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This paper develops a decentralized reinforcement learning (RL) scheme for multi-intersection adaptive traffic signal control (TSC), called "CVLight", that leverages data collected from connected vehicles (CVs).
An open-source framework for adaptive traffic signal control
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Sumo–simulation of urban mobility: an overview, in: Proceedings of SIMUL 2011, The Third International Conference on Advances in System Simulation, ThinkMind
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Multi-agent reinforcement learning for dynamic routing games: A unified paradigm
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Krajzewicz, D., Erdmann, J., Behrisch, M., Bieker, L., 2012 · 2012
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Traffic signal control with connected vehicles
Goodall, N.J., Smith, B.L., Park, B., 2013 · 2013
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Cumulative travel-time responsive real-time intersection control algorithm in the connected vehicle environment
Lee, J., Park, B., Yun, I., 2013 · 2013
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A survey of traffic control with vehicular communications
Li, L., Wen, D., Yao, D., 2013 · 2013
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Max pressure control of a network of signalized intersections
Varaiya, P., 2013 · 2013
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Microscopic estimation of arterial vehicle positions in a low-penetration-rate connected vehicle environment
Goodall, N.J., Park, B., Smith, B.L., 2014 · 2014
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Kingma, D.P., Ba, J., 2014 · 2014
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Cooperative multi-agent traffic signal control system using fast gradient-descent function approximation for v2i networks, in: 2014 IEEE International Conference on Communications (ICC), IEEE. pp. 2562–2567
Liu, W., Liu, J., Peng, J., Zhu, Z., 2014 · 2014
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A real-time adaptive signal control in a connected vehicle environment
Feng, Y., Head, K.L., Khoshmagham, S., Zamanipour, M., 2015 · 2015
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Long queue estimation for signalized intersections using mobile data
Hao, P., Ban, X., 2015 · 2015
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Delving deep into rectifiers: Surpassing human-level performance on imagenet classification, in: Proceedings of the IEEE international conference on computer vision, pp. 1026–1034
He, K., Zhang, X., Ren, S., Sun, J., 2015 · 2015
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Human-level control through deep reinforcement learning
Mnih, V., Kavukcuoglu, K., Silver, D., Rusu, A.A., Veness, J., Bellemare, M.G., Graves, A., Riedmiller, M., Fidjeland, A.K., Ostrovski, G., et al., 2015 · 2015
Cited alongside, same era.
Queue length estimation using connected vehicle technology for adaptive signal control
Tiaprasert, K., Zhang, Y., Wang, X.B., Zeng, X., 2015 · 2015
Cited alongside, same era.
Interworking of dsrc and cellular network technologies for v2x communications: A survey
Abboud, K., Omar, H.A., Zhuang, W., 2016 · 2016
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Multi-agent deep reinforcement learning for large-scale traffic signal control
Chu, T., Wang, J., Codecà, L., Li, Z., 2019 · 2019
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Decentralized network level adaptive signal control by multi-agent deep reinforcement learning
Gong, Y., Abdel-Aty, M., Cai, Q., Rahman, M.S., 2019 · 2019
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Urban traffic signal control with connected and automated vehicles: A survey
Guo, Q., Li, L., Ban, X.J., 2019 · 2019
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Cooperative schedule-driven intersection control with connected and autonomous vehicles, in: 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE. pp. 1668–1673
Hu, H.C., Smith, S.F., Goldstein, R., 2019 · 2019
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The real-time traffic signal control system for the minimum emission using reinforcement learning in v2x environment
Kim, J., Jung, S., Kim, K., Lee, S., 2019 · 2019
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Next generation 5g wireless networks: A comprehensive survey
Agiwal, M., Roy, A., Saxena, N., 2016 · 2016
Cited alongside, same era.
Connected vehicle–based adaptive signal control and applications
Feng, Y., Zamanipour, M., Head, K.L., Khoshmagham, S., 2016 · 2016
Cited alongside, same era.
Traffic signal timing optimization incorporating individual vehicle fuel consumption characteristics under connected vehicles environment, in: 2016 International Conference on Connected Vehicles and Expo (ICCVE), IEEE. pp. 13–18
Li, W., Ban, X.J., Wang, J., 2016 · 2016
Cited alongside, same era.
Coordinated deep reinforcement learners for traffic light control
Van der Pol, E., Oliehoek, F.A., 2016 · 2016
Cited alongside, same era.
Adaptive coordination based on connected vehicle technology
Beak, B., Head, K.L., Feng, Y., 2017 · 2017
Cited alongside, same era.
Distributed cooperative reinforcement learning-based traffic signal control that integrates v2x networks’ dynamic clustering
Liu, W., Qin, G., He, Y., Jiang, F., 2017 · 2017
Cited alongside, same era.
Estimating traffic volumes for signalized intersections using connected vehicle data
Zheng, J., Liu, H.X., 2017 · 2017
Cited alongside, same era.
Cooperative traffic signal and perimeter control in semi-connected urban-street networks
Mohebifard, R., Al Islam, S.B., Hajbabaie, A., 2019 · 2019
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Presslight: Learning max pressure control to coordinate traffic signals in arterial network, in: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, pp. 1290–1298
Wei, H., Chen, C., Zheng, G., Wu, K., Gayah, V., Xu, K., Li, Z., 2019 · 2019
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Cooperative traffic signal control using multi-step return and off-policy asynchronous advantage actor-critic graph algorithm
Yang, S., Yang, B., Wong, H.S., Kang, Z., 2019 · 2019
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A real-time network-level traffic signal control methodology with partial connected vehicle information
Al Islam, S.B., Hajbabaie, A., Aziz, H.A., 2020 · 2020
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Toward a thousand lights: Decentralized deep reinforcement learning for large-scale traffic signal control, in: Proceeding of the Thirty-fourth AAAI Conference on Artificial Intelligence (AAAI’20). New York, NY
Chacha Chen, H.W., Xu, N., Zheng, G., Yang, M., Xiong, Y., Xu, K., Li, Z., 2020 · 2020
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A comprehensive survey on internet of things (iot) toward 5g wireless systems
Chettri, L., Bera, R., 2020 · 2020
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Connected vehicle-based traffic signal coordination
Li, W., Ban, X., 2020 · 2020
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Reward design for driver repositioning using multi-agent reinforcement learning
Shou, Z., Di, X., 2020 · 2020
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Multi-agent deep reinforcement learning for urban traffic light control in vehicular networks
Wu, T., Zhou, P., Liu, K., Yuan, Y., Wang, X., Huang, H., Wu, D.O., 2020 · 2020
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Efficiency and equity are both essential: A generalized traffic signal controller with deep reinforcement learning, in: 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE. pp. 5526–5533
Yan, S., Zhang, J., Büscher, D., Burgard, W., · 2020
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Using reinforcement learning with partial vehicle detection for intelligent traffic signal control
Zhang, R., Ishikawa, A., Wang, W., Striner, B., Tonguz, O.K., 2020 · 2020
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A survey on autonomous vehicle control in the era of mixed-autonomy: From physics-based to AI-guided driving policy learning
Di, X., Shi, R., 2021 · 2021
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The connected vehicle: Big data, big opportunities
SAS, 2015 · 2021
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Connected vehicle
USDOT, 2019 · 2021
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Connected vehicle as a mobile sensor for real time queue length at signalized intersections
Gao, K., Han, F., Dong, P., Xiong, N., Du, R., 2019 · 2059
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