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面向预期功能安全的汽车队列主动容错控制

机械工程学报 2024年第10期60卷 384-398页

作者：王博罗禹贡赵超王永胜清华大学车辆与运载学院北京100084

针对智能网联汽车队列预期功能安全挑战,以同时存在感知、控制执行与通信系统性能局限的智能网联汽车为研究对象,提出面向预期功能安全的汽车队列主动容错控制。首先,提出适应不同间歇车间通信拓扑构型的队列容错控制方法,分别设计分布... 详细信息

针对智能网联汽车队列预期功能安全挑战,以同时存在感知、控制执行与通信系统性能局限的智能网联汽车为研究对象,提出面向预期功能安全的汽车队列主动容错控制。首先,提出适应不同间歇车间通信拓扑构型的队列容错控制方法,分别设计分布式增广综合干扰估计器、容错跟踪控制器和安全控制器,用于提供估计信息、应对理想或部分连接的和应对完全中断车间通信拓扑构型;此外,提出了时变车间通信条件下的控制器平稳切换充分条件及其在线参数自适应更新方法,应对时变的间歇通信与控制器切换。基于Matlab/Simulink建立7车队列模型和控制策略,基于dSpace和真实通信硬件搭建队列容错控制硬件在环试验平台,对比验证了所提控制策略的有效性和优越性。仿真和试验结果表明,所提方法在多种工况下均可保障队列在同时存在感知、控制执行和通信性能局限条件下的安全稳定运行,且良好的鲁棒性和切换平顺性。

关键词：智能网联汽车队列预期功能安全状态估计容错控制

基于场景划分的智能网联汽车协同换道避障方法

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汽车工程 2024年第5期46卷 745-753页

作者：周俊宇李克强任晗啸于杰罗禹贡清华大学车辆与运载学院汽车安全与节能国家重点实验室北京100084

为解决传统基于V2V通信的两车协同换道对于前方交通存在未知交通情况,及周围车辆信息获知不准确情况下换道成功率低且无法保证交通效率最优的问题,本文提出了一种基于场景划分的ICV两阶段协同换道避障方法。首先,将换道过程划分为纵向... 详细信息

为解决传统基于V2V通信的两车协同换道对于前方交通存在未知交通情况,及周围车辆信息获知不准确情况下换道成功率低且无法保证交通效率最优的问题,本文提出了一种基于场景划分的ICV两阶段协同换道避障方法。首先,将换道过程划分为纵向间距调整阶段与横向换道阶段,分别使用四次多项式与五次多项式描述两个阶段ICV的轨迹;其次,根据纵向间距调整结束时刻车辆的相对位置设计了4种场景,并设计以车辆调整末速度、距离与换道时间为目标函数的换道模型,在保证换道成功率的同时减少换道行为对上游交通产生的影响;最后,为了验证算法的有效性,在4种场景下分别设计可行工况,并对间距调整过程进行速度-时间与距离-时间关系图进行分析,证明间距调整过程均满足安全约束;同时,本文通过遍历循环计算换道避障算法的边界值,说明了ICV换道避障成功率与车间距、车辆与障碍物间距之间具有相关性。

关键词：智能网联汽车换道避障轨迹规划边界分析

面向进出站强制换道过程的智能网联公交车两车协同换道策略

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清华大学学报（自然科学版） 2024年第8期64卷 1456-1468页

作者：任晗啸罗禹贡关书睿于杰周俊宇李克强清华大学智能绿色车辆与交通全国重点实验室北京100084

目前针对智能网联公交车换道策略的研究多基于单车智能实现,缺少对周围车辆的考虑,难以处理车间冲突,无法同时保障公交车进出站强制换道的安全性和成功率,且容易对上游交通造成影响。该文旨在面向公交车进出站强制换道过程,提出一种基... 详细信息

目前针对智能网联公交车换道策略的研究多基于单车智能实现,缺少对周围车辆的考虑,难以处理车间冲突,无法同时保障公交车进出站强制换道的安全性和成功率,且容易对上游交通造成影响。该文旨在面向公交车进出站强制换道过程,提出一种基于云控系统的两车协同换道策略。针对进站过程,建立了基于换道收益准则的换道决策模型,制定了包含纵向调整、协同换道的两段式滚动时域轨迹规划方法,并基于分层二次规划改善算法实时性;针对出站过程,采用基于规则的决策方法和提前减速策略,制定了考虑港湾式车站特点的轨迹规划方法,以适应车站形状和公交车机动性的要求。仿真和硬件在环实验表明:该策略能够有效提升公交车进出站强制换道的成功率,并在保障换道安全的同时降低对上游交通的影响,且在真实云平台的运算、通信环境下具备可用性。

