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Enhancing Safety in Autonomous Vehicle Navigation:An Optimized Path Planning Approach Leveraging Model Predictive Control
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作者 Shih-Lin Lin Bo-Chen Lin 《Computers, Materials & Continua》 SCIE EI 2024年第9期3555-3572,共18页
This paper explores the application of Model Predictive Control(MPC)to enhance safety and efficiency in autonomous vehicle(AV)navigation through optimized path planning.The evolution of AV technology has progressed ra... This paper explores the application of Model Predictive Control(MPC)to enhance safety and efficiency in autonomous vehicle(AV)navigation through optimized path planning.The evolution of AV technology has progressed rapidly,moving from basic driver-assistance systems(Level 1)to fully autonomous capabilities(Level 5).Central to this advancement are two key functionalities:Lane-Change Maneuvers(LCM)and Adaptive Cruise Control(ACC).In this study,a detailed simulation environment is created to replicate the road network between Nantun andWuri on National Freeway No.1 in Taiwan.The MPC controller is deployed to optimize vehicle trajectories,ensuring safe and efficient navigation.Simulated onboard sensors,including vehicle cameras and millimeterwave radar,are used to detect and respond to dynamic changes in the surrounding environment,enabling real-time decision-making for LCM and ACC.The simulation resultshighlight the superiority of the MPC-based approach in maintaining safe distances,executing controlled lane changes,and optimizing fuel efficiency.Specifically,the MPC controller effectively manages collision avoidance,reduces travel time,and contributes to smoother traffic flow compared to traditional path planning methods.These findings underscore the potential of MPC to enhance the reliability and safety of autonomous driving in complex traffic scenarios.Future research will focus on validating these results through real-world testing,addressing computational challenges for real-time implementation,and exploring the adaptability of MPC under various environmental conditions.This study provides a significant step towards achieving safer and more efficient autonomous vehicle navigation,paving the way for broader adoption of MPC in AV systems. 展开更多
关键词 autonomous driving model predictive control(MPC) lane change maneuver(LCM) adaptive cruise control(ACC)
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Evolutionary Decision-Making and Planning for Autonomous Driving Based on Safe and Rational Exploration and Exploitation 被引量:2
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作者 Kang Yuan Yanjun Huang +4 位作者 Shuo Yang Zewei Zhou Yulei Wang Dongpu Cao Hong Chen 《Engineering》 SCIE EI CAS CSCD 2024年第2期108-120,共13页
Decision-making and motion planning are extremely important in autonomous driving to ensure safe driving in a real-world environment.This study proposes an online evolutionary decision-making and motion planning frame... Decision-making and motion planning are extremely important in autonomous driving to ensure safe driving in a real-world environment.This study proposes an online evolutionary decision-making and motion planning framework for autonomous driving based on a hybrid data-and model-driven method.First,a data-driven decision-making module based on deep reinforcement learning(DRL)is developed to pursue a rational driving performance as much as possible.Then,model predictive control(MPC)is employed to execute both longitudinal and lateral motion planning tasks.Multiple constraints are defined according to the vehicle’s physical limit to meet the driving task requirements.Finally,two principles of safety and rationality for the self-evolution of autonomous driving are proposed.A motion envelope is established and embedded into a rational exploration and exploitation scheme,which filters out unreasonable experiences by masking unsafe actions so as to collect high-quality training data for the DRL agent.Experiments with a high-fidelity vehicle model and MATLAB/Simulink co-simulation environment are conducted,and the results show that the proposed online-evolution framework is able to generate safer,more rational,and more efficient driving action in a real-world environment. 展开更多
关键词 autonomous driving DECISION-MAKING Motion planning Deep reinforcement learning model predictive control
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A Combined Reinforcement Learning and Model Predictive Control for Car-Following Maneuver of Autonomous Vehicles 被引量:2
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作者 Liwen Wang Shuo Yang +2 位作者 Kang Yuan Yanjun Huang Hong Chen 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2023年第3期315-325,共11页
