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学者姓名：黄炜
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从控制架构与驾驶权决策出发,阐述了人机共驾的研究现状以及发展趋势;在控制架构方面,分析了切换控制架构和共享控制架构的特点和应用范围,并提出了混杂控制架构概念;在驾驶权决策方面,讨论了不同驾驶权决策方法对不同来源、不同性质信息的使用方式,概括了执行驾驶权分配时直接和间接共享控制方式所涉及的方法,梳理了策略层决策与执行层决策的研究角度与方法.研究结果表明:针对高阶自动驾驶上路运行安全问题,发展混杂控制架构对安全员干预场景下的系统动态进行描述有利于避免模型失配,从而为控制性能优化和稳定性设计提供了基础;通过融合全息态势感知与数据智能的方式收集和整合多个信息源的数据,能够更加全面地理解人机共驾系统中诸多要素的动态变化并做出最优驾驶权决策;相较于直接共享控制,间接共享控制能避免人机控制流直接对抗,但是其动态驾驶权分配执行层面不仅需要考虑人机之间的冲突反馈,还需要确保合理的交互体验以体现间接共享控制的优势;基于智能体的策略层决策方法并不依赖于数学模型精度,能够自适应环境的动态变化;基于博弈论的执行层决策方法通过建模人机交互过程能够增强驾驶权决策系统的可控性和可解释性;未来的人机共驾系统设计应进一步优化交互体验,关注发展平等共融的人机关系,并提高控制系统的鲁棒性以及驾驶权决策的可解释性和适应性.
Keyword ：
交互协同 交互协同 人机共驾 人机共驾 博弈论 博弈论 强化学习 强化学习 混杂控制 混杂控制 驾驶权 驾驶权
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| GB/T 7714 | 黄炜 , 黄起鹏 . 人机共驾控制架构与驾驶权决策研究综述 [J]. | 交通运输工程学报 , 2025 , 25 (1) : 48-65 . |
| MLA | 黄炜 等. "人机共驾控制架构与驾驶权决策研究综述" . | 交通运输工程学报 25 . 1 (2025) : 48-65 . |
| APA | 黄炜 , 黄起鹏 . 人机共驾控制架构与驾驶权决策研究综述 . | 交通运输工程学报 , 2025 , 25 (1) , 48-65 . |
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针对自动驾驶中对行人等较小目标及被遮挡目标检测精度较低的问题,提出一种基于自注意力机制的融合图像和点云的三维目标检测算法,在基于原始点云数据处理的F-PointNet网络上进行改进.首先,通过在点云特征提取网络中引入两层基于Transformer的自注意力机制模块,兼顾点云全局特征和局部特征,提高三维目标的检测精度.其次,在损失函数中引入弹性网络正则化权重衰减项,提高模型的泛化能力,实现更高精度的收敛.基于KITTI数据集进行对比实验,结果表明,引入自注意机制和弹性网络正则化后,在简单、中等和困难 3 种难度情境下,与初始模型对比,行人的检测精度分别提高6.47%、6.31%和5.61%,骑行人的检测精度分别提高 15.34%、12.88%和 11.79%.
Keyword ：
三维目标检测 三维目标检测 图像 图像 点云 点云 自注意力机制 自注意力机制
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| GB/T 7714 | 林晓鹏 , 彭育辉 , 黄炜 et al. 自注意力机制下融合图像和点云的三维目标检测 [J]. | 福州大学学报（自然科学版） , 2025 , 53 (2) : 168-176 . |
| MLA | 林晓鹏 et al. "自注意力机制下融合图像和点云的三维目标检测" . | 福州大学学报（自然科学版） 53 . 2 (2025) : 168-176 . |
| APA | 林晓鹏 , 彭育辉 , 黄炜 , 陈文强 . 自注意力机制下融合图像和点云的三维目标检测 . | 福州大学学报（自然科学版） , 2025 , 53 (2) , 168-176 . |
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This paper concerns with the development of computationally efficient lane keeping control method for the autonomous vehicles. To obtain autonomous lane keeping, model predictive control (MPC) scheme was intensively investigated in the previous studies owing to its inherent advantage of dealing with constrained multivariable systems. However, the tradeoff problem between the good tracking performance and the low computational complexity is inevitably raised in developing of MPC-based lane keeping technology. To alleviate the conflict between performance and cost, an on-board MPC with fuzzy preview distance is designed in this study. A linear system dynamics model is used in the MPC design to reduce the computational cost, and a fuzzy logic algorithm is developed to select an appropriate preview distance for enhancing the MPC performance. Further, hardware-in-the-loop test is adopted to explore the effectiveness and efficiency of the proposed control method. In comparison to the proportional-integral controller, the experimental results show that the MPC is more sensitive to the selective value of fixed preview distance. Since the significant impact of preview distance selection on the MPC-based lane keeping performance, the fuzzy logic algorithm is of the essence in terms of selecting the appropriate preview distance for MPC enhancement under different vehicle speed and road curvature. Eventually, experimental results validate that the proposed fuzzy preview distance algorithm can effectively improve the MPC-based lane keeping performance for autonomous vehicles subject to limited computational resource.
