A5003126186- Vehicle Dynamics and Control Systems
- Electric and Hybrid Vehicle Technologies
- Autonomous Vehicle Technology and Safety
- Advanced Battery Technologies Research
- Electric Vehicles and Infrastructure
- Traffic control and management
- Mechanical Engineering and Vibrations Research
- Hydraulic and Pneumatic Systems
- Real-time simulation and control systems
- Robotic Path Planning Algorithms
- Vehicle emissions and performance
- Traffic Prediction and Management Techniques
- Soil Mechanics and Vehicle Dynamics
- Advanced Control Systems Optimization
- Reinforcement Learning in Robotics
- Traffic and Road Safety
- Vibration Control and Rheological Fluids
- Transportation Planning and Optimization
- Vehicular Ad Hoc Networks (VANETs)
- Explainable Artificial Intelligence (XAI)
- Transportation and Mobility Innovations
- Electrochemical sensors and biosensors
- Advanced biosensing and bioanalysis techniques
- Human-Automation Interaction and Safety
- Refrigeration and Air Conditioning Technologies
Tongji University
2020-2025
China General Nuclear Power Corporation (China)
2025
Fujian Medical University
2023-2024
Second Affiliated Hospital of Fujian Medical University
2023-2024
Beijing Institute of Technology
2023-2024
Wuhan Polytechnic University
2022-2024
Education University of Hong Kong
2024
Seqirus (United States)
2023
Jilin University
2015-2022
Beijing Museum of Natural History
2022
A path planning and tracking framework is presented to maintain a collision-free for autonomous vehicles. For path-planning approaches, 3-D virtual dangerous potential field constructed as superposition of trigonometric functions the road exponential function obstacles, which can generate desired trajectory collision avoidance when vehicle with obstacles likely happen. Next, track planned maneuvers, path-tracking controller formulated task multiconstrained model predictive control (MMPC)...
This paper presents a novel motion planning and tracking framework for automated vehicles based on artificial potential field (APF) elaborated resistance approach. Motion is one of the key parts autonomous driving, which plans sequence movement states to help drive safely, comfortably, economically, human-like, etc. In this paper, APF method used assign different functions obstacles road boundaries; while drivable area meshed assigned values in each edge functions. A local current comparison...
In order to drive safely in a dynamic environment, autonomous vehicles should be able predict the future states of traffic participants nearby, especially surrounding vehicles, similar capability predictive driving human drivers. That is why researchers are devoted field trajectory prediction and propose different methods. This paper provide comprehensive comparative review trajectory-prediction methods proposed over last two decades for driving. It starts with problem formulation algorithm...
A motion planning method for autonomous vehicles confronting emergency situations where collision is inevitable, generating a path to mitigate the crash as much possible, proposed in this paper. The Model predictive control (MPC) algorithm adopted here planning. If avoidance impossible model system, potential severity, and artificial field are filled into controller objective achieve general obstacle lowest severity. Furthermore, vehicle dynamic also considered an optimal problem. Based on...
A predictive energy management strategy considering travel route information is proposed to explore the energy-saving potential of plug-in hybrid electric vehicles. The extreme learning machine used as a short-term speed predictor, and battery temperature added an optimization term cost function. By comparing training data sets, it found that using real-world historical for can achieve higher prediction accuracy than typical standard driving cycles. predictor trained based on further improve...
Autonomous vehicle (AV) is regarded as the ultimate solution to future automotive engineering; however, safety still remains key challenge for development and commercialization of AVs. Therefore, a comprehensive understanding status AVs reported accidents becoming urgent. In this article, levels automation are reviewed according role automated system in autonomous driving process, which will affect frequency disengagements when modes. Additionally, public on-road AV accident reports...
Vehicle control is one of the most critical challenges in autonomous vehicles (AVs) and connected automated (CAVs), it paramount vehicle safety, passenger comfort, transportation efficiency, energy saving. This survey attempts to provide a comprehensive thorough overview current state technology, focusing on evolution from estimation trajectory tracking AVs at microscopic level collaborative CAVs macroscopic level. First, this review starts with key estimation, specifically sideslip angle,...
Aggregates of an amphiphilic monoboronic acid bearing a hydrophobic pyrene fluorophore were employed for highly modulating, sensitive, and selective ratiometric fluorescent sensing glucose in aqueous solution. The selectivity was improved by "knock-out" binding fructose phenylboronic acid.
This paper investigates the lane keeping control of autonomous ground vehicles (AGVs) considering rollover prevention and input saturation. An enhanced state observer-based sliding mode (SMC) strategy is proposed to achieve purpose maintain errors as well roll angle within prescribed performance boundaries. Three contributions are made in this paper. First, a function (PPF) controller design, aiming implement error transformation so constrain controlled variables Second, modified surface...
This paper presents a shared control driver assistance system based on the driving intention identification and situation assessment to avoid obstacles. A constrained linear-time-varying model predictive controller is designed follow obstacle-avoidance path, which obtained by artificial potential method in real time. human driver's desired maneuver are recognized inductive multilabel classification with an unlabeled data approach that trained lateral offset velocity road center line. In...
This paper presents a novel local motion planning framework in hierarchical manner for autonomous vehicles to follow trajectory and agilely avoid obstacles. In the upper layer, new path-planning method based on resistance network is applied plan behaviors (e.g. lane keeping or changing), where human-like factors can be included simulate different driver styles, such as aggressive, moderate, conservative. The planned results (i.e. lane-change command path) will guide lower-layer planner...
Differential drive assistance steering (DDAS) is an emerging assisted mechanism in in-wheel-motor driven (IWMD) electric vehicles, yielded by the differential moment of front tires system. DDAS can steer wheels when there no power from motor, and thus be used as a redundant mechanism. To realize yaw control active entirely breaks down guarantee transient performance therein, this paper proposes integral sliding mode (ISMC) approach for IWMD vehicles steered DDAS. Two contributions are made...
To improve the maneuverability and stability of a vehicle fully leverage advantages torque vectoring technology in dynamics control, finite-time yaw rate sideslip angle tracking controller is proposed by combining second-order sliding mode (SOSM) with backstepping method this paper. However, existing research indicates that first-order (FOSM) control suffers from chattering problem, while traditional SOSM requires knowing bound uncertain term advance to obtain switching gain, which difficult...
Ethical decision-making during inevitable crashes, especially when humans involved, has become a big and sensitive roadblock for future mass adoption of autonomous vehicles. Towards addressing this challenge, paper proposes predictive control framework ethical in driving using rational ethics. For flexibly implementing rules, the Lexicographic Optimization-based model controller (LO-MPC) been designed, which obstacles constraints are prioritized. Simulation environment is set up PreScan,...