[1]

Wu J, Qu X. 2022. Intersection control with connected and automated vehicles: a review. Journal of Intelligent and Connected Vehicles 5:260−269

doi: 10.1108/JICV-06-2022-0023
[2]

Florin R, Olariu S. 2015. A survey of vehicular communications for traffic signal optimization. Vehicular Communications 2:70−79

doi: 10.1016/j.vehcom.2015.03.002
[3]

Hamilton A, Waterson B, Cherrett T, Robinson A, Snell I. 2013. The evolution of urban traffic control: changing policy and technology. Transportation Planning and Technology 36:24−43

doi: 10.1080/03081060.2012.745318
[4]

Webster FV. 1958. Traffic signal settings. London, England: Her Majesty's Stationery Office
[5]

Wong CK, Wong SC. 2003. Lane-based optimization of signal timings for isolated junctions. Transportation Research Part B: Methodological 37:63−84

doi: 10.1016/S0191-2615(01)00045-5
[6]

Yin Y. 2008. Robust optimal traffic signal timing. Transportation Research Part B: Methodological 42:911−924

doi: 10.1016/j.trb.2008.03.005
[7]

Yun I, Park BB. 2012. Stochastic optimization for coordinated actuated traffic signal systems. Journal of Transportation Engineering 138:819−829

doi: 10.1061/(ASCE)TE.1943-5436.0000384
[8]

Dai R, Cai P, Wang X, Zhang R. 2023. A computationally efficient and refined signal control method for isolated intersections in a connected vehicle environment. Expert Systems with Applications 234:121073

doi: 10.1016/j.eswa.2023.121073
[9]

Mercader P, Uwayid W, Haddad J. 2020. Max-pressure traffic controller based on travel times: an experimental analysis. Transportation Research Part C: Emerging Technologies 110:275−290

doi: 10.1016/j.trc.2019.10.002
[10]

Abed Al Raheem Magableh A, Almakhadmeh MA, Alsrehin N, Klaib AF. 2020. Smart traffic light management systems: a systematic literature review. Journal International Journal of Technology Diffusion 11:22−47

doi: 10.4018/ijtd.2020070102
[11]

Touhbi S, Babram MA, Nguyen-Huu T, Marilleau N, Hbid ML, et al. 2017. Adaptive traffic signal control: exploring reward definition for reinforcement learning. Procedia Computer Science 109:513−520

doi: 10.1016/j.procs.2017.05.327
[12]

Joo H, Ahmed SH, Lim Y. 2020. Traffic signal control for smart cities using reinforcement learning. Computer Communications 154:324−330

doi: 10.1016/j.comcom.2020.03.005
[13]

Acar B, Sterling M. 2023. Ensuring federated learning reliability for infrastructure-enhanced autonomous driving. Journal of Intelligent and Connected Vehicles 6:125−135

doi: 10.26599/JICV.2023.9210009
[14]

Sun H, Chen C, Liu Q, Zhao J. 2020. Traffic signal control method based on deep reinforement learning. Computer Science 47:169−174
[15]

La P , Bhatnagar S. 2011. Reinforcement learning with function approximation for traffic signal control. IEEE Transactions on Intelligent Transportation Systems 12:412−421

doi: 10.1109/TITS.2010.2091408
[16]

Shabestary SMA, Abdulhai B. 2022. Adaptive traffic signal control with deep reinforcement learning and high dimensional sensory inputs: case study and comprehensive sensitivity analyses. IEEE Transactions on Intelligent Transportation Systems 23:20021−20035

doi: 10.1109/TITS.2022.3179893
[17]

Haddad TA, Hedjazi D, Aouag S. 2022. A deep reinforcement learning-based cooperative approach for multi-intersection traffic signal control. Engineering Applications of Artificial Intelligence 114:105019

doi: 10.1016/j.engappai.2022.105019
[18]

Shabestary SMA, Abdulhai B. 2018. Deep learning vs. discrete reinforcement learning for adaptive traffic signal control. Proc. 2018 21st International Conference on Intelligent Transportation Systems (ITSC), Maui, HI, USA, 2018. US: IEEE. pp. 286–293 doi: 10.1109/ITSC.2018.8569549
[19]

Liang X, Du X, Wang G, Han Z. 2019. A deep reinforcement learning network for traffic light cycle control. IEEE Transactions on Vehicular Technology 68:1243−1253

doi: 10.1109/TVT.2018.2890726
[20]

Nigam A, Srivastava S. 2023. Hybrid deep learning models for traffic stream variables prediction during rainfall. Multimodal Transportation 2:100052

doi: 10.1016/j.multra.2022.100052
[21]

Bouktif S, Cheniki A, Ouni A, El-Sayed H. 2023. Deep reinforcement learning for traffic signal control with consistent state and reward design approach. Knowledge-Based Systems 267:110440

doi: 10.1016/j.knosys.2023.110440
[22]

Liang X, Guler SI, Gayah VV. 2020. An equitable traffic signal control scheme at isolated signalized intersections using Connected Vehicle technology. Transportation Research Part C: Emerging Technologies 110:81−97

doi: 10.1016/j.trc.2019.11.005
[23]

Chu T, Wang J, Codecà L, Li Z. 2020. Multi-agent deep reinforcement learning for large-scale traffic signal control. IEEE Transactions on Intelligent Transportation Systems 21:1086−1095

doi: 10.3390/app15158605
[24]

Aslani M, Mesgari MS, Wiering M. 2017. Adaptive traffic signal control with actor-critic methods in a real-world traffic network with different traffic disruption events. Transportation Research Part C: Emerging Technologies 85:732−52

doi: 10.1016/j.trc.2017.09.020
[25]

Haydari A, Yilmaz Y. 2022. Deep reinforcement learning for intelligent transportation systems: a survey. IEEE Transactions on Intelligent Transportation Systems 23(1):11−32

doi: 10.1109/TITS.2020.3008612
[26]

El-Tantawy S, Abdulhai B. 2010. An agent-based learning towards decentralized and coordinated traffic signal control. Proc. 13th International IEEE Conference on Intelligent Transportation Systems, Funchal, Portugal, 2010. US: IEEE. pp. 665–670 doi: 10.1109/ITSC.2010.5625066
[27]

Mousavi SS, Schukat M, Howley E. 2017. Traffic light control using deep policy-gradient and value-function-based reinforcement learning. IET Intelligent Transport Systems 11:417−423

doi: 10.1049/iet-its.2017.0153
[28]

Khamis MA, Gomaa W. 2013. Enhanced multiagent multi-objective reinforcement learning for urban traffic light control. Proc. 2012 11th International Conference on Machine Learning and Applications, Boca Raton, FL, USA, 2012. US: IEEE. pp. 586–591 doi: 10.1109/ICMLA.2012.108
[29]

Noaeen M, Naik A, Goodman L, Crebo J, Abrar T, et al. 2022. Reinforcement learning in urban network traffic signal control: a systematic literature review. Expert Systems with Applications 199:116830

doi: 10.1016/j.eswa.2022.116830
[30]

Van Hasselt H, Guez A, Silver D. 2016. Deep reinforcement learning with double Q-learning. Proceedings of the AAAI Conference on Artificial Intelligence 30(1):2094−2100

doi: 10.1609/aaai.v30i1.10295
[31]

Mnih V, Kavukcuoglu K, Silver D, Rusu AA, Veness J, et al. 2015. Human-level control through deep reinforcement learning. Nature 518:529−533

doi: 10.1038/nature14236