Model predictive control is widely used in the design of autonomous driving algorithms.However,its parameters are sensitive to dynamically varying driving conditions,making it difficult to be implemented into practice... Model predictive control is widely used in the design of autonomous driving algorithms.However,its parameters are sensitive to dynamically varying driving conditions,making it difficult to be implemented into practice.As a result,this study presents a self-learning algorithm based on reinforcement learning to tune a model predictive controller.Specifically,the proposed algorithm is used to extract features of dynamic traffic scenes and adjust the weight coefficients of the model predictive controller.In this method,a risk threshold model is proposed to classify the risk level of the scenes based on the scene features,and aid in the design of the reinforcement learning reward function and ultimately improve the adaptability of the model predictive controller to real-world scenarios.The proposed algorithm is compared to a pure model predictive controller in car-following case.According to the results,the proposed method enables autonomous vehicles to adjust the priority of performance indices reasonably in different scenarios according to risk variations,showing a good scenario adaptability with safety guaranteed. 展开更多
关键词 model predictive control Reinforcement learning autonomous vehicles
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Dynamic Cell Modeling for Accurate SOC Estimation in Autonomous Electric Vehicles
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作者 Qasim Ajao Lanre Sadeeq 《Journal of Power and Energy Engineering》 2023年第8期1-15,共15页
This paper presents findings on dynamic cell modeling for state-of-charge (SOC) estimation in an autonomous electric vehicle (AEV). The studied cells are Lithium-Ion Polymer-based with a nominal capacity of around 8 A... This paper presents findings on dynamic cell modeling for state-of-charge (SOC) estimation in an autonomous electric vehicle (AEV). The studied cells are Lithium-Ion Polymer-based with a nominal capacity of around 8 Ah, optimized for power-needy applications. The AEV operates in a harsh environment with rate requirements up to ±25C and highly dynamic rate profiles, unlike portable-electronic applications with constant power output and fractional C rates. SOC estimation methods effective in portable electronics may not suffice for the AEV. Accurate SOC estimation necessitates a precise cell model. The proposed SOC estimation method utilizes a detailed Kalman-filtering approach. The cell model must include SOC as a state in the model state vector. Multiple cell models are presented, starting with a simple one employing “Coulomb counting” as the state equation and Shepherd’s rule as the output equation, lacking prediction of cell relaxation dynamics. An improved model incorporates filter states to account for relaxation and other dynamics in closed-circuit cell voltage, yielding better performance. The best overall results are achieved with a method combining nonlinear autoregressive filtering and dynamic radial basis function networks. The paper includes lab test results comparing physical cells with model predictions. The most accurate models obtained have an RMS estimation error lower than the quantization noise floor expected in the battery-management-system design. Importantly, these models enable precise SOC estimation, allowing the vehicle controller to utilize the battery pack’s full operating range without overcharging or undercharging concerns. 展开更多
关键词 autonomous Electric Vehicle modeling Battery model Battery Management Systems (BMS) Lithium Polymer State of Charge Kalman-Filter
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MPC-based Motion Planning and Control Enables Smarter and Safer Autonomous Marine Vehicles:Perspectives and a Tutorial Survey 被引量:4
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作者 Henglai Wei Yang Shi 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2023年第1期8-24,共17页
Autonomous marine vehicles(AMVs)have received considerable attention in the past few decades,mainly because they play essential roles in broad marine applications such as environmental monitoring and resource explorat... Autonomous marine vehicles(AMVs)have received considerable attention in the past few decades,mainly because they play essential roles in broad marine applications such as environmental monitoring and resource exploration.Recent advances in the field of communication technologies,perception capability,computational power and advanced optimization algorithms have stimulated new interest in the development of AMVs.In order to deploy the constrained AMVs in the complex dynamic maritime environment,it is crucial to enhance the guidance and control capabilities through effective and practical planning,and control algorithms.Model predictive control(MPC)has been exceptionally successful in different fields due to its ability to systematically handle constraints while optimizing control performance.This paper aims to provide a review of recent progress in the context of motion planning and control for AMVs from the perceptive of MPC.Finally,future research trends and directions in this substantial research area of AMVs are highlighted. 展开更多
