Double Deep Q-Network with a Dual-Agent for Traffic Signal Control
Article
Gu, Jianfeng, Fang, Yong, Sheng, Zhichao and Wen, Peng. 2020. "Double Deep Q-Network with a Dual-Agent for Traffic Signal Control
." Applied Sciences. 10 (5), pp. 1-17. https://doi.org/10.3390/app10051622
| Article Title | Double Deep Q-Network with a Dual-Agent for Traffic Signal Control |
|---|---|
| ERA Journal ID | 211776 |
| Article Category | Article |
| Authors | Gu, Jianfeng, Fang, Yong, Sheng, Zhichao and Wen, Peng |
| Journal Title | Applied Sciences |
| Journal Citation | 10 (5), pp. 1-17 |
| Article Number | 1622 |
| Number of Pages | 17 |
| Year | Mar 2020 |
| Publisher | MDPI AG |
| Place of Publication | Switzerland |
| ISSN | 2076-3417 |
| Digital Object Identifier (DOI) | https://doi.org/10.3390/app10051622 |
| Web Address (URL) | https://www.mdpi.com/2076-3417/10/5/1622 |
| Abstract | Adaptive traffic signal control (ATSC) based on deep reinforcement learning (DRL) has shown promising prospects to reduce traffic congestion. Most existing methods keeping traffic signal phases fixed adopt two agent actions to match a four-phase suffering unstable performance and undesirable operation in a four-phase signalized intersection. In this paper, a Double Deep Q-Network (DDQN) with a dual-agent algorithm is proposed to obtain a stable traffic signal control policy. Specifically, two agents are denoted by two different states and shift the control of green lights to make the phase sequence fixed and control process stable. State representations and reward functions are presented by improving the observability and reducing the leaning difficulty of two agents. To enhance the feasibility and reliability of two agents in the traffic control of the four-phase signalized intersection, a network structure incorporating DDQN is proposed to map states to rewards. Experiments under Simulation of Urban Mobility (SUMO) are carried out, and results show that the proposed traffic signal control algorithm is effective in improving traffic capacity. |
| Keywords | adaptive traffic signal control; deep reinforcement learning; Double Deep Q-Network |
| ANZSRC Field of Research 2020 | 400899. Electrical engineering not elsewhere classified |
| Byline Affiliations | Shanghai University, China |
| University of Southern Queensland |
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Zhu, Guohun, Li, Yan, Wen, Peng (Paul), Wang, Shuaifang and Zhong, Ning. 2013. "Unsupervised classification of epileptic EEG signals with multi scale K-means algorithm." Imamura, Kazayuki, Usui, Shiro, Shirao, Tomoaki, Kasamatsu, Takuji, Schwabe, Lars and Zhong, Ning (ed.) 2013 International Conference on Brain and Health Informatics (BHI 2013). Maebashi, Japan 29 - 31 Oct 2013 Germany. Springer. https://doi.org/10.1007/978-3-319-02753-1_16Consciousness and depth of anesthesia assessment based on Bayesian analysis of EEG signals
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Li, Mao, Li, Yan and Wen, Peng (Paul). 2014. "Simulation study of pO2 distribution in induced tumour masses and normal tissues within a microcirculation environment." Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization. 17 (4), pp. 334-343. https://doi.org/10.1080/10255842.2012.683428Consciousness, EEG and depth of anaesthesia monitoring
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Zhu, Guohun, Li, Yan and Wen, Peng Paul. 2012. "An efficient visibility graph similarity algorithm and its application for sleep stages classification." Zanzotto, Fabio Massimo, Tsumoto, Shusaku, Taatgen, Niels and Yao, Yiyu (ed.) 2012 International Conference on Brain Informatics (BI 2012). Macau, China 04 - 07 Dec 2012 Heidelberg, Germany. Springer. https://doi.org/10.1007/978-3-642-35139-6_18Analysing epileptic EEGs with a visibility graph algorithm
