This is a collection of research papers for Traffic Signal Control with RL. And the repository will be continuously updated to track the frontier of RL-based traffic signal control.
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There are contributors to this paper collection, we will continue to update it.
If you find LibSignal useful for your research or development, please cite our paper. Mei, H., Lei, X., Da, L. et al. Libsignal: an open library for traffic signal control. Mach Learn (2023). https://doi.org/10.1007/s10994-023-06412-y
@article{mei2023libsignal,
title={Libsignal: an open library for traffic signal control},
author={Mei, Hao and Lei, Xiaoliang and Da, Longchao and Shi, Bin and Wei, Hua},
journal={Machine Learning},
pages={1--37},
year={2023},
publisher={Springer}
}
In the paper collection, we collected RL-based traffic signal control papers published in the recent years (2016-2021) on 8 top conferences and journals, namely, NeurIPS, AAAI, AAMAS, KDD, CIKM, IEEE TITS, ITSC, TR-B and their workshop papers. In addition, the surveys since 2018 and representative papers mentioned in the surveys are also included. We will continue to update the collection.
Graph Neural Networks for Intelligent Transportation Systems: A Survey. S Rahmani, A Baghbani, et, al. IEEE Transactions on Intelligent Transportation Systems. 2023. link
Deep Reinforcement Learning Based Traffic Signal Control: A Comparative Analysis. C Wu, I Kim, et, al. 2023. link
Reinforcement learning in urban network traffic signal control: A systematic literature review. M Noaeen, A Naik, L Goodman, J Crebo, et, al.. 2022. link
The Real Deal: A Review of Challenges and Opportunities in Moving Reinforcement Learning-Based Traffic Signal Control Systems Towards Reality. R Chen, F Fang, N Sadeh. 2022. link
A review of reinforcement learning applications in adaptive traffic signal control. M Miletić, E Ivanjko, et, al. IET Intelligent Transportation System. 2022. link
Traffic Signal Control Methods: Current Status, Challenges, and Emerging Trends. I Tomar, S Indu, N Pandey. Data Analytics and Management. 2022. link
Reinforcement learning in urban network traffic signal control: A systematic literature review. M Noaeen, A Naik, L Goodman, J Crebo, T Abrar. Expert Systems with Applications. 2022. link
A Comparison of Deep Reinforcement Learning Models for Isolated Traffic Signal Control. F Mao, Z Li, L Li. IEEE Intelligent Transportation Systems Magazine. 2022. link
A Comparative Study of Algorithms for Intelligent Traffic Signal Control. H Chaudhuri, V Masti, V Veerendranath. Machine Learning and Autonomous Systems. 2022. link
Recent advances in reinforcement learning for traffic signal control: A survey of models and evaluation. H Wei, G Zheng, V Gayah, Z Li. ACM SIGKDD Explorations Newsletter. 2021. link
A Survey on Deep Reinforcement Learning for Traffic Signal Control. W Miao, L Li, Z Wang. Chinese Control and Decision Conference. 2021. link
Comparative Evaluation of Road Traffic Simulators based on Modeler's Specifications: An Application to Intermodal Mobility Behaviors.. AO Diallo, G Lozenguez, A Doniec, R Mandiau. International Conference on Agents and Artificial Intelligence . 2021. link
Deep reinforcement learning in transportation research: A review. NP Farazi, B Zou, T Ahamed, L Barua. Transportation Research Interdisciplinary Perspectives. 2021. link
Reinforcement learning for traffic signal control: comparison with commercial systems. A Cabrejas-Egea, R Zhang, N Walton. Transportation research procedia. 2021. link
Decision-making at unsignalized intersection for autonomous vehicles: Left-turn maneuver with deep reinforcement learning. T Liu, X Mu, B Huang, X Tang, F Zhao, X Wang. arXiv preprint arXiv .... 2020. link
Deep reinforcement learning and transportation research: A comprehensive review. NP Farazi, T Ahamed, L Barua, B Zou. arXiv preprint arXiv:2010.06187. 2020. link
State-of-art review of traffic signal control methods: challenges and opportunities. SSSM Qadri, MA Gökçe, E Öner. European transport research review. 2020. link
Deep reinforcement learning for traffic signal control: A review. F Rasheed, KLA Yau, RM Noor, C Wu, YC Low. IEEE Access. 2020. link
A review on swarm intelligence and evolutionary algorithms for solving the traffic signal control problem. PW Shaikh, M El-Abd, M Khanafer. IEEE transactions on .... 2020. link
QarSUMO: A Parallel, Congestion-optimized Traffic Simulator. H Chen, K Yang, SG Rizzo, G Vantini, P Taylor. International Conference on Advances in Geographic Information Systems. 2020. link
Assessment of reward functions for reinforcement learning traffic signal control under real-world limitations. AC Egea, S Howell, M Knutins. International Conference on Systems, Man, and Cybernetics. 2020. link
A review on swarm intelligence and evolutionary algorithms for solving the traffic signal control problem. PW Shaikh, M El-Abd, M Khanafer. TITS. 2020. link
Deep reinforcement learning for intelligent transportation systems: A survey. A Haydari, Y Yilmaz. TITS. 2020. link
A survey on traffic signal control methods. H Wei, G Zheng, V Gayah, Z Li. arXiv preprint. 2019. link
Cityflow: A multi-agent reinforcement learning environment for large scale city traffic scenario. H Zhang, S Feng, C Liu, Y Ding, Y Zhu, Z Zhou. TheWebConf. 2019. link
A survey on reinforcement learning models and algorithms for traffic signal control. KLA Yau, J Qadir, HL Khoo, MH Ling. ACM Computing Surveys. 2017. link
Comprehensive analysis of reinforcement learning methods and parameters for adaptive traffic signal control. S El-Tantawy, B Abdulhai. TRB. 2011. link
Attendlight: Universal attention-based reinforcement learning model for traffic signal control. A Oroojlooy, M Nazari. NeurIPS. 2020. link
Learning individually inferred communication for multi-agent cooperation. Z Ding, T Huang, Z Lu. NeurIPS. 2020. link
Safelight: A reinforcement learning method toward collision-free traffic signal control. Liang E, Su Z, Fang C, et al. AAAI. 2022. link
OAM: An Option-Action Reinforcement Learning Framework for Universal Multi-Intersection Control. Liang E, Su Z, Fang C, et al. AAAI. 2022. link
Hierarchically and cooperatively learning traffic signal control. B Xu, Y Wang, Z Wang, H Jia, Z Lu. AAAI. 2021. link
Metalight: Value-based meta-reinforcement learning for traffic signal control. X Zang, H Yao, G Zheng, N Xu, K Xu, Z Li. AAAI. 2020. link
Toward a thousand lights: Decentralized deep reinforcement learning for large-scale traffic signal control. C Chen, H Wei, N Xu, G Zheng, M Yang. AAAI. 2020. link
Feudal multi-agent deep reinforcement learning for traffic signal control. J Ma, F Wu. AAMAS. 2020. link
Reinforcement Learning for Traffic Signal Control Optimization: A Concept for Real-World Implementation. H Meess, J Gerner, D Hein, S Schmidtner. AAMAS. 2022. link
Cooperative max-pressure enhanced traffic signal control. Li L, Li R, Peng Y, et al. CIKM. 2022. link
Meta-Reinforcement Learning for Multiple Traffic Signals Control. Lou Y, Wu J, Ran Y. CIKM. 2022. link
DynSTGAT: Dynamic Spatial-Temporal Graph Attention Network for Traffic Signal Control. L Wu, M Wang, D Wu, J Wu. CIKM. 2021. link
Generalight: Improving environment generalization of traffic signal control via meta reinforcement learning. H Zhang, C Liu, W Zhang, G Zheng, Y Yu. CIKM. 2020. link
Colight: Learning network-level cooperation for traffic signal control. H Wei, N Xu, H Zhang, G Zheng, X Zang. CIKM. 2019. link
Learning phase competition for traffic signal control. G Zheng, Y Xiong, X Zang, J Feng, H Wei. CIKM. 2019. link
Learning traffic signal control from demonstrations. Y Xiong, G Zheng, K Xu, Z Li. CIKM. 2019. link
CoTV: Cooperative Control for Traffic Light Signals and Connected Autonomous Vehicles Using Deep Reinforcement Learning. Guo J, Cheng L, Wang S. TITS. 2023. link
DeepGAL: Intelligent Vehicle Control for Traffic Congestion Alleviation at Intersections. Cao M, Li V O K, Shuai Q. TITS. 2023. link
Real-Time Cooperative Vehicle Coordination at Unsignalized Road Intersections. Luo J, Zhang T, Hao R, et al. TITS. 2023. link
A gain with no pain: Exploring intelligent traffic signal control for emergency vehicles. Cao M, Li V O K, Shuai Q. TITS. 2023. link