关键词：智能网联汽车公交车强制换道协同换道

面向强制换道场景的智能网联汽车协同换道策略

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汽车工程 2024年第2期46卷 201-210,280页

作者：关书睿李克强周俊宇石佳孔伟伟罗禹贡清华大学车辆与运载学院汽车安全与节能国家重点实验室北京100084 中国农业大学工学院北京100083

智能网联汽车的协同换道技术已得到广泛研究,但现有协同换道策略难以解决强制换道场景下的车辆协同问题,或对上游交通造成的负面影响较大。本文旨在面向强制换道场景需求,提出一种考虑理论最小安全距离的两阶段协同换道策略。首先,提出... 详细信息

智能网联汽车的协同换道技术已得到广泛研究,但现有协同换道策略难以解决强制换道场景下的车辆协同问题,或对上游交通造成的负面影响较大。本文旨在面向强制换道场景需求,提出一种考虑理论最小安全距离的两阶段协同换道策略。首先,提出了两车协同换道系统控制架构,并面向车辆强制换道场景制定了协同换道方案。随后,设计了间距调整、协同换道两阶段的滚动时域轨迹规划方法,并求解理论最小安全距离作为间距调整阶段末态约束,解决了现有研究间距策略保守的问题。最后,通过仿真与硬件在环试验验证了所提策略的有效性、优越性与计算实时性。结果表明,所提策略可有效提升换道成功率,在保障换道安全性的条件下降低了换道行为对交通的影响,且在实际边缘云平台的实时计算、通信环境下具备可用性。

关键词：智能网联汽车协同换道强制换道轨迹规划

Integrated adaptive dynamic surface car-following control for nonholonomic autonomous electric vehicles

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Science China(Technological Sciences) 2017年第8期60卷 1221-1230页

作者： GUO JingHua luo yugong LI KeQiang Department of Mechanical and Electrical Engineering Xiamen University State Key Laboratory of Automotive Safety and Energy Tsinghua University

In this paper,the car-following control problem of nonholonomic autonomous electric vehicles in the curved highway is *** to the fact that the nonholonomic autonomous electric vehicles have the features of strong coupling,parametric uncertainties,nonlinearities and external disturbances,a novel integrated adaptive car-following control system is constructed to supervise the longitudinal and lateral motions of ***,an adaptive fuzzy dynamic surface car-following control strategy is presented to determine a vector of total forces and torque of autonomous electric vehicles,which can guarantee the uniform ultimate boundedness of close-loop control ***,an optimal tire forces distribution law is proposed to dynamically allocate the desired coupled tire longitudinal and lateral forces in ***,simulation results illustrate the effectiveness and robustness of the proposed car-following control approach.

关键词： autonomous electric vehicles car following adaptive dynamic surface control strong coupling integrated control

Adaptive fuzzy sliding mode control for coordinated longitudinal and lateral motions of multiple autonomous vehicles in a platoon

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Science China(Technological Sciences) 2017年第4期60卷 576-586页

作者： GUO JingHua luo yugong LI KeQiang Department of Mechanical and Electrical Engineering Xiamen University State Key Laboratory of Automotive Safety and Energy Tsinghua University

In this paper, the platoon control problem of autonomous vehicles in highway is studied. Since the autonomous vehicles have the characteristics of nonlinearities, external disturbances and strong coupling, a novel adaptive fuzzy sliding coordinated control system is constructed to supervise the longitudinal and lateral motions of autonomous vehicles, in which the fuzzy system is employed to approximate the unknown nonlinear functions. Due to the low sensitivity to disturbances and plant parameter variations, the proposed control approach is an efficient way to handle with the complex dynamic plants operating under un-certainty conditions. The asymptotic stability of adaptive coordinated platoon close-loop control system is verified based on the Lyapunov stability theory. The results indicate that the presented adaptive coordinated platoon control approach can accurately achieve the tracking performance and ensures the stability and riding comfort of autonomous vehicles in a platoon. Finally,simulation test is exploited to demonstrate the effectiveness of the proposed control approach.

