A5002740588- Autonomous Vehicle Technology and Safety
- Hydraulic and Pneumatic Systems
- Traffic control and management
- Advanced machining processes and optimization
- Iterative Learning Control Systems
- Robotic Path Planning Algorithms
- Electric and Hybrid Vehicle Technologies
- Advanced Surface Polishing Techniques
- Gear and Bearing Dynamics Analysis
- Vehicle Dynamics and Control Systems
- Reinforcement Learning in Robotics
- Electrowetting and Microfluidic Technologies
- Human-Automation Interaction and Safety
- Advanced Machining and Optimization Techniques
- Control and Dynamics of Mobile Robots
- Geological Modeling and Analysis
- Seismic Performance and Analysis
- Interactive and Immersive Displays
- Advanced Numerical Analysis Techniques
- Advanced Control Systems Optimization
- Tactile and Sensory Interactions
- Modular Robots and Swarm Intelligence
- Transportation and Mobility Innovations
- Transportation Planning and Optimization
- Control Systems in Engineering
The University of Texas at Arlington
2024-2025
Ford Motor Company (United States)
2011-2024
National Chung Cheng University
2019-2022
Vehicle active safety systems stabilise the vehicle by controlling tyre forces. They work well only when forces commanded are within friction limit. Therefore, knowledge of tyre/road coefficient can improve performance systems. This study presents four methods to estimate based on different excitation conditions: medium lateral excitation, large small longitudinal and excitation. For cases, estimation is lateral/yaw dynamics Brush model, whereas for basis relationship between slip traction...
Decision-making for autonomous driving is challenging, considering the complex interactions among multiple traffic agents (including vehicles (AVs), human-driven vehicles, and pedestrians) computational load needed to evaluate these interactions. This paper develops two general potential game-based frameworks, namely, finite continuous games, decision-making in driving. The frameworks account AVs' types of action spaces, i.e., respectively. developed provide theoretical guarantees existence...
Performing real-time receding horizon motion planning for autonomous vehicles while providing safety guarantees remains difficult. This is because existing methods to accurately predict ego vehicle behavior under a chosen controller use online numerical integration that requires fine time discretization and thereby adversely affects performance. To address this limitation, several recent papers have proposed apply offline reachability analysis conservatively the of vehicle. Reachable sets...
This article proposes a novel decision-making framework for autonomous vehicles (AVs), called predictor–corrector potential game (PCPG), composed of predictor and corrector. To enable human-like reasoning characterize agent interactions, receding-horizon multiplayer is formulated. address the challenges caused by complexity solving requirement real-time operation, (PG)-based developed in PG predictor, where agents' cost functions are heuristically predefined. We acknowledge that behaviors...
The paper proposes a dynamic model of an automotive dry dual clutch system, which comprises submodels lever-based electromechanical actuator and assembly. is developed by using the bond graph approach, it can be used for design, analysis, control tasks. Special attention devoted to modeling friction, compliance, lever geometry effects, as they are ones that predominantly determine accuracy static curve description computational efficiency model. Several custom-designed test rigs utilized...
A Stackelberg differential game theoretic model predictive controller is proposed for an autonomous highway driving problem. The hierarchical controller's high-level component the two-player lane change game, where each player uses a (MPC) to control his/her own motion. converted into bi-level optimization problem and solved with branch bound algorithm. Additionally, inverse MPC algorithm developed estimate weights of cost function target vehicle. low-level hybrid controls both vehicle's...
This paper presents an optimization algorithm for tuning the interpolation parameters of computer numerical control (CNC) controllers; it operates by considering multiple objective functions, namely, contour errors, machining time (MT), and vibrations. The position commands, vibration signals from 1024 experiments were considered in designed trajectory. experimental data—the maximum error (MCoE), MT, corner (CVib)—were analyzed to compute performance index. A backpropagation neural network...
The paper presents a dynamic model of dual clutch lever-based electromechanical actuator. Bond graph modeling technique is used to describe the actuator dynamics. parameterized and thoroughly validated based on experimental data collected by using test rig. validation results are for purpose analysis behavior under typical operating modes.
This study proposed an approach to control voice coil motors (VCMs) installed in smartphone modules as autofocus actuators. The VCM developed this comprises guide rods. magnetic field attraction force between rods and movable parts serves lens restoring force. did not use feedback elements avoid the stick-slip phenomenon parts. Instead, used a high-low frequency composite signal based on findings from mathematical model analysis dynamic attribute analysis, preventing offering more favorable...
The main purpose of this correspondence is to clarify and correct some statements from the brief paper (Li et al., 2020), which introduces analyzes so-called energy-driven-damper (EDD) control strategy for semiactive dampers in context advanced vehicle suspensions.
With the development of artificial intelligence and breakthroughs in deep learning, large-scale Foundation Models (FMs), such as GPT, CLIP, etc., have achieved remarkable results many fields including natural language processing computer vision. The application FMs autonomous driving holds considerable promise. For example, they can contribute to enhance scene understanding reasoning. By pre-training on rich linguistic visual data, understand interpret various elements a scene, provide...