关键词 autonomous marine vehicles(AMVs) model predictive control(MPC) motion control motion planning
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Role-based Bayesian decision framework for autonomous unmanned systems 被引量:2
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作者 PANG Weijian MA Xinyi +2 位作者 LIANG Xueming LIU Xiaogang DONG Erwa 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2023年第6期1397-1408,共12页
In the process of performing a task,autonomous unmanned systems face the problem of scene changing,which requires the ability of real-time decision-making under dynamically changing scenes.Therefore,taking the unmanne... In the process of performing a task,autonomous unmanned systems face the problem of scene changing,which requires the ability of real-time decision-making under dynamically changing scenes.Therefore,taking the unmanned system coordinative region control operation as an example,this paper combines knowledge representation with probabilistic decisionmaking and proposes a role-based Bayesian decision model for autonomous unmanned systems that integrates scene cognition and individual preferences.Firstly,according to utility value decision theory,the role-based utility value decision model is proposed to realize task coordination according to the preference of the role that individual is assigned.Then,multi-entity Bayesian network is introduced for situation assessment,by which scenes and their uncertainty related to the operation are semantically described,so that the unmanned systems can conduct situation awareness in a set of scenes with uncertainty.Finally,the effectiveness of the proposed method is verified in a virtual task scenario.This research has important reference value for realizing scene cognition,improving cooperative decision-making ability under dynamic scenes,and achieving swarm level autonomy of unmanned systems. 展开更多
关键词 autonomous unmanned systems multi-entity Bayesian network(MEBN) situation awareness decision modeling.
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Multi-constrained model predictive control for autonomous ground vehicle trajectory tracking 被引量:22
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作者 龚建伟 徐威 +3 位作者 姜岩 刘凯 郭红芬 孙银健 《Journal of Beijing Institute of Technology》 EI CAS 2015年第4期441-448,共8页
A multi-constrained model predictive control ( MPC ) algorithm for trajectory tracking of an autonomous ground vehicle is proposed and tested in this paper. First, to simplify the computa- tion, an active steering l... A multi-constrained model predictive control ( MPC ) algorithm for trajectory tracking of an autonomous ground vehicle is proposed and tested in this paper. First, to simplify the computa- tion, an active steering linear error model is applied in the MPC controller. Then, a control incre- ment constraint and a relaxing factor are taken into account in the objective function to ensure the smoothness of the trajectory, using a softening constraints technique. In addition, the controller can obtain optimal control sequences which satisfy both the actual kinematic constraints and the actuator constraints. The circular trajectory tracking performance of the proposed method is compared with that of another MPC controller. To verify the trajectory tracking capabilities of the designed control- ler at different desired speed, the simulation experiments are carried out at the speed of 3m/s, 5m/ s and 10m/s. The results demonstrate the MPC controller has a good speed adaptability. 展开更多
关键词 autonomous ground vehicle active steering control model predictive control trajecto-ry tracking
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Ribbon model based path tracking method for autonomous ground vehicles 被引量:10
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作者 陈清阳 孙振平 +1 位作者 刘大学 李晓辉 《Journal of Central South University》 SCIE EI CAS 2014年第5期1816-1826,共11页
To resolve the path tracking problem of autonomous ground vehicles,an analysis of existing path tracking methods was carried out and an important conclusion was got.The vehicle-road model is crucial for path following... To resolve the path tracking problem of autonomous ground vehicles,an analysis of existing path tracking methods was carried out and an important conclusion was got.The vehicle-road model is crucial for path following.Based on the conclusion,a new vehicle-road model named "ribbon model" was constructed with consideration of road width and vehicle geometry structure.A new vehicle-road evaluation algorithm was proposed based on this model,and a new path tracking controller including a steering controller and a speed controller was designed.The difficulties of preview distance selection and parameters tuning with speed in the pure following controller are avoided in this controller.To verify the performance of the novel method,simulation and real vehicle experiments were carried out.Experimental results show that the path tracking controller can keep the vehicle in the road running as fast as possible,so it can adjust the control strategy,such as safety,amenity,and rapidity criteria autonomously according to the road situation.This is important for the controller to adapt to different kinds of environments,and can improve the performance of autonomous ground vehicles significantly. 展开更多
