The emergence of connected and autonomous vehicles (CAVs) presents increased opportunities to mitigate traffic congestion, improve safety and reduce accidents. Professor Zhong-Ping Jiang, and researchers Leilei Cui and Sayan Chakraborty are applying innovative reinforcement learning control methods to one challenging aspect of CAV control: lane changing in mixed traffic. The team takes a novel approach by reducing the trajectory planning and tracking problem down to the minimization of a cost function that depends on a target way-point in the lane a CAV is targeting.
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Dynamic flow networks are a class of useful models for a variety of engineering systems including transportation systems, production lines and communication networks. This session will introduce its basic concepts, mathematical modeling and control strategies. The application will be illustrated with ramp metering, a typical strategy for freeway management. |
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In the State-of-the-Field event series, C2SMART leverages its consortium of researchers and experts to share a vision of the future of mobility and transportation systems. They'll share advances, opportunities, predictions, |
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