Zhu, Guohun, Li, Yan and Wen, Peng (Paul). 2012. "Analysing epileptic EEGs with a visibility graph algorithm." Chen, Qianbin, Huan, Jun (Luke), Xu, Yong, Zhang, Tianqi and Wang, Lipo (ed.) 5th International Conference on Biomedical Engineering and Informatics (BMEI 2012). Chongqing, China 16 - 18 Oct 2012 Piscataway, NJ. United States. https://doi.org/10.1109/BMEI.2012.6513212Measuring the hypnotic depth of anaesthesia based on the EEG signal using combined wavelet transform, eigenvector and normalisation techniques
Nguyen-Ky, Tai, Wen, Peng, Li, Yan and Malan, Mel. 2012. "Measuring the hypnotic depth of anaesthesia based on the EEG signal using combined wavelet transform, eigenvector and normalisation techniques." Computers in Biology and Medicine. 42 (6), pp. 680-691. https://doi.org/10.1016/j.compbiomed.2012.03.004Effects of model complexity and tissue anisotropic conductivity on cortical modulation during transcranial direct current stimulation
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Li, Mao, Li, Yan and Wen, Peng (Paul). 2012. "Tumor-induced effects on PO2 distribution in a normal tissue." Zhang, Yuan-Ting, Naghavi, Morteza, Bonato, Paolo and Carmen, C. Y. Poon (ed.) 2012 IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics (BHI 2012). Hong Kong and Shenzhen, China 02 - 07 Jan 2012 Hong Kong, China. https://doi.org/10.1109/BHI.2012.6211594The effects of time-delay on feedback control of depth of anesthesia
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Wen, Peng and Li, Yan. 2011. "Twin rotor system modelling de-coupling and optimal control." ICMA 2011: IEEE International Conference on Mechatronics and Automation. Beijing, China 07 - 10 Aug 2011 Piscataway, NJ. United States. https://doi.org/10.1109/ICMA.2011.5986259Evaluating functional connectivity in alcoholics based on maximal weight matching
Zhu, Guohun, Li, Yan and Wen, Peng. 2011. "Evaluating functional connectivity in alcoholics based on maximal weight matching." Journal of Advanced Computational Intelligence and Intelligent Informatics. 15 (9), pp. 1221-1227.EEG signal classification based on simple random sampling technique with least square support vector machine
Li, Yan and Wen, Peng. 2011. "EEG signal classification based on simple random sampling technique with least square support vector machine." International Journal of Biomedical Engineering and Technology. 7 (4), pp. 390-409. https://doi.org/10.1504/IJBET.2011.044417Convection drying process modeling and simulation study based on tomato
Shahab, Anna, Wen, Peng and Richard, George. 2009. "Convection drying process modeling and simulation study based on tomato." Giannoccaro, Nicola Ivan and Klingajay, Mongkorn (ed.) International Conference on Robotics, Informatics, Intelligence Control System Technology (RIIT 2009). Bangkok, Thailand 11 - 14 Dec 2009 Bangkok, Thailand.Real-time pressure monitoring and control of a hydraulic system without sensor
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Nguyen-Ky, T., Wen, Peng and Li, Yan. 2009. "Theoretical basis for identification of different anesthetic states based on routinely recorded EEG during operation." Computers in Biology and Medicine. 39 (1), pp. 40-45. https://doi.org/10.1016/j.compbiomed.2008.10.007Effects of white matter on EEG of multi-layered spherical head models
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Bashar, Md. Rezaul, Li, Yan and Wen, Peng. 2008. "A study of white matter and skull inhomogeneous anisotropic tissue conductivities on EEG forward head modeling." Karim, Mohammad (ed.) DMAI 2008: 1st IEEE International Workshop on Data Mining and Artificial Intelligence. Khulna, Bangladesh 24 - 27 Dec 2008 Bangladesh. https://doi.org/10.1109/ICCITECHN.2008.4803103Tension control of a winding machine for rectangular coils