关键词 autonomous ground vehicle path tracking ribbon model
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Modeling and gender difference analysis of acceptance of autonomous driving technology 被引量:2
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作者 Chen Yuexia Zha Qifen +2 位作者 Jing Peng Cheng Hengquan Shao Danning 《Journal of Southeast University(English Edition)》 EI CAS 2021年第2期216-221,共6页
In order to deeply analyze the differences in the acceptance of autonomous driving technology among different gender groups,a multiple indicators and multiple causes model was constructed by integrating a technology a... In order to deeply analyze the differences in the acceptance of autonomous driving technology among different gender groups,a multiple indicators and multiple causes model was constructed by integrating a technology acceptance model and theory of planned behavior to comprehensively reveal the gender differences in the influence mechanisms of subjective and objective factors.The analysis is based on data collected from Chinese urban residents.Among objective factors,age has a significant negative impact on women's perceived behavior control and a significant positive impact on perceived ease of use.Education has a significant positive impact on men's perceived behavior control,and has a strong positive impact on women's perceived usefulness(PU).For men,income and education are found to have strong positive impacts on perceived behavior control.Among subjective factors,perceived ease of use(PEU)has the greatest influence on women's behavior intention,and it is the only influential factor for women's intention to use autonomous driving technology,with an influence coefficient of 0.72.The influencing path of men's intention to use autonomous driving technology is more complex.It is not only directly affected by the significant and positive joint effects of attitude and PU,but also indirectly affected by perceived behavior controls,subjective norms,and PEU. 展开更多
关键词 autonomous vehicle acceptance of autonomous driving technology technology acceptance model theory of planned behavior multiple indicators and multiple causes model
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Modeling the heterogeneous traffic flow considering the effect of self-stabilizing and autonomous vehicles 被引量:1
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作者 Yuan Gong Wen-Xing Zhu 《Chinese Physics B》 SCIE EI CAS CSCD 2022年第2期434-443,共10页
With the increasing maturity of automatic driving technology,the homogeneous traffic flow will gradually evolve into the heterogeneous traffic flow,which consists of human-driving and autonomous vehicles.To better stu... With the increasing maturity of automatic driving technology,the homogeneous traffic flow will gradually evolve into the heterogeneous traffic flow,which consists of human-driving and autonomous vehicles.To better study the characteristics of the heterogeneous traffic system,this paper proposes a new car-following model for autonomous vehicles and heterogeneous traffic flow,which considers the self-stabilizing effect of vehicles.Through linear and nonlinear methods,this paper deduces and analyzes the stability of such a car-following model with the self-stabilizing effect.Finally,the model is verified by numerical simulation.Numerical results show that the self-stabilizing effect can make the heterogeneous traffic flow more stable,and that increasing the self-stabilizing coefficient or historical time length can strengthen the stability of heterogeneous traffic flow and alleviate traffic congestion effectively.In addition,the heterogeneous traffic flow can also be stabilized with a higher proportion of autonomous vehicles. 展开更多
关键词 heterogeneous traffic flow self-stabilizing effect car-following model autonomous vehicle
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Lane-Exchanging Driving Strategy for Autonomous Vehicle via Trajectory Prediction and Model Predictive Control 被引量:1
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作者 Yimin Chen Huilong Yu +1 位作者 Jinwei Zhang Dongpu Cao 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2022年第4期256-267,共12页
