Area of research
Control and Systems Engineering · Transportation
Research interest
Research focused on Artificial intelligence and Traffic flow (computer networking), with related work in Deep learning, Trajectory, Diesel fuel. Notable publications include 'Capturing Car-Following Behaviors by Deep Learning', 'Trajectory data-based traffic flow studies: A revisit', and 'Parallel testing of vehicle intelligence via virtual-real interaction'.
Unravelling the Oxygen Evolution Mechanism of Lithium‐Rich Antifluorite Prelithiation Agent Based on Anionic Oxidation
Trial of Pegcetacoplan in C3 Glomerulopathy and Immune-Complex MPGN
Study on gradient structure and surface strengthening mechanism of LPBF 2099 Al-Li alloy induced by ultrasonic surface rolling
A Survey on Large Language Model-Powered Autonomous Driving
VALIANT: A Randomized, Multicenter, Double-Blind, Placebo (PBO)-Controlled, Phase 3 Trial of Pegcetacoplan for Patients with Native or Post-transplant Recurrent Glomerulopathy (C3G) or Primary Immune Complex Membranoproliferative Glomerulonephritis (IC-MPGN)
Clinical Safety and Efficacy of Pegcetacoplan in a Phase 2 Study of Patients with C3 Glomerulopathy and Other Complement-Mediated Glomerular Diseases
ChatGPT as Your Vehicle Co-Pilot: An Initial Attempt
Parallel Vision for Long-Tail Regularization: Initial Results From IVFC Autonomous Driving Testing
A General Framework for Decentralized Safe Optimal Control of Connected and Automated Vehicles in Multi-Lane Signal-Free Intersections
Reducing traffic violations in the online food delivery industry—A case study in Xi'an City, China
Automated vehicle-involved traffic flow studies: A survey of assumptions, models, speculations, and perspectives
Comparison of Cooperative Driving Strategies for CAVs at Signal-Free Intersections
A bi-level cooperative operation approach for AGV based automated valet parking
Density-Aware Haze Image Synthesis by Self-Supervised Content-Style Disentanglement
Trajectory data-based traffic flow studies: A revisit
A bi-level cooperative driving strategy allowing lane changes
Parallel testing of vehicle intelligence via virtual-real interaction
Long memory is important: A test study on deep-learning based car-following model
Capturing Car-Following Behaviors by Deep Learning
Numerical investigation on the effect of reactivity gradient in an RCCI engine fueled with gasoline and diesel