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Li, Yingchun, Wang, Zicong, Wen, Peng and Meng, Max Q.-H.. 2007. "Accurately monitoring the depth of anaesthesia using an intelligent method." 2007 IEEE/ICM International Conference on Complex Medical Engineering (CME 2007). Beijing, China 23 - 27 May 2007 Beijing, China. https://doi.org/10.1109/ICCME.2007.4381761Monitoring depth of anaesthesia using auditory evoked potential and bispectrum
Wang, Zicong, Li, Yingchun, Wen, Peng and Meng, Max Q.-H.. 2007. "Monitoring depth of anaesthesia using auditory evoked potential and bispectrum." 2007 IEEE International Conference on Integration Technology. Shenzhen, China 20 - 24 Mar 2007 Shenzhen, China. https://doi.org/10.1109/ICITECHNOLOGY.2007.4290486Networked PID control system modeling and simulation using Markov chain
Teng, Lanzhi and Wen, Peng. 2007. "Networked PID control system modeling and simulation using Markov chain." 2007 IEEE International Conference on Integration Technology. Shenzhen, China 20 - 24 Mar 2007 Shenzhen, China.A novel attribute reduction algorithm based on peer-to-peer technique and rough set theory
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Wen, Peng and Li, Yan. 2004. "An internet based supervision control and data acquisition system with fault tolerance." 2004 International Conference on Computational Intelligence for Modelling, Control and Automation (CIMCA 2004). Gold Coast, Australia 12 - 14 Jul 2004 Washington, DC, united States.Deadline fault tolerance in a networked real-time system
Wen, Peng and Li, Yan. 2006. "Deadline fault tolerance in a networked real-time system." 4th International Conference on Active Media Technology (AMT 2006). Brisbane, Australia 07 - 09 Jun 2006 United States.The impact of inhomogeneous tissue anisotropy on potential distribution within head model
Wen, Peng. 2003. "The impact of inhomogeneous tissue anisotropy on potential distribution within head model." Professor Yogesh K Dwivedi. 26 (3), pp. 87-90.EEG human head modelling based on heterogeneous tissue conductivity
Wen, Peng and Li, Yan. 2006. "EEG human head modelling based on heterogeneous tissue conductivity." Professor Yogesh K Dwivedi. 29 (3), pp. 235-240.The real-time computing model for a network based control system
Wen, Peng and Li, Yan. 2004. "The real-time computing model for a network based control system." 8th International Conference on Control, Automation, Robotics and Vision (ICARCV 2004) . Kunming, China 06 - 09 Dec 2004 United States.Bayesian model for brain computation
Li, Yan and Wen, Peng. 2005. "Bayesian model for brain computation." Wu, Jinglong and Ito, Koji (ed.) 1st International Conference on Complex Medical Engineering (CME 2005). Takamatsu, Japan 15 - 18 May 2005 Kagawa, Japan.Electronic height indicator for agricultural machines
Wen, Peng and Kidd, Jason G.. 2005. "Electronic height indicator for agricultural machines." Australian Journal of Electrical and Electronics Engineering. 2 (1), pp. 13-20.Preliminary investigation of the digital human head
McCarthy, Elizabeth and Wen, Peng. 2005. "Preliminary investigation of the digital human head." Wu, Jinglong and Ito, Koji (ed.) 1st International Conference on Complex Medical Engineering (CME 2005). Takamatsu, Japan 15 - 18 May 2005 Kagawa, Japan.Comparison study of different head model structures with homogeneous/inhomogeneous conductivity
Wen, P. and Li, Y.. 2001. "Comparison study of different head model structures with homogeneous/inhomogeneous conductivity." Physical and Engineering Sciences in Medicine. 24 (1), pp. 31-36. https://doi.org/10.1007/BF03178283This item comprises data from the following sources: Web of Science