Network-wide traffic signal control using bilinear system modeling and adaptive optimization. Wang H, Zhu M, Hong W, et al. TITS. 2022. link
Mastering arterial traffic signal control with multi-agent attention-based soft actor-critic model. Mao F, Li Z, Lin Y, et al. TITS. 2022. link
Distributed Signal Control of Arterial Corridors Using Multi-Agent Deep Reinforcement Learning. Zhang W, Yan C, Li X, et al. TITS. 2022. link
Network-Level Traffic Signal Cooperation: A Higher-Order Conflict Graph Approach. Li W, Wang B, Khattak Z H, et al. TITS. 2022. link
PV-TSC: Learning to control traffic signals for pedestrian and vehicle traffic in 6G era. Xu K, Huang J, Kong L, et al. TITS. 2022. link
A Gain With No Pain: Exploring Intelligent Traffic Signal Control for Emergency Vehicles. M Cao, VOK Li, Q Shuai. TITS. 2022. link
PV-TSC: Learning to Control Traffic Signals for Pedestrian and Vehicle Traffic in 6G Era. K Xu, J Huang, L Kong, J Yu. TITS. 2022. link
Data augmented deep behavioral cloning for urban traffic control operations under a parallel learning framework. X Li, P Ye, J Jin, F Zhu, FY Wang. TITS. 2021. link
IG-RL: Inductive graph reinforcement learning for massive-scale traffic signal control. FX Devailly, D Larocque. TITS. 2021. link
Traffic signal control with reinforcement learning based on region-aware cooperative strategy. M Wang, L Wu, J Li, L He. TITS. 2021. link
Fuzzy inference enabled deep reinforcement learning-based traffic light control for intelligent transportation system. N Kumar, SS Rahman, N Dhakad. TITS. 2020. link
Optimizing signal timing control for large urban traffic networks using an adaptive linear quadratic regulator control strategy. H Wang, M Zhu, W Hong, C Wang. TITS. 2020. link
Multi-agent deep reinforcement learning for large-scale traffic signal control. T Chu, J Wang, L Codecà , Z Li. TITS. 2019. link
Meta-heuristics for bi-objective urban traffic light scheduling problems. K Gao, Y Zhang, Y Zhang, R Su. TITS. 2018. link
Reinforcement learning with function approximation for traffic signal control. LA Prashanth, S Bhatnagar. TITS. 2010. link
QueueLearner: A Knowledge-Combined Reinforcement Learning to Understand Queuing Evolution in Isolated Traffic Signal Control. Han T, Oguchi T, Lyu S. ITSC. 2022. link
A Hierarchical Spatio-Temporal Cooperative Reinforcement Learning Approach for Traffic Signal Control. Li M, Hu Z, Huang H, et al. ITSC. 2022. link
A Spatial-Temporal Deep Reinforcement Learning Model for Large-Scale Centralized Traffic Signal Control. Yi C, Wu J, Ren Y, et al. ITSC. 2022. link
A Deep Reinforcement Learning Framework with Memory Network to Coordinate Traffic Signal Control. Kong A Y, Lu B X, Yang C Z, et al. ITSC. 2022. link
Safe and Psychologically Pleasant Traffic Signal Control with Reinforcement Learning using Action Masking. Müller A, Sabatelli M. ITSC. 2022. link
Meta-Reinforcement Learning for Centralized Multiple Intersections Traffic Signal Control. Ren Y, Wu J, Yi C, et al. ITSC. 2022. link
A deep reinforcement learning approach for fair traffic signal control. M Raeis, A Leon-Garcia. ITSC. 2021. link
An ontology-based intelligent traffic signal control model. S Ghanadbashi, F Golpayegani. ITSC. 2021. link
Designing Reinforcement Learning Agents for Traffic Signal Control with the Right Goals: a Time-Loss based Approach. M D'Almeida, A Paes, D Mossé. ITSC. 2021. link
A deep on-policy learning agent for traffic signal control of multiple intersections. CC Yen, D Ghosal, M Zhang. ITSC. 2020. link
A reinforcement learning approach for intelligent traffic signal control at urban intersections. M Guo, P Wang, CY Chan. ITSC. 2019. link
Reinforcement learning with explainability for traffic signal control. SG Rizzo, G Vantini, S Chawla. ITSC. 2019. link
Traffic Signal Control for Isolated Intersection Based on Coordination Game and Pareto Efficiency. Y Zhao, Y Liang, J Hu, Z Zhang. ITSC. 2019. link
Training reinforcement learning agent for traffic signal control under different traffic conditions. J Zeng, J Hu, Y Zhang. ITSC. 2019. link
Deep learning vs. discrete reinforcement learning for adaptive traffic signal control. SMA Shabestary, B Abdulhai. ITSC. 2018. link
Traffic signal control based on reinforcement learning with graph convolutional neural nets. T Nishi, K Otaki, K Hayakawa. ITSC. 2018. link
Traffic behavior recognition from traffic videos under occlusion condition: a Kalman filter approach. Jiao J, Wang H. TR-C. 2022. link
Intelligent vehicle pedestrian light (IVPL): A deep reinforcement learning approach for traffic signal control. Yazdani M, Sarvi M, Bagloee S A, et al. TR-C. 2022. link
Adaptive Traffic Signal Control for large-scale scenario with Cooperative Group-based Multi-agent reinforcement learning. T Wang, J Cao, A Hussain. TR-C. 2021. link
DRL-TP3: A learning and control framework for signalized intersections with mixed connected automated traffic. Y Guo, J Ma. TR-C. 2021. link
Network-wide traffic signal control optimization using a multi-agent deep reinforcement learning. Z Li, H Yu, G Zhang, S Dong, CZ Xu. TR-C. 2021. link
An equitable traffic signal control scheme at isolated signalized intersections using Connected Vehicle technology. XJ Liang, SI Guler, VV Gayah. TR-C. 2020. link
Reinforcement learning with average cost for adaptive control of traffic lights at intersections. LA Prashanth, S Bhatnagar. ITSC. 2011. link
An efficient deep reinforcement learning model for urban traffic control. Y Lin, X Dai, L Li, FY Wang. ICDM Workshop. 2018. link
Deep reinforcement learning for traffic light optimization. M CoÅŸkun, A Baggag, S Chawla. ICDM Workshop. 2018. link
A reinforcement learning approach with Fourier basis linear function approximation for traffic signal control. T Ziemke, LN Alegre, ALC Bazzan. ECAI Workshop. 2020. link
Coordinated deep reinforcement learners for traffic light control. E Van der Pol, FA Oliehoek. NeurIPS Workshop. 2016. link
Towards Explainable Deep Reinforcement Learning for Traffic Signal Control. LV Schreiber, GO Ramos, ALC Bazzan. ICML Workshop. 2021. link
Multi-agent reinforcement learning for traffic signal control: A cooperative approach. M Kolat, B Kővári, T Bécsi. Sustainability, 2023. link
Distributed agent-based deep reinforcement learning for large scale traffic signal control. Q Wu, J Wu, J Shen, et, al. Knowledge-Based Systems. 2022. link
Intelligent Traffic Signal Phase Distribution System Using Deep Q-Network. H Joo, Y Lim. Applied Sciences. 2022. link
Model Predictive Traffic Control by Bi-Level Optimization. K Stoilova, T Stoilov. Applied Sciences. 2022. link
A Concurrent Switching Model for Traffic Congestion Control. H Rastgoftar, X Liu, JB Jeannin. arXiv preprint. 2022. link
CoTV: Cooperative Control for Traffic Light Signals and Connected Autonomous Vehicles using Deep Reinforcement Learning. J Guo, L Cheng, S Wang. arXiv preprint. 2022. link
Offline Reinforcement Learning for Road Traffic Control. M Kunjir, S Chawla. arXiv preprint. 2022. link
Proximal Policy Optimization Learning based Control of Congested Freeway Traffic. S Mo, J Qi, A Pan. arXiv preprint. 2022. link
Cooperative Traffic Signal Control Through A Counterfactual Multi-Agent Deep Actor Critic Approach. X Song, B Zhou, D Ma. Available at SSRN 40219. 2022. link
Dynamic Traffic Light Control with Reinforcement Learning Based on Gnn Prediction. C Zhao, G Wang. Available at SSRN 40405. 2022. link
Deep Reinforcement Learning for Addressing Disruptions in Traffic Light Control. F Rasheed, KLA Yau, RM Noor. Computers, Materials and Continua. 2022. link
Exploring reward efficacy in traffic management using deep reinforcement learning in intelligent transportation system. A Paul, S Mitra. ETRI Journal. 2022. link
Learning from Oracle Demonstrations–A new approach to develop Autonomous Intersection Management control algorithms based on Multi-Agent Deep .... A Guillen-Perez, MD Cano. IEEE Access. 2022. link
Intelligent Traffic Light Control by Exploring Strategies in an Optimised Space of Deep Q-Learning. J Liu, S Qin, Y Luo, Y Wang. IEEE Transactions on Vehicular Technology. 2022. link
