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Vehicle dynamics

About: Vehicle dynamics is a research topic. Over the lifetime, 12909 publications have been published within this topic receiving 204091 citations.


Papers
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Journal ArticleDOI
TL;DR: This paper addresses a trajectory-tracking control problem for mobile robots by combining tube-based model predictive control (MPC) in handling kinematic constraints and adaptive control in handling dynamic constraints.
Abstract: This paper addresses a trajectory-tracking control problem for mobile robots by combining tube-based model predictive control (MPC) in handling kinematic constraints and adaptive control in handling dynamic constraints. In order to handle kinematic constraints, the tube-based MPC scheme is introduced, which includes the state feedback controller to suppress the external disturbance in the velocity level. The tube-based MPC is transformed to a constrained quadratic programming (QP) problem, and then the QP problem can be efficiently solved by a primal-dual neural network over a finite receding horizon so as to obtain the optimal control velocity. Besides, an adaptive controller employing the neural network technology is proposed to acquire the approximation of the uncertain robotic dynamics. Moreover, an auxiliary control is developed in order to deal with actuator saturation, and a disturbance observer is designed to reject the external disturbance online in the dynamic level. Subsequently, through Lyapunov function synthesis, the stability of the closed-loop system have been guaranteed. Finally, in order to verify the effectiveness, the experimental studies are carried out using an actual mobile robot.

78 citations

Journal ArticleDOI
TL;DR: Using dynamic coordination graph to model the continuously changing topology during vehicles’ interactions and come up with two basic learning approaches to coordinate the driving maneuvers for a group of vehicles, which are workable in a more complex and realistic setting with any number of vehicles.
Abstract: Autonomous driving is one of the most important AI applications and has attracted extensive interest in recent years. A large number of studies have successfully applied reinforcement learning techniques in various aspects of autonomous driving, ranging from low-level control of driving maneuvers to higher level of strategic decision-making. However, comparatively less progress has been made in investigating how co-existing autonomous vehicles would interact with each other in a common environment and how reinforcement learning can be helpful in such situations by applying multiagent reinforcement learning techniques in the high-level strategic decision-making of the following or overtaking for a group of autonomous vehicles in highway scenarios. Learning to achieve coordination among vehicles in such situations is challenging due to the unique feature of vehicular mobility, which renders it infeasible to directly apply the existing coordinated learning approaches. To solve this problem, we propose using dynamic coordination graph to model the continuously changing topology during vehicles’ interactions and come up with two basic learning approaches to coordinate the driving maneuvers for a group of vehicles. Several extension mechanisms are then presented to make these approaches workable in a more complex and realistic setting with any number of vehicles. The experimental evaluation has verified the benefits of the proposed coordinated learning approaches, compared with other approaches that learn without coordination or rely on some traditional mobility models based on some expert driving rules.

78 citations

Proceedings ArticleDOI
01 Sep 2008
TL;DR: Nereus as discussed by the authors is a hybrid underwater vehicle designed to perform scientific survey and sampling to the full depth of the ocean of 11,000 meters -almost twice the depth of any present-day operational vehicle.
Abstract: This paper reports an overview of the new Nereus hybrid underwater vehicle and summarizes the vehicle's performance during its first sea trials in November 2007. Nereus is a novel operational underwater vehicle designed to perform scientific survey and sampling to the full depth of the ocean of 11,000 meters - almost twice the depth of any present-day operational vehicle. Nereus operates in two different modes. For broad area survey, the vehicle can operate untethered as an autonomous underwater vehicle (AUV) capable of exploring and mapping the sea floor with sonars and cameras. For close up imaging and sampling, Nereus can be converted at sea to operate as a tethered remotely operated vehicle (ROV). This paper reports the overall vehicle design and design elements including ceramic pressure housings and flotation spheres; manipulator and sampling system; light fiber optic tether; lighting and imaging; power and propulsion; navigation; vehicle dynamics and control; and acoustic communications.

78 citations

Book
13 May 2014
TL;DR: In this paper, the authors introduce the problems involved in designing and modeling all types of rail vehicles, including freight and passenger rolling stock, locomotives, and self-powered vehicles used for public transport.
Abstract: A thorough understanding of the issues that affect dynamic performance, as well as more inventive methods for controlling rail vehicle dynamics, is needed to meet the demands for safer rail vehicles with higher speed and loads. Design and Simulation of Rail Vehicles examines the field of rail vehicle design, maintenance, and modification, as well as performance issues related to these types of vehicles. This text analyzes rail vehicle design issues and dynamic responses, describes the design and features of rail vehicles, and introduces methods that address the operational conditions of this complex system. Progresses from Basic Concepts and Terminology to Detailed Explanations and Techniques. Focused on both non-powered and powered rail vehicles—freight and passenger rolling stock, locomotives, and self-powered vehicles used for public transport—this book introduces the problems involved in designing and modeling all types of rail vehicles. It explores the applications of vehicle dynamics, train operations, and track infrastructure maintenance. It introduces the fundamentals of locomotive design, multibody dynamics, and longitudinal train dynamics, and discusses co-simulation techniques. It also highlights recent advances in rail vehicle design, and contains applicable standards and acceptance tests from around the world. Design and Simulation of Rail Vehicles serves as an introductory text for graduate or senior undergraduate students, and as a reference for practicing engineers and researchers investigating performance issues related to these types of vehicles.

78 citations

Proceedings ArticleDOI
13 Apr 2010
TL;DR: This paper examines the tight coupling of the computing and communications aspects of the system with its physical dynamics, and proposes methods to simplify the design procedure for such tightly coupled systems.
Abstract: One of the main characteristics of a Cyber Physical System (CPS) is the tight coupling of the computing and communications aspects of the system with its physical dynamics. In this paper, we examine this characteristic for a cooperative vehicle safety (CVS) system, and identify how the design and operation of such CPSs should consider this tight coupling. In CVS systems, vehicles broadcast their physical state information over a shared wireless network to allow their neighbors to track them and predict possible collisions. The physical dynamics of vehicle movement and the required accuracy from tracking process dictate certain load on the network. The network performance is directly affected by the amount of offered load, and in turn directly affects the tracking process and its required load. The tight mutual dependence of physical dynamics of vehicle (physical component), estimation/tracking process and communication process (cyber components) require a new look at how such systems are designed and operated. We consider these factors and propose methods to simplify the design procedure for such tightly coupled systems. The method includes modeling the subcomponent of the CPS and devising interaction and control algorithms to operate them. The proposed methods are compared with methods based on separate design of components that deal with physical and cyber aspects. Through simulation experiments we show significant gains in performance when CPS design considerations are respected.

78 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023167
2022478
2021620
2020811
2019749
2018749