关键词： autonomous vehicles vehicle dynamics coordinated platoon control nonlinearities adaptive fuzzy sliding mode

Key Technologies in Connected Autonomous Electrified Vehicles

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Chinese Journal of Mechanical Engineering 2021年第5期34卷 1-2页

作者： yugong luo Wenbo Chu Dongpu Cao State Key Laboratory of Automotive Safety and Energy Tsinghua UniversityBeijing 100084China China Intelligent and Connected Vehicles(Beijing)Research Institute Co. LtdBeijing 100176China Department of Mechanical and Mechatronics Engineering University of WaterlooWaterlooON N2L 3G1Canada

The rapid development of technologies such as artificial intelligence,Internet of Things,big data,and information communication has promoted the development of connected autonomous electrified vehicles with functions such as complex environment perception,intelligent decision-making,collaborative control,and *** main objective of this special issue aims at bringing scholars to show their latest research results in environmental perception systems.

关键词： autonomous connected promoted

Neural-Fuzzy-Based Adaptive Sliding Mode Automatic Steering Control of Vision-based Unmanned Electric Vehicles

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Chinese Journal of Mechanical Engineering 2021年第5期34卷 56-68页

作者： Jinghua Guo Keqiang Li Jingjing Fan yugong luo Jingyao Wang School of Aerospace Engineering Xiamen UniversityXiamen 361005China State Key Laboratory of Automotive Safety and Energy Tsinghua UniversityBeijing 100084China School of Electrical and Control Engineering North China University of TechnologyBeijing 100144China

This paper presents a novel neural-fuzzy-based adaptive sliding mode automatic steering control strategy to improve the driving performance of vision-based unmanned electric vehicles with time-varying and uncertain ***,the kinematic and dynamic models which accurately express the steering behaviors of vehicles are constructed,and in which the relationship between the look-ahead time and vehicle velocity is ***,in order to overcome the external disturbances,parametric uncertainties and time-varying features of vehicles,a neural-fuzzy-based adaptive sliding mode automatic steering controller is proposed to supervise the lateral dynamic behavior of unmanned electric vehicles,which includes an equivalent control law and an adaptive variable structure control *** this novel automatic steering control system of vehicles,a neural network system is utilized for approximating the switching control gain of variable structure control law,and a fuzzy inference system is presented to adjust the thickness of boundary layer in *** stability of closed-loop neural-fuzzy-based adaptive sliding mode automatic steering control system is proven using the Lyapunov ***,the results illustrate that the presented control scheme has the excellent properties in term of error convergence and robustness.

关键词： Vision-based unmanned electric vehicles Automatic steering Neural-fuzzy adaptive sliding control Vehicle lateral dynamics

An adaptive cascade trajectory tracking control for over-actuated autonomous electric vehicles with input saturation

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Science China(Technological Sciences) 2019年第12期62卷 2153-2160页

作者： GUO JingHua luo yugong WANG JingYao LI KeQiang CHEN Tao School of Aerospace Engineering Xiamen UniversityXiamen 361005China State Key Laboratory of Automotive Safety and Energy Tsinghua UniversitBejing 100084China China Automotive Engineering Research Institute Co LtdChongqing 401122China

This paper presented a novel adaptive cascade nonlinear trajectory tracking control scheme of over-actuated autonomous electric vehicles involving input saturation. First, a nonlinear vehicle dynamic model with input saturation is established, which can accurately describe the features of uncertainties and coupling of autonomous electric vehicles, and the hyperbolic tangent function is designed to estimate the saturation function for dealing with the input saturation problem. Then, a novel adaptive cascade trajectory tracking control scheme is designed. An adaptive neural network-based terminal sliding control law is proposed for producing the generalized force/moment in real-time, the asymptotic stability of this adaptive control system is proven by Lyapunov theory, and a quasi-newton distribution law is designed to determine the optimum tire forces that guarantee the actual generalized forces/moment are close to the desired values. Finally, simulation results demonstrate the effectiveness of the proposed control scheme.

关键词： autonomous electric vehicles input saturation over-actuated distribution adaptive terminal sliding control