Micro Junction Agent: A Scalable Multi-agent Reinforcement Learning Method for Traffic Control. BK Choi, JSB Choe, J Kim. International Conference on Agents and Artificial Intelligence. 2022. link
Dynamic Weight-based Multi-Objective Reward Architecture for Adaptive Traffic Signal Control System. ARM Jamil, N Nower. International Journal of Intelligent Transportation Systems Research. 2022. link
Centralized and Decentralized Signal Control with Short-Term Origin-Destination Demand for Network Traffic. C Zhang, TZ Qiu, A Kim. Journal of Advanced Transportation. 2022. link
IPDALight: Intensity-and phase duration-aware traffic signal control based on Reinforcement Learning. W Zhao, Y Ye, J Ding, T Wang, T Wei. Journal of Systems Architecture. 2022. link
Distributed agent-based deep reinforcement learning for large scale traffic signal control. Q Wu, J Wu, J Shen, B Du, A Telikani. Knowledge-Based Systems. 2022. link
A fog-based Traffic Light Management Strategy (TLMS) based on fuzzy inference engine. SA Gamel, AI Saleh, HA Ali. Neural Computing and Applications. 2022. link
Information upwards, recommendation downwards: reinforcement learning with hierarchy for traffic signal control. TO Antes, ALC Bazzan, AR Tavares. Procedia Computer Science. 2022. link
Biased pressure: cyclic reinforcement learning model for intelligent traffic signal control. B Ibrokhimov, YJ Kim, S Kang. Sensors. 2022. link
SecureTLC: Secure and Two-level Traffic Signal Control for Intelligent Transportation System. CC Yen. UC Davis Electronic Theses and Dissertations. 2022. link
Attacking Deep Reinforcement Learning-Based Traffic Signal Control Systems with Colluding Vehicles, Qu, Ao, Yihong Tang, and Wei Ma. arXiv preprint arXiv:2111.02845. 2021. link
Traffic Signal Optimization for Multiple Intersections Based on Reinforcement Learning. J Gu, M Lee, C Jun, Y Han, Y Kim, J Kim. Applied Sciences. 2021. link
A Decentralized Reinforcement Learning Framework for Efficient Passage of Emergency Vehicles. H Su, YD Zhong, D Biswadip, A Chakraborty. arXiv preprint. 2021. link
A Methodology for the Development of RL-Based Adaptive Traffic Signal Controllers. GS Varela, PP Santos, A Sardinha, FS Melo. arXiv preprint. 2021. link
Back to Basics: Deep Reinforcement Learning in Traffic Signal Control. S Kanis, L Samson, D Bloembergen. arXiv preprint. 2021. link
DQN Control Solution for KDD Cup 2021 City Brain Challenge. Y Chen, K Chen, K Chen, L Wang. arXiv preprint. 2021. link
EMVLight: A Decentralized Reinforcement Learning Framework for Efficient Passage of Emergency Vehicles. H Su, YD Zhong, B Dey, A Chakraborty. arXiv preprint. 2021. link
Expression is enough: Improving traffic signal control with advanced traffic state representation. L Zhang, Q Wu, J Shen, L Lü, J Wu, B Du. arXiv preprint. 2021. link
Variationally and intrinsically motivated reinforcement learning for decentralized traffic signal control. L Zhu, P Peng, Z Lu, X Wang, Y Tian. arXiv preprint. 2021. link
A deterministic predictive traffic signal control model in intelligent transportation and geoinformation systems. VV Myasnikov, AA Agafonov, AS Yumaganov. Computer Optics. 2021. link
Traffic Signal Control: a Double Q-learning Approach. A Agafonov, V Myasnikov. Conference on Computer Science and Intelligence Systems. 2021. link
Multi-agent Deep Reinforcement Learning with Spatio-Temporal Feature Fusion for Traffic Signal Control. X Du, J Wang, S Chen, Z Liu. ECML-PKDD. 2021. link
Traffic Signal Control System Based on Intelligent Transportation System and Reinforcement Learning. J Hurtado-Gómez, JD Romo, R Salazar-Cabrera. Electronics. 2021. link
Learning scalable multi-agent coordination by spatial differentiation for traffic signal control. J Liu, H Zhang, Z Fu, Y Wang. Engineering Applications of Artificial Intelligence. 2021. link
Intelligent Traffic Signal Control System using Deep Q-network. H Joo, Y Lim. Eurasia Conference on IOT, Communication and Engineering. 2021. link
Hierarchical traffic signal optimization using reinforcement learning and traffic prediction with long-short term memory. M Abdoos, ALC Bazzan. Expert systems with applications. 2021. link
Transfer Learning Method in Reinforcement Learning-based Traffic Signal Control. Z Mao, J Li, N Zheng, K Tei. Global Conference on Consumer Electronics. 2021. link
Probabilistic Graph Neural Networks for Traffic Signal Control. T Zhong, Z Xu, F Zhou. ICASSP. 2021. link
Urban Traffic Light Control Considering Capacity Difference Between Public Bus and Private Vehicles. Z Liu, N Wu, K Gao. IEEE Access. 2021. link
Self-Optimizing Traffic Light Control Using Hybrid Accelerated Extremum Seeking. F Galarza-Jimenez, JI Poveda. IEEE Conference on Decision and Control. 2021. link
Knowledge embedding-assisted multi-exemplar learning particle swarm optimization for traffic signal timing optimization. ZJ Deng, LY Luo, ZH Zhan. IEEE Congress on Evolutionary Computation. 2021. link
TSLib: A Unified Traffic Signal Control Framework Using Deep Reinforcement Learning and Benchmarking. TV Tran, TN Doan, M Sartipi. IEEE International Conference on Big Data (Big Data). 2021. link
Reinforcement Learning-driven Attack on Road Traffic Signal Controllers. NS Arabi, T Halabi, M Zulkernine. IEEE International Conference on Cyber Security and Resilience. 2021. link
A Meta Multi-agent Reinforcement Learning Algorithm for Multi-intersection Traffic Signal Control. S Yang, B Yang. IEEE Intl Conf on Dependable, Autonomic and Secure Computing. 2021. link
Adversarial Attacks and Defense in Deep Reinforcement Learning (DRL)-Based Traffic Signal Controllers. A Haydari, M Zhang, CN Chuah. IEEE Open Journal of Intelligent Transportation Systems . 2021. link
Improving Traffic Signal Control With Joint-Action Reinforcement Learning. JVB Labres, ALC Bazzan. IEEE Symposium Series on Computational Intelligence. 2021. link
GAN and Multi-Agent DRL based Decentralized Traffic Light Signal Control. Z Wang, H Zhu, M He, Y Zhou, X Luo. IEEE Transactions on Vehicular Technology. 2021. link
Deep Reinforcement Learning Model to Mitigate Congestion in Real-Time Traffic Light Networks. FSP Borges, AP Fonseca, RC Garcia. Infrastructures. 2021. link
Minimize Traffic Congestion with Emergency Facilitation using Deep Reinforcement Learning. D Kodagoda, D Perera, G Seneviratne. International Conference on Advances in ICT for Emerging Regions. 2021. link
Joint Control of Lane Allocation and Traffic Light for Changeable-Lane Intersection Based on Reinforcement Learning. ESA Gyarteng, R Shi, Y Long. International Conference on Algorithms, Computing and Artificial Intelligence. 2021. link
Combining SysML with Petri Nets for the Design of an Urban Traffic Signal Control. LS Souza, MS Soares. International Conference on Computational Science and Its Applications. 2021. link
Intelligent Traffic Signal Control with Deep Reinforcement Learning at Single Intersection. Y Li, J He, Y Gao. International Conference on Computing and Artificial Intelligence. 2021. link
Agent-Based Traffic Signal Control Using a Reinforcement Learning Approach. A Agafonov, A Yumaganov. International Conference on Information Technology and Nanotechnology. 2021. link
Adaptive Traffic Control With TinyML. AN Roshan, B Gokulapriyan. International Conference on Wireless Communications, Signal Processing and Networking. 2021. link
A Spatial-Temporal Graph Attention Network for Multi-intersection Traffic Light Control. L He, L Wu, M Wang, J Li, D Wu. International Joint Conference on Neural Networks. 2021. link
Evaluating action durations for adaptive traffic signal control based on deep Q-learning. SA Celtek, A Durdu, MEM Ali. International Journal of Intelligent Transportation Systems Research . 2021. link
Control and Coordination of Self-Adaptive Traffic Signal Using Deep Reinforcement Learning.. P Mandhare, J Yadav, V Kharat. International Journal of Next-Generation Computing. 2021. link
An Innovative Hybrid Biologically Inspired Method for Traffic Optimization Problem. S Srivastava, T Stephan, SK Sahana. International Journal on Artificial Intelligence Tools. 2021. link
An effective hybrid-heuristic algorithm for urban traffic light scheduling. CW Tsai, TC Teng, JT Liao, MC Chiang. Neural Computing and Applications . 2021. link
