Vehicle Dynamics

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Overview

Vehicle-dynamics research models how forces and motion interact, helping predict behavior and keep cars, trucks, motorcycles, and mobile robots safe and controllable. Approaches range from physics-based bicycle, tire, and multibody models to learned or hybrid methods such as Gaussian processes, Koopman models, and neural state-space models, often informed by system identification and onboard sensors. These models support model predictive control, stability and safety constraints, and reinforcement learning in settings from autonomous racing to rough terrain, with evaluation in simulation and on real vehicles. A central challenge is ensuring that accurate predictions also produce reliable closed-loop control across changing surfaces, speeds, and vehicle configurations without sacrificing safety for performance.

Latest papers

CardsList

77 papers11 papers in the last four weeks, down 21% on the four weeks before. 0.1% of all new papers.

  1. On Common Misconceptions in Classical Vehicle Dynamics

    Apr 14, 2026Massimo GuiggianiVehicle DynamicsDynamical Systems

    Department of Civil and Industrial Engineering, Universit`a di Pisa, Italy

  2. MVAdapt: Zero-Shot Multi-Vehicle Adaptation for End-to-End Autonomous Driving

    Apr 13, 2026Haesung Oh, Jaeheung ParkEnd-to-End Autonomous DrivingVehicle Dynamics

    Interdisciplinary Program in AI, Seoul National University, South Korea · Faculty of the Interdisciplinary Program in AI, Seoul National University, South Korea

  3. RAGE-XY: RADAR-Aided Longitudinal and Lateral Forces Estimation For Autonomous Race Cars

    Apr 9, 2026Davide Malvezzi, Nicola Musiu, Eugenio Mascaro +2Vehicle DynamicsAutonomous Racing

  4. PD-SOVNet: A Physics-Driven Second-Order Vibration Operator Network for Estimating Wheel Polygonal Roughness from Axle-Box Vibrations

    Apr 8, 2026Xiancheng Wang, Lin Wang, Rui Wang +5Structural Health MonitoringPhysics-Informed ML

    School of Ocean Engineering, Harbin Institute of Technology, West Wenhua Road, Weihai, 264209, Shandong, China · Technical Center, Bogie Development Department, CRRC Qingdao Sifang Locomotive and Rolling Stock Co., Ltd, Jinhong East Road, Qingdao, 266111, Shandong, China

  5. ReinVBC: A Model-based Reinforcement Learning Approach to Vehicle Braking Controller

    Apr 6, 2026Haoxin Lin, Junjie Zhou, Daheng Xu +1RL ControlModel-Based RL

    National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China · School of Artificial Intelligence, Nanjing University, Nanjing, China · Polixir Technologies, Nanjing, China

  6. RAGE: A Tightly Coupled Radar-Aided Grip Estimator For Autonomous Race Cars

    Apr 3, 2026Davide Malvezzi, Nicola Musiu, Eugenio Mascaro +2Vehicle DynamicsAutonomous Racing

  7. Koopman Operator Framework for Modeling and Control of Off-Road Vehicle on Deformable Terrain

    Mar 30, 2026Kartik Loya, Phanindra TallapragadaTerrain-Aware Robot LocomotionVehicle Dynamics

    Department of Mechanical Engineering, Clemson University, Clemson, SC 29607 USA

  8. High-Speed, All-Terrain Autonomy: Ensuring Safety at the Limits of Mobility

    Mar 20, 2026James R. Baxter, Bogdan I. Epureanu, Paramsothy Jayakumar +1Safe Motion PlanningOff-Road Robot Navigation

    Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI · U.S. Army Ground Vehicle Systems Center, Warren, MI

  9. Physics-informed Deep Mixture-of-Koopmans Vehicle Dynamics Model with Dual-branch Encoder for Distributed Electric-drive Trucks

    Mar 18, 2026Jinyu Miao, Pu Zhang, Rujun Yan +8Vehicle DynamicsKoopman Operator Learning

    School of Vehicle and Mobility, and State Key Laboratory of Intelligent Green Vehicle and Mobility, Tsinghua University, Beijing, China · KargoBot Inc., Beijing, China

  10. LPV-MPC for Lateral Control in Full-Scale Autonomous Racing

    Mar 14, 2026Hassan Jardali, Ihab S. Mohamed, Durgakant Pushp +1Model Predictive ControlAutonomous Driving

    Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN 47408 USA

  11. Response-Aware Risk-Constrained Control Barrier Function With Application to Vehicles

    Mar 13, 2026Qijun Liao, Jue YangSafety-Critical ControlControl Barrier Functions

    School of Mechanical Engineering, University of Science and Technology Beijing, Beijing, 100083, China

  12. Vision-Augmented On-Track System Identification for Autonomous Racing via Attention-Based Priors and Iterative Neural Correction

    Mar 10, 2026Zhiping Wu, Cheng Hu, Yiqin Wang +2Nonlinear System IdentificationVehicle Dynamics

    State Key Laboratory of Industrial, Zhejiang University, Hangzhou 310027, China

  13. High-Slip-Ratio Control for Peak Tire-Road Friction Estimation Using Automated Vehicles

    Mar 10, 2026Zhaohui Liang, Hang Zhou, Heye Huanh +1Vehicle DynamicsAutonomous Driving

    Civil & Environmental Engineering Department, University of Wisconsin, Madison, Madison, WI

  14. Inverse-dynamics observer design for a linear single-track vehicle model with distributed tire dynamics

    Mar 8, 2026Luigi Romano, Ole Morten Aamo, Jan Åslund +1Vehicle DynamicsInverse Dynamics

    Department of Electrical Engineering, Linköping University, Linköping, Sweden · Department of Engineering Cybernetics, NTNU, Trondheim, Norway · Department of Electrical Engineering, Linköping University, Linköping

  15. CAR: Cross-Vehicle Kinodynamics Adaptation via Mobility Representation

    Mar 6, 2026Tong Xu, Chenhui Pan, Xuesu XiaoRobotic ControlMobile Robotics

    Department of Computer Science, George Mason University

  16. Dual-Regime Hybrid Aerodynamic Modeling of Winged Blimps With Neural Mixing

    Feb 25, 2026Xiaorui Wang, Hongwu Wang, Yue Fan +2Vehicle DynamicsSystem Identification

    The authors are with the Robotics and Control Laboratory, School of Advanced Manufacturing and Robotics, and the State Key Laboratory of Turbulence and Complex Systems, Peking University, Beijing, 100871, China

  17. Geometric Inverse Flight Dynamics on SO(3) and Application to Tethered Fixed-Wing Aircraft

    Feb 19, 2026Antonio Franchi, Chiara GabellieriInverse DynamicsVehicle Dynamics

    Robotics and Mechatronics lab, Faculty of Electrical Engineering, Mathematics & Computer Science, University of Twente, Enschede, The Netherlands. · Department of Computer, Control and Management Engineering, Sapienza University of Rome, 00185 Rome, Italy.