The cooperation between an autonomous vehicle and a nearby vehicle is critical to ensure driving safety in the laneexchanging scenario.The nearby vehicle trajectory needs to be predicted,from which the autonomous vehi... The cooperation between an autonomous vehicle and a nearby vehicle is critical to ensure driving safety in the laneexchanging scenario.The nearby vehicle trajectory needs to be predicted,from which the autonomous vehicle is controlled to prevent possible collisions.This paper proposes a lane-exchanging driving strategy for the autonomous vehicle to cooperate with the nearby vehicle by integrating vehicle trajectory prediction and motion control.A trajectory prediction method is developed to anticipate the nearby vehicle trajectory.The Gaussian mixture model(GMM),together with the vehicle kinematic model,are synthesized to predict the nearby vehicle trajectory.A potential-feldbased model predictive control(MPC)approach is utilized by the autonomous vehicle to conduct the lane-exchanging maneuver.The potential feld of the nearby vehicle is considered in the controller design for collision avoidance.On-road driving data verifcation shows that the nearby vehicle trajectory can be predicted by the proposed method.CarSim®simulations validate that the autonomous vehicle can perform the lane-exchanging maneuver and avoid the nearby vehicle using the proposed driving strategy.The autonomous vehicle can thus safely perform the laneexchanging maneuver and avoid the nearby vehicle. 展开更多
关键词 autonomous vehicle Lane-exchanging Vehicle trajectory prediction Potential feld model predictive control
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Dynamics Modeling and Simulation of Autonomous Underwater Vehicles with Appendages 被引量:3
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作者 Yumin Su Jinxin Zhao Jian Cao Guocheng Zhang 《Journal of Marine Science and Application》 2013年第1期45-51,共7页
To provide a simulation system platform for designing and debugging a small autonomous underwater vehicle's (AUV) motion controller, a six-degree of freedom (6-DOF) dynamic model for AUV controlled by thruster an... To provide a simulation system platform for designing and debugging a small autonomous underwater vehicle's (AUV) motion controller, a six-degree of freedom (6-DOF) dynamic model for AUV controlled by thruster and fins with appendages is examined. Based on the dynamic model, a simulation system for the AUV's motion is established. The different kinds of typical motions are simulated to analyze the motion performance and the maneuverability of the AUV. In order to evaluate the influences of appendages on the motion performance of the AUV, simulations of the AUV with and without appendages are performed and compared. The results demonstrate the AUV has good maneuverability with and without appendages. 展开更多
关键词 autonomous underwater vehicle (AUV) motion performance dynamics modeling appendages simulation system
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Valuation Model for Adding Energy Resource into Autonomous Energy Cluster
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作者 Ewoud de Kok Ebisa Negeri +1 位作者 Ad van Wijk Nico Baken 《Smart Grid and Renewable Energy》 2013年第5期417-427,共11页
With the availability of distributed generation (DG), clusters that can autonomously manage their energy profile are emerging in the power grid. These autonomous clusters manage their load profiles by orchestrating th... With the availability of distributed generation (DG), clusters that can autonomously manage their energy profile are emerging in the power grid. These autonomous clusters manage their load profiles by orchestrating their energy resources, such as DG, storage, flexible energy consuming appliances, etc. The performance of such an autonomous cluster depends on the composition of its energy resources. In this paper, we study how the performance of a cluster is affected by adding energy resources such as generating units, storage systems or consuming appliances. First, we characterize the energy resources by parameters that describe their relevant properties. Afterwards, we describe a comprehensive set of performance indicators of a cluster that capture the economical, environmental, and social aspects. We present a model that shows how the energy resources influence the performance indicators of the cluster. We have tested our model with a case study, revealing its effectiveness to evaluate the value added by an energy resource to a cluster. 展开更多
关键词 Prosumer autonomous ENERGY CLUSTERS VALUATION model
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Pullback Attractor of a Non-autonomous Model for Epitaxial Growth
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作者 DUAN NING ZHAO XIAO-PENG Gao Wen-jie 《Communications in Mathematical Research》 CSCD 2018年第4期289-295,共7页
In this paper, we consider a non-autonomous model for epitaxial growth. It is shown that a pullback attractor of the model exists when the external force has exponential growth.