IHG-MA: Inductive heterogeneous graph multi-agent reinforcement learning for multi-intersection traffic signal control. S Yang, B Yang, Z Kang, L Deng. Neural networks. 2021. link
Quantifying the impact of non-stationarity in reinforcement learning-based traffic signal control. LN Alegre, ALC Bazzan, BC da Silva. PeerJ Computer Science. 2021. link
Traffic signal optimization on a square lattice with quantum annealing. D Inoue, A Okada, T Matsumori, K Aihara, H Yoshida. Scientific reports. 2021. link
Traffic signal optimization on a square lattice with quantum annealing. D Inoue, A Okada, T Matsumori, K Aihara, H Yoshida. Scientific reports. 2021. link
Traffic signal control using hybrid action space deep reinforcement learning. S Bouktif, A Cheniki, A Ouni. Sensors. 2021. link
Network Traffic Signal Control with Short-Term Origin-Destination Demand in a Connected Vehicle Environment via Mobile Edge Computing. C Zhang. University of Alberta Libraries. 2021. link
Agent-Based Urban Traffic Management for Connected and Automated Vehicles. S Liu. University of California Riverside Dissertations. 2021. link
Impact of Deep RL-based Traffic Signal Control on Air Quality. A Haydari, M Zhang, CN Chuah. Vehicular Technology Conference. 2021. link
Application of deep reinforcement learning in traffic signal control: An overview and impact of open traffic data. M Gregurić, M Vujić, C Alexopoulos, M Miletić. Applied Sciences. 2020. link
A Traffic Light Dynamic Control Algorithm with Deep Reinforcement Learning Based on GNN Prediction. X Hu, C Zhao, G Wang. arXiv preprint. 2020. link
Adaptive Coordination Offsets for Signalized Arterial Intersections using Deep Reinforcement Learning. KA Diaz, D Dailisan, U Sharaf, C Santos, Q Gan. arXiv preprint. 2020. link
Adaptive Traffic Control with Deep Reinforcement Learning: Towards State-of-the-art and Beyond. S Alemzadeh, R Moslemi, R Sharma. arXiv preprint. 2020. link
Assessment of Reward Functions in Reinforcement Learning for Multi-Modal Urban Traffic Control under Real-World limitations. A Cabrejas-Egea, C Connaughton. arXiv preprint. 2020. link
Pdlight: a deep reinforcement learning traffic light control algorithm with pressure and dynamic light duration. C Zhao, X Hu, G Wang. arXiv preprint. 2020. link
Deep reinforcement learning for traffic signal control under disturbances: A case study on Sunway city, Malaysia. F Rasheed, KLA Yau, YC Low. Future Generation Computer Systems. 2020. link
Learning Multi-Agent Communication with Policy Fingerprints for Adaptive Traffic Signal Control. Y Zhao, G Xu, Y Duy, M Fangz. IEEE 16th International Conference on Automation Science and Engineering. 2020. link
A Novel Approach to Coordinating Green Wave System with Adaptation Evolutionary Strategy. Y Zheng, R Guo, D Ma, Z Zhao, X Li. IEEE Access. 2020. link
Cooperative Control for Multi-Intersection Traffic Signal Based on Deep Reinforcement Learning and Imitation Learning. Y Huo, Q Tao, J Hu. IEEE Access. 2020. link
Optimizing transportation dynamics at a city-scale using a reinforcement learning framework. L Khaidem, M Luca, F Yang, A Anand, B Lepri. IEEE Access. 2020. link
PlanLight: Learning to Optimize Traffic Signal Control With Planning and Iterative Policy Improvement. H Zhang, M Kafouros, Y Yu. IEEE Access. 2020. link
Reducing congestion in an intelligent traffic system with collaborative and adaptive signaling on the edge. A Jaleel, MA Hassan, T Mahmood, MU Ghani. IEEE Access. 2020. link
A Cooperative Multiagent System for Traffic Signal Control Using Game Theory and Reinforcement Learning. M Abdoos. IEEE Intelligent Transportation Systems Magazine. 2020. link
Deep reinforcement learning based traffic signal optimization for multiple intersections in ITS. A Paul, S Mitra. IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS). 2020. link
Assessment of reward functions for reinforcement learning traffic signal control under real-world limitations. AC Egea, S Howell, M Knutins. IEEE International Conference on Systems, Man, and Cybernetics. 2020. link
Optimised traffic light management through reinforcement learning: Traffic state agnostic agent vs. holistic agent with current V2I traffic state knowledge. JVS Busch, V Latzko, M Reisslein. IEEE Open Journal of Intelligent Transportation Systems . 2020. link
Large-scale traffic signal control using a novel multiagent reinforcement learning. X Wang, L Ke, Z Qiao, X Chai. IEEE Transactions on Cybernetics. 2020. link
STMARL: A spatio-temporal multi-agent reinforcement learning approach for cooperative traffic light control. Y Wang, T Xu, X Niu, C Tan, E Chen. IEEE Transactions on Mobile Computing . 2020. link
Multi-agent deep reinforcement learning for urban traffic light control in vehicular networks. T Wu, P Zhou, K Liu, Y Yuan, X Wang. IEEE Transactions on Vehicular Technology. 2020. link
Analysis of Intersection Traffic Light Management System in Mandalay City. EE Moel, TM Wynn, MZ Oo. International Conference on Advanced Information Technologies. 2020. link
Vision-Based Adaptive Traffic Light Controller for Single Intersection. M Sutharsan, S Rajakaruna. International Conference on Information Technology Research. 2020. link
Iedqn: Information exchange dqn with a centralized coordinator for traffic signal control. D Xie, Z Wang, C Chen, D Dong. International Joint Conference on Neural Networks. 2020. link
State complexity reduction in reinforcement learning based adaptive traffic signal control. M Miletić, K Kušić, M Gregurić. International Symposium ELMAR. 2020. link
Efficiency and equity are both essential: A generalized traffic signal controller with deep reinforcement learning. S Yan, J Zhang, D Büscher. IROS. 2020. link
Adaptive traffic signal control model on intersections based on deep reinforcement learning. D Li, J Wu, M Xu, Z Wang, K Hu. Journal of Advanced Transportation. 2020. link
Internet of Thing Based Smart Traffic Control Signal Using Solar Energy. V Kalpana, S Shanthi, A Britto. Journal of Computational and Theoretical Nanoscience. 2020. link
Network-wide traffic signal control based on the discovery of critical nodes and deep reinforcement learning. M Xu, J Wu, L Huang, R Zhou, T Wang. Journal of Intelligent Transportation Systems . 2020. link
An edge based multi-agent auto communication method for traffic light control. Q Wu, J Wu, J Shen, B Yong, Q Zhou. Sensors. 2020. link
Intelligent intersection control for delay optimization: Using meta-heuristic search algorithms. A Jamal, M Tauhidur Rahman, HM Al-Ahmadi, I Ullah. Sustainability. 2020. link
Online traffic signal control through sample-based constrained optimization. S Dhamija, A Gon, P Varakantham. the International Conference on Automated Planning and Scheduling. 2020. link
Improving Traffic Safety and Efficiency by Adaptive Signal Control Systems Based on Deep Reinforcement Learning. Y Gong. University of Central Florida Libraries. 2020. link
Control of traffic light timing using decentralized deep reinforcement learning. H Maske, T Chu, U Kalabić. World Congress of the International Federation of Automatic Control. 2020. link
Traffic signal control using deep reinforcement learning with multiple resources of rewards. D Zhong, A Boukerche. ACM International Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, & Ubiquitous Networks. 2019. link
Intersection signal timing optimization considering the travel safety of the elderly. C Ma, P Liu. Advances in Mechanical Engineering. 2019. link
Fitness landscapes analysis and adaptive algorithms design for traffic lights optimization on SIALAC benchmark. F Leprêtre, C Fonlupt, S Verel, V Marion, R Armas. Applied Soft Computing. 2019. link
Diagnosing reinforcement learning for traffic signal control. G Zheng, X Zang, N Xu, H Wei, Z Yu, V Gayah. arXiv preprint. 2019. link
ES-CTC: A deep neuroevolution model for cooperative intelligent freeway traffic control. Y Wu, H Tan, Z Jiang, B Ran. arXiv preprint. 2019. link
Integrating independent and centralized multi-agent reinforcement learning for traffic signal network optimization. Z Zhang, J Yang, H Zha. arXiv preprint. 2019. link
Learning an interpretable traffic signal control policy. J Ault, JP Hanna, G Sharon. arXiv preprint. 2019. link
