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Application of reinforcement learning with continuous state space to ramp metering in real-world conditions.

, , and . ITSC, page 1590-1595. IEEE, (2012)

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Assessment of Adaptive Traffic Signal Control Using Hardware in the Loop Simulation., , , , and . ITSC, page 1189-1195. IEEE, (2015)Design of Reinforcement Learning Parameters for Seamless Application of Adaptive Traffic Signal Control., , and . J. Intell. Transp. Syst., 18 (3): 227-245 (2014)Multiagent Reinforcement Learning for Integrated Network of Adaptive Traffic Signal Controllers (MARLIN-ATSC): Methodology and Large-Scale Application on Downtown Toronto., , and . IEEE Trans. Intell. Transp. Syst., 14 (3): 1140-1150 (2013)Application of reinforcement learning with continuous state space to ramp metering in real-world conditions., , and . ITSC, page 1590-1595. IEEE, (2012)Assessing the Potential Impacts of Connected Vehicles: Mobility, Environmental, and Safety Perspectives., , , and . J. Intell. Transp. Syst., 20 (3): 229-243 (2016)Speedup of DTA-Based Simulation of Large Metropolises for Quasi Real-Time ITS Applications., , , , , and . ITSC, page 483-490. IEEE, (2015)Robust Network Design for Roadway Networks: Unifying Framework and Application., , , , and . IEEE Intell. Transport. Syst. Mag., 7 (2): 34-46 (2015)Optimizing the number and locations of freeway roadside equipment units for travel time estimation in a connected vehicle environment., , , and . J. Intell. Transp. Syst., 21 (4): 296-309 (2017)Traffic capacity implications of automated vehicles mixed with regular vehicles., , , and . J. Intell. Transp. Syst., 22 (3): 244-262 (2018)Harnessing the Power of HPC in Simulation and Optimization of Large Transportation Networks: Spatio-Temporal Traffic Management in the Greater Toronto Area., , , , and . IEEE Intell. Transport. Syst. Mag., 10 (1): 95-106 (2018)