关键词 pullback attractor non-autonomous model asymptotic compactness
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Persistence and Extinction of a Non-Autonomous Plant Disease Model with Roguing<sup>*</sup>
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作者 Lijun Xia Hengmin Lv +1 位作者 Jinxing Yuan Yongquan Liu 《Journal of Applied Mathematics and Physics》 2020年第10期2197-2212,共16页
On the basis of analyzing the shortages of present studies on plant disease model for autonomous phenomenon, and considering the actual situation, this paper applies the joint factors of environmental change and the i... On the basis of analyzing the shortages of present studies on plant disease model for autonomous phenomenon, and considering the actual situation, this paper applies the joint factors of environmental change and the infectivity for latent plants into the system;therefore we deal with a non-autonomous plant disease model with roguing. Some sufficient conditions are established for extinction of diseases and permanence of the system in this paper. 展开更多
关键词 Non-autonomous Plant Disease model Roguing EXTINCTION PERMANENCE
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AUTONOMOUS AGENT FRAMEWORK AND ITS DECISION-MAKING
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作者 李斌 朱梧槚 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2005年第1期59-63,共5页
Autonomy, a key property associated with the agent, is an important topic in the current research of the agent theory. Although no definition of the agent autonomy is universally accepted, an important aspect of the a... Autonomy, a key property associated with the agent, is an important topic in the current research of the agent theory. Although no definition of the agent autonomy is universally accepted, an important aspect of the agent autonomy is the decision-making capability of the agents. This paper investigates the autonomy of the agent, presents a framework for autonomous agent and discusses its decision-making process. Started with introducing a language for representing autonomous agent, a framework is proposed for modeling autonomous agent based on a BDI model and the situation calculus. Finally, a kind of decision-making process of the autonomous agent is presented. 展开更多
关键词 autonomous agent agent theory BDI model situation calculus DECISION-MAKING
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Trajectory Tracking of Autonomous Vehicle with the Fusion of DYC and Longitudinal–Lateral Control 被引量:19
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作者 Fen Lin Yaowen Zhang +3 位作者 Youqun Zhao Guodong Yin Huiqi Zhang Kaizheng Wang 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2019年第1期212-227,共16页
The current research of autonomous vehicle motion control mainly focuses on trajectory tracking and velocity tracking. However, numerous studies deal with trajectory tracking and velocity tracking separately, and the ... The current research of autonomous vehicle motion control mainly focuses on trajectory tracking and velocity tracking. However, numerous studies deal with trajectory tracking and velocity tracking separately, and the yaw stability is seldom considered during trajectory tracking. In this research, a combination of the longitudinal–lateral control method with the yaw stability in the trajectory tracking for autonomous vehicles is studied. Based on the vehicle dynamics, considering the longitudinal and lateral motion of the vehicle, the velocity tracking and trajectory tracking problems can be attributed to the longitudinal and lateral control. A sliding mode variable structure control method is used in the longitudinal control. The total driving force is obtained from the velocity error in order to carry out velocity tracking. A linear time-varying model predictive control method is used in the lateral control to predict the required front wheel angle for trajectory tracking. Furthermore, a combined control framework is established to control the longitudinal and lateral motions and improve the reliability of the longitudinal and lateral direction control. On this basis, the driving force of a tire is allocated reasonably by using the direct yaw moment control, which ensures good yaw stability of the vehicle when tracking the trajectory. Simulation results indicate that the proposed control strategy is good in tracking the reference velocity and trajectory and improves the performance of the stability of the vehicle. 展开更多
关键词 autonomous vehicle TRAJECTORY tracking Direct yaw MOMENT control(DYC) model predictive CONTROL (MPC) Longitudinal–lateral CONTROL
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CBF-Based Distributed Model Predictive Control for Safe Formation of Autonomous Mobile Robots
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作者 MU Jianbin YANG Haili HE Defeng 《Journal of Shanghai Jiaotong university(Science)》 EI 2024年第4期678-688,共11页