Deep reinforcement learning for adaptive traffic signal control. KL Tan, S Poddar, S Sarkar. Dynamic Systems and Control Conference. 2019. link
A bilevel approach to enhance prefixed traffic signal optimization. R GarcÃa-Ródenas, ML López-GarcÃa. Engineering Applications of Artificial Intelligence. 2019. link
Deep reinforcement learning-based traffic signal control using high-resolution event-based data. S Wang, X Xie, K Huang, J Zeng, Z Cai. Entropy. 2019. link
Cooperative deep Q-learning with Q-value transfer for multi-intersection signal control. H Ge, Y Song, C Wu, J Ren, G Tan. IEEE Access. 2019. link
Cooperative deep reinforcement learning for large-scale traffic grid signal control. T Tan, F Bao, Y Deng, A Jin, Q Dai. IEEE Transactions on Cybernetics . 2019. link
A deep reinforcement learning network for traffic light cycle control. X Liang, X Du, G Wang, Z Han. IEEE Transactions on Vehicular Technology. 2019. link
Optimization of vehicle delay and drivers' unhappiness at a signalized network: a multi-objective approach. Y Zhang, Y Zhang, R Su. International Conference on Control and Automation. 2019. link
Road Model Design Based on Reward Function in Traffic Light Control. T Wu, F Kong, Z Fan. International Conference on Control, Automation and Robotics. 2019. link
Road traffic demand estimation and traffic signal control. D Kurmankhojayev, G Tolebi. International Conference on Engineering and MIS. 2019. link
Targeted knowledge transfer for learning traffic signal plans. N Xu, G Zheng, K Xu, Y Zhu, Z Li. PAKDD. 2019. link
Cooperative traffic signal control with traffic flow prediction in multi-intersection. D Kim, O Jeong. Sensors. 2019. link
Developing adaptive traffic signal control by actor–critic and direct exploration methods. M Aslani, MS Mesgari, S Seipel. the Institution of Civil Engineers. 2019. link
Decentralized network level adaptive signal control by multi-agent deep reinforcement learning. Y Gong, M Abdel-Aty, Q Cai, MS Rahman. Transportation Research Interdisciplinary Perspectives. 2019. link
A Deep Reinforcement Learning Approach to Adaptive Traffic Lights Management.. A Vidali, L Crociani, G Vizzari, S Bandini. Workshop "From Objects to Agents". 2019. link
Deep reinforcement learning for intelligent transportation systems. XY Liu, Z Ding, S Borst, A Walid. arXiv preprint. 2018. link
Distributed traffic light control at uncoupled intersections with real-world topology by deep reinforcement learning. M Schutera, N Goby, S Smolarek, M Reischl. arXiv preprint. 2018. link
Deep reinforcement learning for autonomous traffic light control. D Garg, M Chli, G Vogiatzis. IEEE International Conference on Intelligent Transportation Engineering. 2018. link
A hybrid particle swarm optimization and tabu search algorithm for adaptive traffic signal timing optimization. MA Chentoufi, R Ellaia. IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD). 2018. link
Smart traffic light system using machine learning. MB Natafgi, M Osman, AS Haidar. IEEE International Multidisciplinary Conference on Engineering Technology. 2018. link
Multiobjective optimization model of intersection signal timing considering emissions based on field data: A case study of Beijing. W Kou, X Chen, L Yu, H Gong. Journal of the Air & Waste Management Association. 2018. link
Adaptive traffic signal control: Deep reinforcement learning algorithm with experience replay and target network. J Gao, Y Shen, J Liu, M Ito, N Shiratori. arXiv preprint. 2017. link
An experimental review of reinforcement learning algorithms for adaptive traffic signal control. P Mannion, J Duggan, E Howley. Autonomic Road Transport Support Systems . 2016. link
Optimal control for region of the city traffic signal based on selective particle swarm optimization algorithm. Z Yong, W Peng. International Conference on Intelligent Transportation, Big Data and Smart City. 2015. link
Novel traffic signal timing adjustment strategy based on genetic algorithm. HY Tung, WC Ma, TL Yu. IEEE Congress on Evolutionary Computation. 2014. link
Urban area traffic signal timing optimization based on Sa-PSO. C Dong, S Huang, X Liu. International Conference on Artificial Intelligence and Computational Intelligence. 2010. link
Ipdalight: Intensity-and phase duration-aware traffic signal control based on reinforcement learning. W Zhao, Y Ye, J Ding. Journal of Systems Architecture. Journal of Systems Architecture. 2022. link
Hybrid Prediction-Based Approach for Traffic Signal Control Problem. AA Agafonov, VV Myasnikov. Optical Memory and Neural Networks. 2022. link
Comprehensive analysis of reinforcement learning methods and parameters for adaptive traffic signal control. S El-Tantawy, B Abdulhai. TRB. 2011. link
Network-aware Multi-agent Reinforcement Learning for Adaptive Navigation of Vehicles in a Dynamic Road Network. F Arasteh. York University Libraries. 2022. link
Empirical study and analysis of the impact of traffic flow control at road intersections on vehicle energy consumption. D Zhong, P Sun, A Boukerche. ACM Symposium on Mobility Management and Wireless Access. 2020. link
A review of cooperative multi-agent deep reinforcement learning. A OroojlooyJadid, D Hajinezhad. arXiv preprint. 2019. link
Real-time Cooperative Vehicle Coordination at Unsignalized Road Intersections. J Luo, T Zhang, R Hao, D Li, C Chen, Z Na. arXiv preprint arXiv .... 2022. link
Smarts: Scalable multi-agent reinforcement learning training school for autonomous driving. M Zhou, J Luo, J Villella, Y Yang, D Rusu. arXiv preprint arXiv .... 2020. link
Differential variable speed limits control for freeway recurrent bottlenecks via deep reinforcement learning. Y Wu, H Tan, B Ran. arXiv preprint arXiv:1810.10952. 2018. link
Optimizing online matching for ride-sourcing services with multi-agent deep reinforcement learning. J Ke, F Xiao, H Yang, J Ye. arXiv preprint arXiv:1902.06228. 2019. link
Multi-agent reinforcement learning for dynamic routing games: A unified paradigm. Z Shou, X Di. arXiv preprint arXiv:2011.10915. 2020. link
Learning Eco-Driving Strategies at Signalized Intersections. V Jayawardana, C Wu. arXiv preprint arXiv:2204.12561. 2022. link
Intelligent traffic management systems for next generation IoV in smart city scenario. V Vijayaraghavan, J Rian Leevinson. Connected Vehicles in the Internet of Things . 2020. link
Evaluating semi-cooperative Nash/Stackelberg Q-learning for traffic routes plan in a single intersection. J Guo, I Harmati. Control Engineering Practice. 2020. link
Effects of Smart Traffic Signal Control on Air Quality. Front. Sustain. P Fazzini, M Torre, V Rizza, F Petracchini. Frontiers in Sustainable Cities. 2022. link
Flow: A modular learning framework for mixed autonomy traffic. C Wu, AR Kreidieh, K Parvate. IEEE Transactions on Robotics . 2021. link
Traffic Management of Urban Network by Bi-Level Optimization. K Stoilova, T Stoilov, K Pavlova. Journal Information Technologies and Control. 2019. link
Cooperative multi-agent reinforcement learning in express system. Y Li, Y Zheng, Q Yang. KDD. 2020. link
Efficient and effective express via contextual cooperative reinforcement learning. Y Li, Y Zheng, Q Yang. KDD. 2019. link
Spatio-temporal capsule-based reinforcement learning for mobility-on-demand network coordination. S He, KG Shin. TheWebConf. 2019. link
Integrated Traffic Control for Freeway Recurrent Bottleneck Based on Deep Reinforcement Learning. C Wang, Y Xu, J Zhang, B Ran. TITS. 2022. link
Learning to delay in ride-sourcing systems: a multi-agent deep reinforcement learning framework. KE Jintao, H Yang, J Ye. TKDE. 2020. link
Differential variable speed limits control for freeway recurrent bottlenecks via deep actor-critic algorithm. Y Wu, H Tan, L Qin, B Ran. TR-C. 2020. link
Multi-vehicle routing problems with soft time windows: A multi-agent reinforcement learning approach. K Zhang, F He, Z Zhang, X Lin, M Li. TR-C. 2020. link
Intelligent traffic analytics: from monitoring to controlling. S Wang, Y Shen, Z Bao, X Qin. WSDM. 2019. link
This is a collection of research papers for Traffic Signal Control with RL. And the repository will be continuously updated to track the frontier of RL-based traffic signal control.
