 2015, 55: 460-473.
[24] 王正武,罗大庸,黄中祥.基于CTM的信号优化设计及求解[J].交通运输工程学报,2007,7(4):84-88.
WANG Zheng-wu, LUO Da-yong, HUANG Zhong-xiang. Optimization designing and solving of signal based on CTM[J]. Journal of Traffic and Transportation Engineering, 2007, 7(4): 84-88.(in Chinese)
[25] MOHEBIFARD R, HAJBABAIE A. Optimal network-level traffic signal control: a benders decomposition-based solution algorithm[J]. Transportation Research Part B: Methodological, 2019, 121: 252-274.
[26] AI ISLAM S M A B, HAJBABAIE A, AZIZ H M A. A real-time network-level traffic signal control methodology with partial connected vehicle information[J]. Transportation Research Part C: Emerging Technologies, 2020, 121: 102830.
[27] ZAIDI A A, KULCSÁR B, WYMEERSCH H. Back-pressure traffic signal control with fixed and adaptive routing for urban vehicular networks[J]. IEEE Transactions on Intelligent Transportation Systems, 2016, 17(8): 2134-2143.
[28] YU Hao, LIU Pan, FAN Yue-yue, et al. Developing a decentralized signal control strategy considering link storage capacity[J]. Transportation Research Part C: Emerging Technologies, 2021, 124: 102971.
[29] GARTNER N H, LITTLE J D C, GABBAY H. Optimization of traffic signal settings by mixed-integer linear programming: Part II: the network synchronization problem[J]. Transportation Science, 1975, 9(4): 321-343.
[30] MA Cheng-yuan, YU Chun-hui, YANG Xiao-guang. Trajectory planning for connected and automated vehicles at isolated signalized intersections under mixed traffic environment[J]. Transportation Research Part C: Emerging Technologies, 2021, 130: 103309.
[31] YU C H, FENG Y H, LIU H X, et al. Corridor level cooperative trajectory optimization with connected and automated vehicles[J]. Transportation Research Part C: Emerging Technologies, 2019, 105: 405-421.