A distributed model predictive control(DMPC)method based on robust control barrier function(RCBF)is developed to achieve the safe formation target of multi-autonomous mobile robot systems in an uncertain disturbed env... A distributed model predictive control(DMPC)method based on robust control barrier function(RCBF)is developed to achieve the safe formation target of multi-autonomous mobile robot systems in an uncertain disturbed environment.The first step is to analyze the safety requirements of the system during safe formation and categorize them into collision avoidance and distance connectivity maintenance.RCBF constraints are designed based on collision avoidance and connectivity maintenance requirements,and security constraints are achieved through a combination.Then,the specified safety constraints are integrated with the objective of forming a multi-autonomous mobile robot formation.To ensure safe control,the optimization problem is integrated with the DMPC method.Finally,the RCBF-DMPC algorithm is proposed to ensure iterative feasibility and stability while meeting the constraints and expected objectives.Simulation experiments illustrate that the designed algorithm can achieve cooperative formation and ensure system security. 展开更多
关键词 distributed model predictive control(DMPC) robust control barrier function(RCBF) autonomous mobile robot formation control collision avoidance
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Adaptive Coordinated Path Tracking Control Strategy for Autonomous Vehicles with Direct Yaw Moment Control 被引量:4
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作者 Ying Tian Qiangqiang Yao +1 位作者 Peng Hang Shengyuan Wang 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2022年第1期223-237,共15页
It is a striking fact that the path tracking accuracy of autonomous vehicles based on active front wheel steering is poor under high-speed and large-curvature conditions.In this study,an adaptive path tracking control... It is a striking fact that the path tracking accuracy of autonomous vehicles based on active front wheel steering is poor under high-speed and large-curvature conditions.In this study,an adaptive path tracking control strategy that coordinates active front wheel steering and direct yaw moment is proposed based on model predictive control algorithm.The recursive least square method with a forgetting factor is used to identify the rear tire cornering stiffness and update the path tracking system prediction model.To adaptively adjust the priorities of path tracking accuracy and vehicle stability,an adaptive strategy based on fuzzy rules is applied to change the weight coefficients in the cost function.An adaptive control strategy for coordinating active front steering and direct yaw moment is proposed to improve the path tracking accuracy under high-speed and large-curvature conditions.To ensure vehicle stability,the sideslip angle,yaw rate and zero moment methods are used to construct optimization constraints based on the model predictive control frame.It is verified through simulation experiments that the proposed adaptive coordinated control strategy can improve the path tracking accuracy and ensure vehicle stability under high-speed and largecurvature conditions. 展开更多
关键词 autonomous vehicles Path tracking model predictive control Adaptive coordinated
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Path Planning and Navigation of Oceanic Autonomous Sailboats and Vessels: A Survey 被引量:2
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作者 JING Wei LIU Chao +7 位作者 LI Ting RAHMAN A B M Mohaimenur XIAN Lintao WANG Xi WANG Yu GUO Zhongwen BRENDA Gumede TENDAI Wachi Kelvin 《Journal of Ocean University of China》 SCIE CAS CSCD 2020年第3期609-621,共13页
Oceanic autonomous surface vehicles(ASVs) are one kind of autonomous marine robots that have advantages of energy saving and is flexible to use. Nowadays, ASVs are playing an important role in marine science, maritime... Oceanic autonomous surface vehicles(ASVs) are one kind of autonomous marine robots that have advantages of energy saving and is flexible to use. Nowadays, ASVs are playing an important role in marine science, maritime industry, and national defense. It could improve the efficiency of oceanic data collection, ensure marine transportation safety, and protect national security. One of the core challenges for ASVs is how to plan a safe navigation autonomously under the complicated ocean environment. Based on the type of marine vehicles, ASVs could be divided into two categories: autonomous sailboats and autonomous vessels. In this article, we review the challenges and related solutions of ASVs' autonomous navigation, including modeling analysis, path planning and implementation. Finally, we make a summary of all of those in four tables and discuss about the future research directions. 展开更多
关键词 autonomous sailboats autonomous vessels model analysis path planning
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