Welcome to follow and star!
There are contributors to this paper collection, we will continue to update it.
If you find LibSignal useful for your research or development, please cite our paper. Mei, H., Lei, X., Da, L. et al. Libsignal: an open library for traffic signal control. Mach Learn (2023). https://doi.org/10.1007/s10994-023-06412-y
@article{mei2023libsignal,
title={Libsignal: an open library for traffic signal control},
author={Mei, Hao and Lei, Xiaoliang and Da, Longchao and Shi, Bin and Wei, Hua},
journal={Machine Learning},
pages={1--37},
year={2023},
publisher={Springer}
}
In the paper collection, we collected RL-based traffic signal control papers published in the recent years (2016-2021) on 8 top conferences and journals, namely, NeurIPS, AAAI, AAMAS, KDD, CIKM, IEEE TITS, ITSC, TR-B and their workshop papers. In addition, the surveys since 2018 and representative papers mentioned in the surveys are also included. We will continue to update the collection.
Graph Neural Networks for Intelligent Transportation Systems: A Survey. S Rahmani, A Baghbani, et, al. IEEE Transactions on Intelligent Transportation Systems. 2023. link
Deep Reinforcement Learning Based Traffic Signal Control: A Comparative Analysis. C Wu, I Kim, et, al. 2023. link
Reinforcement learning in urban network traffic signal control: A systematic literature review. M Noaeen, A Naik, L Goodman, J Crebo, et, al.. 2022. link
The Real Deal: A Review of Challenges and Opportunities in Moving Reinforcement Learning-Based Traffic Signal Control Systems Towards Reality. R Chen, F Fang, N Sadeh. 2022. link
A review of reinforcement learning applications in adaptive traffic signal control. M Miletić, E Ivanjko, et, al. IET Intelligent Transportation System. 2022. link
Traffic Signal Control Methods: Current Status, Challenges, and Emerging Trends. I Tomar, S Indu, N Pandey. Data Analytics and Management. 2022. link
Reinforcement learning in urban network traffic signal control: A systematic literature review. M Noaeen, A Naik, L Goodman, J Crebo, T Abrar. Expert Systems with Applications. 2022. link
A Comparison of Deep Reinforcement Learning Models for Isolated Traffic Signal Control. F Mao, Z Li, L Li. IEEE Intelligent Transportation Systems Magazine. 2022. link
A Comparative Study of Algorithms for Intelligent Traffic Signal Control. H Chaudhuri, V Masti, V Veerendranath. Machine Learning and Autonomous Systems. 2022. link
Recent advances in reinforcement learning for traffic signal control: A survey of models and evaluation. H Wei, G Zheng, V Gayah, Z Li. ACM SIGKDD Explorations Newsletter. 2021. link
A Survey on Deep Reinforcement Learning for Traffic Signal Control. W Miao, L Li, Z Wang. Chinese Control and Decision Conference. 2021. link
Comparative Evaluation of Road Traffic Simulators based on Modeler's Specifications: An Application to Intermodal Mobility Behaviors.. AO Diallo, G Lozenguez, A Doniec, R Mandiau. International Conference on Agents and Artificial Intelligence . 2021. link
Deep reinforcement learning in transportation research: A review. NP Farazi, B Zou, T Ahamed, L Barua. Transportation Research Interdisciplinary Perspectives. 2021. link
Reinforcement learning for traffic signal control: comparison with commercial systems. A Cabrejas-Egea, R Zhang, N Walton. Transportation research procedia. 2021. link
Decision-making at unsignalized intersection for autonomous vehicles: Left-turn maneuver with deep reinforcement learning. T Liu, X Mu, B Huang, X Tang, F Zhao, X Wang. arXiv preprint arXiv .... 2020. link
Deep reinforcement learning and transportation research: A comprehensive review. NP Farazi, T Ahamed, L Barua, B Zou. arXiv preprint arXiv:2010.06187. 2020. link
State-of-art review of traffic signal control methods: challenges and opportunities. SSSM Qadri, MA Gökçe, E Öner. European transport research review. 2020. link
Deep reinforcement learning for traffic signal control: A review. F Rasheed, KLA Yau, RM Noor, C Wu, YC Low. IEEE Access. 2020. link
A review on swarm intelligence and evolutionary algorithms for solving the traffic signal control problem. PW Shaikh, M El-Abd, M Khanafer. IEEE transactions on .... 2020. link
QarSUMO: A Parallel, Congestion-optimized Traffic Simulator. H Chen, K Yang, SG Rizzo, G Vantini, P Taylor. International Conference on Advances in Geographic Information Systems. 2020. link
Assessment of reward functions for reinforcement learning traffic signal control under real-world limitations. AC Egea, S Howell, M Knutins. International Conference on Systems, Man, and Cybernetics. 2020. link
A review on swarm intelligence and evolutionary algorithms for solving the traffic signal control problem. PW Shaikh, M El-Abd, M Khanafer. TITS. 2020. link
Deep reinforcement learning for intelligent transportation systems: A survey. A Haydari, Y Yilmaz. TITS. 2020. link
A survey on traffic signal control methods. H Wei, G Zheng, V Gayah, Z Li. arXiv preprint. 2019. link
Cityflow: A multi-agent reinforcement learning environment for large scale city traffic scenario. H Zhang, S Feng, C Liu, Y Ding, Y Zhu, Z Zhou. TheWebConf. 2019. link
A survey on reinforcement learning models and algorithms for traffic signal control. KLA Yau, J Qadir, HL Khoo, MH Ling. ACM Computing Surveys. 2017. link
Comprehensive analysis of reinforcement learning methods and parameters for adaptive traffic signal control. S El-Tantawy, B Abdulhai. TRB. 2011. link
Attendlight: Universal attention-based reinforcement learning model for traffic signal control. A Oroojlooy, M Nazari. NeurIPS. 2020. link
Learning individually inferred communication for multi-agent cooperation. Z Ding, T Huang, Z Lu. NeurIPS. 2020. link
Safelight: A reinforcement learning method toward collision-free traffic signal control. Liang E, Su Z, Fang C, et al. AAAI. 2022. link
OAM: An Option-Action Reinforcement Learning Framework for Universal Multi-Intersection Control. Liang E, Su Z, Fang C, et al. AAAI. 2022. link
Hierarchically and cooperatively learning traffic signal control. B Xu, Y Wang, Z Wang, H Jia, Z Lu. AAAI. 2021. link
Metalight: Value-based meta-reinforcement learning for traffic signal control. X Zang, H Yao, G Zheng, N Xu, K Xu, Z Li. AAAI. 2020. link
Toward a thousand lights: Decentralized deep reinforcement learning for large-scale traffic signal control. C Chen, H Wei, N Xu, G Zheng, M Yang. AAAI. 2020. link
Feudal multi-agent deep reinforcement learning for traffic signal control. J Ma, F Wu. AAMAS. 2020. link
Reinforcement Learning for Traffic Signal Control Optimization: A Concept for Real-World Implementation. H Meess, J Gerner, D Hein, S Schmidtner. AAMAS. 2022. link
Cooperative max-pressure enhanced traffic signal control. Li L, Li R, Peng Y, et al. CIKM. 2022. link
Meta-Reinforcement Learning for Multiple Traffic Signals Control. Lou Y, Wu J, Ran Y. CIKM. 2022. link
DynSTGAT: Dynamic Spatial-Temporal Graph Attention Network for Traffic Signal Control. L Wu, M Wang, D Wu, J Wu. CIKM. 2021. link
Generalight: Improving environment generalization of traffic signal control via meta reinforcement learning. H Zhang, C Liu, W Zhang, G Zheng, Y Yu. CIKM. 2020. link
Colight: Learning network-level cooperation for traffic signal control. H Wei, N Xu, H Zhang, G Zheng, X Zang. CIKM. 2019. link
Learning phase competition for traffic signal control. G Zheng, Y Xiong, X Zang, J Feng, H Wei. CIKM. 2019. link
