Page 156 - 《软件学报》2021年第8期

2438 Journal of Software 软件学报 Vol.32, No.8, August 2021

[24] Kang W, Xiong G, Lv Y, Dong X, Zhu F, K QJ. Traffic signal coordination for emergency vehicles. In: Proc. of the 17th IEEE Int’l
Conf. on Intelligent Transportation Systems (ITSC). IEEE, 2014. 157−161.
[25] Noori H, Fu L, Shiravi S, Noori H, Fu L, Shiravi S. A connected vehicle based traffic signal control strategy for emergency vehicle
preemption. In: Proc. of the Transportation Research Board 95th Annual Meeting. 2016.
[26] Mei Z, Tan Z, Zhang W, Wang D. Simulation analysis of traffic signal control and transit signal priority strategies under arterial
coordination conditions. Simulation, 2019,95(1):51−64.
[27] Younes MB, Boukerche A. An efficient dynamic traffic light scheduling algorithm considering emergency vehicles for intelligent
transportation systems. Wireless Networks, 2018,24(7):2451−2463.
[28] Sutton RS, Barto AG. Reinforcement Learning: An Introduction. MIT Press, 1998.
[29] Liang X, Du X, Wang G, Han Z. A deep reinforcement learning network for traffic light cycle control. IEEE Trans. on Vehicular
Technology, 2019,68(2):1243−1253.
[30] Kim CH, Watanabe K, Nishide S, Guoko M. Epsilon-greedy babbling. In: Proc. of the 2017 Joint IEEE Int’l Conf. on Development
and Learning and Epigenetic Robotics (ICDL-EpiRob). 2017. 227−232.
[31] Esmaeili A, Marvasti F. A novel approach to quantized matrix completion using Huber loss measure. IEEE Signal Processing
Letters, 2019,26(2):337−341.
[32] Adam S, Busoniu L, Babuska R. Experience replay for real-time reinforcement learning control. IEEE Trans. on Systems, Man, and
Cybernetics, Part C (Applications and Reviews), 2011,42(2):201−212.
[33] Kingma DP, Ba J. Adam: A method for stochastic optimization. In: Proc. of the 3rd Int’l Conf. on Learning Representations (ICLR).
San Diego, 2015.
[34] Wu T, Zhou P, Liu K, Yuan Y, Wang X, Huang H, Wu DO. Multi-Agent deep reinforcement learning for urban traffic light control
in vehicular networks. IEEE Trans. on Vehicular Technology, 2020,69(8):8243−8256.
附中文参考文献:
[1] 2018 年交通运行年报.2018. http://www.jtcx.sh.cn/trafficanalyse.html
[3] 吴黎兵,聂雷,刘冰艺,吴妮,邹逸飞,叶璐瑶.一种 VANET 环境下的智能交通信号控制方法.计算机学报,2016,39(6):1105−1119.
[5] 张政馗,庞为光,谢文静,吕鸣松,王义.面向实时应用的深度学习研究综述.软件学报,2020,31(9):2654−2677. http://www.jos.org.cn/
1000-9825/5946.htm [doi: 10.13328/j.cnki.jos.005946]
[9] 徐杨,张玉林,孙婷婷,苏艳芳.基于多智能体交通绿波效应分布式协同控制算法.软件学报, 2012,23(11):2937−2945 http://www.
jos.org.cn/1000-9825/4307.htm [doi: 10.3724/SP.J.1001.2012.04307]

邵明莉(1997－),女,硕士,CCF 学生会员, 章玥(1981－),女,博士,副教授,CCF 专业
主要研究领域为强化学习,交通灯控制. 会员,主要研究领域为软件定义网络,物
联网.

曹鹗(1994－),男,硕士,主要研究领域为云 陈闻杰(1977－),男,博士,副教授,CCF 专
计算工作流调度,物联网. 业会员,主要研究领域为嵌入式系统,物联
网,软硬件协同设计.

胡铭(1995－),男,博士生,CCF 学生会员, 陈铭松(1982－),男,博士,教授,博士生导
主要研究领域为程序分析与综合,CPS 系 师,CCF 高级会员,主要研究领域为嵌入式
统自动化设计. 系统,软硬件协同设计,物联网,信息物理
系统设计自动化.