Learning traffic signal control from demonstrations. Y Xiong, G Zheng, K Xu, Z Li. CIKM. 2019. link
CoTV: Cooperative Control for Traffic Light Signals and Connected Autonomous Vehicles Using Deep Reinforcement Learning. Guo J, Cheng L, Wang S. TITS. 2023. link
DeepGAL: Intelligent Vehicle Control for Traffic Congestion Alleviation at Intersections. Cao M, Li V O K, Shuai Q. TITS. 2023. link
Real-Time Cooperative Vehicle Coordination at Unsignalized Road Intersections. Luo J, Zhang T, Hao R, et al. TITS. 2023. link
A gain with no pain: Exploring intelligent traffic signal control for emergency vehicles. Cao M, Li V O K, Shuai Q. TITS. 2023. link
Network-wide traffic signal control using bilinear system modeling and adaptive optimization. Wang H, Zhu M, Hong W, et al. TITS. 2022. link
Mastering arterial traffic signal control with multi-agent attention-based soft actor-critic model. Mao F, Li Z, Lin Y, et al. TITS. 2022. link
Distributed Signal Control of Arterial Corridors Using Multi-Agent Deep Reinforcement Learning. Zhang W, Yan C, Li X, et al. TITS. 2022. link
Network-Level Traffic Signal Cooperation: A Higher-Order Conflict Graph Approach. Li W, Wang B, Khattak Z H, et al. TITS. 2022. link
PV-TSC: Learning to control traffic signals for pedestrian and vehicle traffic in 6G era. Xu K, Huang J, Kong L, et al. TITS. 2022. link
A Gain With No Pain: Exploring Intelligent Traffic Signal Control for Emergency Vehicles. M Cao, VOK Li, Q Shuai. TITS. 2022. link
PV-TSC: Learning to Control Traffic Signals for Pedestrian and Vehicle Traffic in 6G Era. K Xu, J Huang, L Kong, J Yu. TITS. 2022. link
Data augmented deep behavioral cloning for urban traffic control operations under a parallel learning framework. X Li, P Ye, J Jin, F Zhu, FY Wang. TITS. 2021. link
IG-RL: Inductive graph reinforcement learning for massive-scale traffic signal control. FX Devailly, D Larocque. TITS. 2021. link
Traffic signal control with reinforcement learning based on region-aware cooperative strategy. M Wang, L Wu, J Li, L He. TITS. 2021. link
Fuzzy inference enabled deep reinforcement learning-based traffic light control for intelligent transportation system. N Kumar, SS Rahman, N Dhakad. TITS. 2020. link
Optimizing signal timing control for large urban traffic networks using an adaptive linear quadratic regulator control strategy. H Wang, M Zhu, W Hong, C Wang. TITS. 2020. link
Multi-agent deep reinforcement learning for large-scale traffic signal control. T Chu, J Wang, L Codecà , Z Li. TITS. 2019. link
Meta-heuristics for bi-objective urban traffic light scheduling problems. K Gao, Y Zhang, Y Zhang, R Su. TITS. 2018. link
Reinforcement learning with function approximation for traffic signal control. LA Prashanth, S Bhatnagar. TITS. 2010. link
QueueLearner: A Knowledge-Combined Reinforcement Learning to Understand Queuing Evolution in Isolated Traffic Signal Control. Han T, Oguchi T, Lyu S. ITSC. 2022. link
A Hierarchical Spatio-Temporal Cooperative Reinforcement Learning Approach for Traffic Signal Control. Li M, Hu Z, Huang H, et al. ITSC. 2022. link
A Spatial-Temporal Deep Reinforcement Learning Model for Large-Scale Centralized Traffic Signal Control. Yi C, Wu J, Ren Y, et al. ITSC. 2022. link
A Deep Reinforcement Learning Framework with Memory Network to Coordinate Traffic Signal Control. Kong A Y, Lu B X, Yang C Z, et al. ITSC. 2022. link
Safe and Psychologically Pleasant Traffic Signal Control with Reinforcement Learning using Action Masking. Müller A, Sabatelli M. ITSC. 2022. link
Meta-Reinforcement Learning for Centralized Multiple Intersections Traffic Signal Control. Ren Y, Wu J, Yi C, et al. ITSC. 2022. link
A deep reinforcement learning approach for fair traffic signal control. M Raeis, A Leon-Garcia. ITSC. 2021. link
An ontology-based intelligent traffic signal control model. S Ghanadbashi, F Golpayegani. ITSC. 2021. link
Designing Reinforcement Learning Agents for Traffic Signal Control with the Right Goals: a Time-Loss based Approach. M D'Almeida, A Paes, D Mossé. ITSC. 2021. link
A deep on-policy learning agent for traffic signal control of multiple intersections. CC Yen, D Ghosal, M Zhang. ITSC. 2020. link
A reinforcement learning approach for intelligent traffic signal control at urban intersections. M Guo, P Wang, CY Chan. ITSC. 2019. link
Reinforcement learning with explainability for traffic signal control. SG Rizzo, G Vantini, S Chawla. ITSC. 2019. link
Traffic Signal Control for Isolated Intersection Based on Coordination Game and Pareto Efficiency. Y Zhao, Y Liang, J Hu, Z Zhang. ITSC. 2019. link
Training reinforcement learning agent for traffic signal control under different traffic conditions. J Zeng, J Hu, Y Zhang. ITSC. 2019. link
Deep learning vs. discrete reinforcement learning for adaptive traffic signal control. SMA Shabestary, B Abdulhai. ITSC. 2018. link
Traffic signal control based on reinforcement learning with graph convolutional neural nets. T Nishi, K Otaki, K Hayakawa. ITSC. 2018. link
Traffic behavior recognition from traffic videos under occlusion condition: a Kalman filter approach. Jiao J, Wang H. TR-C. 2022. link
Intelligent vehicle pedestrian light (IVPL): A deep reinforcement learning approach for traffic signal control. Yazdani M, Sarvi M, Bagloee S A, et al. TR-C. 2022. link
Adaptive Traffic Signal Control for large-scale scenario with Cooperative Group-based Multi-agent reinforcement learning. T Wang, J Cao, A Hussain. TR-C. 2021. link
DRL-TP3: A learning and control framework for signalized intersections with mixed connected automated traffic. Y Guo, J Ma. TR-C. 2021. link
Network-wide traffic signal control optimization using a multi-agent deep reinforcement learning. Z Li, H Yu, G Zhang, S Dong, CZ Xu. TR-C. 2021. link
An equitable traffic signal control scheme at isolated signalized intersections using Connected Vehicle technology. XJ Liang, SI Guler, VV Gayah. TR-C. 2020. link
Reinforcement learning with average cost for adaptive control of traffic lights at intersections. LA Prashanth, S Bhatnagar. ITSC. 2011. link
An efficient deep reinforcement learning model for urban traffic control. Y Lin, X Dai, L Li, FY Wang. ICDM Workshop. 2018. link
Deep reinforcement learning for traffic light optimization. M CoÅŸkun, A Baggag, S Chawla. ICDM Workshop. 2018. link
A reinforcement learning approach with Fourier basis linear function approximation for traffic signal control. T Ziemke, LN Alegre, ALC Bazzan. ECAI Workshop. 2020. link
Coordinated deep reinforcement learners for traffic light control. E Van der Pol, FA Oliehoek. NeurIPS Workshop. 2016. link
Towards Explainable Deep Reinforcement Learning for Traffic Signal Control. LV Schreiber, GO Ramos, ALC Bazzan. ICML Workshop. 2021. link
Multi-agent reinforcement learning for traffic signal control: A cooperative approach. M Kolat, B Kővári, T Bécsi. Sustainability, 2023. link
Distributed agent-based deep reinforcement learning for large scale traffic signal control. Q Wu, J Wu, J Shen, et, al. Knowledge-Based Systems. 2022. link
Intelligent Traffic Signal Phase Distribution System Using Deep Q-Network. H Joo, Y Lim. Applied Sciences. 2022. link
Model Predictive Traffic Control by Bi-Level Optimization. K Stoilova, T Stoilov. Applied Sciences. 2022. link
A Concurrent Switching Model for Traffic Congestion Control. H Rastgoftar, X Liu, JB Jeannin. arXiv preprint. 2022. link
CoTV: Cooperative Control for Traffic Light Signals and Connected Autonomous Vehicles using Deep Reinforcement Learning. J Guo, L Cheng, S Wang. arXiv preprint. 2022. link
Offline Reinforcement Learning for Road Traffic Control. M Kunjir, S Chawla. arXiv preprint. 2022. link
Proximal Policy Optimization Learning based Control of Congested Freeway Traffic. S Mo, J Qi, A Pan. arXiv preprint. 2022. link
Cooperative Traffic Signal Control Through A Counterfactual Multi-Agent Deep Actor Critic Approach. X Song, B Zhou, D Ma. Available at SSRN 40219. 2022. link
Dynamic Traffic Light Control with Reinforcement Learning Based on Gnn Prediction. C Zhao, G Wang. Available at SSRN 40405. 2022. link
Deep Reinforcement Learning for Addressing Disruptions in Traffic Light Control. F Rasheed, KLA Yau, RM Noor. Computers, Materials and Continua. 2022. link
Exploring reward efficacy in traffic management using deep reinforcement learning in intelligent transportation system. A Paul, S Mitra. ETRI Journal. 2022. link
Learning from Oracle Demonstrations–A new approach to develop Autonomous Intersection Management control algorithms based on Multi-Agent Deep .... A Guillen-Perez, MD Cano. IEEE Access. 2022. link
Intelligent Traffic Light Control by Exploring Strategies in an Optimised Space of Deep Q-Learning. J Liu, S Qin, Y Luo, Y Wang. IEEE Transactions on Vehicular Technology. 2022. link
Micro Junction Agent: A Scalable Multi-agent Reinforcement Learning Method for Traffic Control. BK Choi, JSB Choe, J Kim. International Conference on Agents and Artificial Intelligence. 2022. link
Dynamic Weight-based Multi-Objective Reward Architecture for Adaptive Traffic Signal Control System. ARM Jamil, N Nower. International Journal of Intelligent Transportation Systems Research. 2022. link
Centralized and Decentralized Signal Control with Short-Term Origin-Destination Demand for Network Traffic. C Zhang, TZ Qiu, A Kim. Journal of Advanced Transportation. 2022. link
IPDALight: Intensity-and phase duration-aware traffic signal control based on Reinforcement Learning. W Zhao, Y Ye, J Ding, T Wang, T Wei. Journal of Systems Architecture. 2022. link
Distributed agent-based deep reinforcement learning for large scale traffic signal control. Q Wu, J Wu, J Shen, B Du, A Telikani. Knowledge-Based Systems. 2022. link
A fog-based Traffic Light Management Strategy (TLMS) based on fuzzy inference engine. SA Gamel, AI Saleh, HA Ali. Neural Computing and Applications. 2022. link
Information upwards, recommendation downwards: reinforcement learning with hierarchy for traffic signal control. TO Antes, ALC Bazzan, AR Tavares. Procedia Computer Science. 2022. link
Biased pressure: cyclic reinforcement learning model for intelligent traffic signal control. B Ibrokhimov, YJ Kim, S Kang. Sensors. 2022. link
SecureTLC: Secure and Two-level Traffic Signal Control for Intelligent Transportation System. CC Yen. UC Davis Electronic Theses and Dissertations. 2022. link
Attacking Deep Reinforcement Learning-Based Traffic Signal Control Systems with Colluding Vehicles, Qu, Ao, Yihong Tang, and Wei Ma. arXiv preprint arXiv:2111.02845. 2021. link
Traffic Signal Optimization for Multiple Intersections Based on Reinforcement Learning. J Gu, M Lee, C Jun, Y Han, Y Kim, J Kim. Applied Sciences. 2021. link
A Decentralized Reinforcement Learning Framework for Efficient Passage of Emergency Vehicles. H Su, YD Zhong, D Biswadip, A Chakraborty. arXiv preprint. 2021. link
A Methodology for the Development of RL-Based Adaptive Traffic Signal Controllers. GS Varela, PP Santos, A Sardinha, FS Melo. arXiv preprint. 2021. link
Back to Basics: Deep Reinforcement Learning in Traffic Signal Control. S Kanis, L Samson, D Bloembergen. arXiv preprint. 2021. link
DQN Control Solution for KDD Cup 2021 City Brain Challenge. Y Chen, K Chen, K Chen, L Wang. arXiv preprint. 2021. link
EMVLight: A Decentralized Reinforcement Learning Framework for Efficient Passage of Emergency Vehicles. H Su, YD Zhong, B Dey, A Chakraborty. arXiv preprint. 2021. link
Expression is enough: Improving traffic signal control with advanced traffic state representation. L Zhang, Q Wu, J Shen, L Lü, J Wu, B Du. arXiv preprint. 2021. link
Variationally and intrinsically motivated reinforcement learning for decentralized traffic signal control. L Zhu, P Peng, Z Lu, X Wang, Y Tian. arXiv preprint. 2021. link
A deterministic predictive traffic signal control model in intelligent transportation and geoinformation systems. VV Myasnikov, AA Agafonov, AS Yumaganov. Computer Optics. 2021. link
Traffic Signal Control: a Double Q-learning Approach. A Agafonov, V Myasnikov. Conference on Computer Science and Intelligence Systems. 2021. link
Multi-agent Deep Reinforcement Learning with Spatio-Temporal Feature Fusion for Traffic Signal Control. X Du, J Wang, S Chen, Z Liu. ECML-PKDD. 2021. link
Traffic Signal Control System Based on Intelligent Transportation System and Reinforcement Learning. J Hurtado-Gómez, JD Romo, R Salazar-Cabrera. Electronics. 2021. link
Learning scalable multi-agent coordination by spatial differentiation for traffic signal control. J Liu, H Zhang, Z Fu, Y Wang. Engineering Applications of Artificial Intelligence. 2021. link
Intelligent Traffic Signal Control System using Deep Q-network. H Joo, Y Lim. Eurasia Conference on IOT, Communication and Engineering. 2021. link
Hierarchical traffic signal optimization using reinforcement learning and traffic prediction with long-short term memory. M Abdoos, ALC Bazzan. Expert systems with applications. 2021. link
Transfer Learning Method in Reinforcement Learning-based Traffic Signal Control. Z Mao, J Li, N Zheng, K Tei. Global Conference on Consumer Electronics. 2021. link
Probabilistic Graph Neural Networks for Traffic Signal Control. T Zhong, Z Xu, F Zhou. ICASSP. 2021. link
Urban Traffic Light Control Considering Capacity Difference Between Public Bus and Private Vehicles. Z Liu, N Wu, K Gao. IEEE Access. 2021. link
Self-Optimizing Traffic Light Control Using Hybrid Accelerated Extremum Seeking. F Galarza-Jimenez, JI Poveda. IEEE Conference on Decision and Control. 2021. link
Knowledge embedding-assisted multi-exemplar learning particle swarm optimization for traffic signal timing optimization. ZJ Deng, LY Luo, ZH Zhan. IEEE Congress on Evolutionary Computation. 2021. link
TSLib: A Unified Traffic Signal Control Framework Using Deep Reinforcement Learning and Benchmarking. TV Tran, TN Doan, M Sartipi. IEEE International Conference on Big Data (Big Data). 2021. link
Reinforcement Learning-driven Attack on Road Traffic Signal Controllers. NS Arabi, T Halabi, M Zulkernine. IEEE International Conference on Cyber Security and Resilience. 2021. link
A Meta Multi-agent Reinforcement Learning Algorithm for Multi-intersection Traffic Signal Control. S Yang, B Yang. IEEE Intl Conf on Dependable, Autonomic and Secure Computing. 2021. link
Adversarial Attacks and Defense in Deep Reinforcement Learning (DRL)-Based Traffic Signal Controllers. A Haydari, M Zhang, CN Chuah. IEEE Open Journal of Intelligent Transportation Systems . 2021. link
Improving Traffic Signal Control With Joint-Action Reinforcement Learning. JVB Labres, ALC Bazzan. IEEE Symposium Series on Computational Intelligence. 2021. link
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