Keyword ：
autonomous vehicle autonomous vehicle fuzzy logic fuzzy logic Lane keeping Lane keeping model predictive control model predictive control preview distance preview distance
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| GB/T 7714 | Huang, Wei , Xia, Wei , Wu, Zhengxiao et al. On-board model predictive control for autonomous lane keeping with fuzzy preview distance: Design and experiment [J]. | PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING , 2024 . |
| MLA | Huang, Wei et al. "On-board model predictive control for autonomous lane keeping with fuzzy preview distance: Design and experiment" . | PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING (2024) . |
| APA | Huang, Wei , Xia, Wei , Wu, Zhengxiao , Liu, Xinjie , Shi, Tianhua , Peng, Yuhui et al. On-board model predictive control for autonomous lane keeping with fuzzy preview distance: Design and experiment . | PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING , 2024 . |
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Trajectory following is an important function of autonomous vehicles. To enable a four-wheel independent drive electric vehicle to precisely follow a predefined or real-time generated trajectory with good lateral stability and ride comfort at high velocity, a model predictive control (MPC) scheme with feedback compensation considering model mismatch is proposed in this paper to coordinate the direct yaw-moment control and active front steering. The system input signal computed by model predictive control is corrected by the feedback compensation to cope with the model mismatch existing between the controlled vehicle and the nominal model. Moreover, co-simulation is carried out between the software MATLAB/Simulink and Carsim to verify the proposed method. In comparison, the integration of the direct yaw-moment control and active front steering through model predictive control can overcome the non-smooth problem of vehicle dynamics while implementing the active front steering only. However, the value of the external yaw moment computed by the model predictive controller might be too large due to the predictive error in extreme situations, which could endanger the vehicle. The results reveal that the proposed model predictive control scheme with feedback compensation can effectively compensate the front steering angle and enhance the control effect. Therefore, it can significantly improve the trajectory following accuracy and yaw stability.
Keyword ：
Autonomous vehicle Autonomous vehicle direct yaw-moment control direct yaw-moment control feedback compensation feedback compensation model predictive control model predictive control trajectory following trajectory following
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| GB/T 7714 | Ye, Xingyu , Zhu, Shaopeng , Ao, Di et al. Nonlinear model predictive trajectory following control with feedback compensation for autonomous four-wheel independent drive electric vehicles [J]. | PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING , 2024 , 238 (2-3) : 478-490 . |
| MLA | Ye, Xingyu et al. "Nonlinear model predictive trajectory following control with feedback compensation for autonomous four-wheel independent drive electric vehicles" . | PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING 238 . 2-3 (2024) : 478-490 . |
| APA | Ye, Xingyu , Zhu, Shaopeng , Ao, Di , Huang, Wei . Nonlinear model predictive trajectory following control with feedback compensation for autonomous four-wheel independent drive electric vehicles . | PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING , 2024 , 238 (2-3) , 478-490 . |
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为更好解决基于同步定位与地图构建(SLAM)地图无人车的长期定位问题,提出一种基于语义图相似匹配与候选帧的语义扫描上下文描述符,通过粗、细两步定位实现对点云场景的重定位.首先,提取点云语义和几何特征,剔除移动、可移动类对象,通过融合语义信息和拓扑关系构建语义图,以图相似度计算实现快速重定位粗匹配;其次,通过全局语义迭代最近点(ICP)方法计算点云之间的相对偏航角和水平位移,为点云配准提供良好的初始值;最后,通过语义扫描上下文生成全局语义描述符,通过对比描述符判别点云相似性,完成精准重定位.实验结果表明:所提方法相较基于语义图的地点识别方法在地点识别精度、遮挡场景和视角变化场景下精度分别提升20.10%、20.90%和20.47%.
Keyword ：
同步定位与地图构建 同步定位与地图构建 点云配准 点云配准 语义图 语义图 语义扫描上下文 语义扫描上下文 重定位 重定位
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| GB/T 7714 | 黄孝鸿 , 彭育辉 , 黄炜 . 基于语义图和语义扫描上下文的激光点云两步重定位方法 [J]. | 激光与光电子学进展 , 2024 , 61 (18) : 189-196 . |
| MLA | 黄孝鸿 et al. "基于语义图和语义扫描上下文的激光点云两步重定位方法" . | 激光与光电子学进展 61 . 18 (2024) : 189-196 . |
| APA | 黄孝鸿 , 彭育辉 , 黄炜 . 基于语义图和语义扫描上下文的激光点云两步重定位方法 . | 激光与光电子学进展 , 2024 , 61 (18) , 189-196 . |
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为提高自动泊车成功率,建立车位环境复杂度量化评价模型.以车位类型、车位线属性等 7 个指标建立车位环境复杂度评价指标体系,并提出相应的量化表征方法.针对主客观组合赋权法无法正确计算单个样本临界指标权重的问题,在层次分析法基础上,提出基于平方和归一化的权重二次分配方法.运用模糊综合评价求解车位环境复杂度,通过设计仿真测试来验证所提模型.结果表明:与层次分析法、熵权法相比,所提赋权方法能够正确对临界决定性指标赋予较大权重,避免无效权重赋予;所提模型能够正确反映车位环境复杂度变化,对泊车成功率有较大提升,为泊车位的自动选择提供一种可行的新路径.
Keyword ：
层次分析法 层次分析法 智能交通 智能交通 模糊综合评价 模糊综合评价 自动泊车系统 自动泊车系统 车位主动选择 车位主动选择
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| GB/T 7714 | 陈泽辉 , 彭育辉 , 黄炜 et al. 环境复杂度量化评价下的车位选择方法 [J]. | 福州大学学报（自然科学版） , 2024 , 52 (1) : 61-68 . |
| MLA | 陈泽辉 et al. "环境复杂度量化评价下的车位选择方法" . | 福州大学学报（自然科学版） 52 . 1 (2024) : 61-68 . |
| APA | 陈泽辉 , 彭育辉 , 黄炜 , 姚宇捷 , 吴庆 , 何维堃 . 环境复杂度量化评价下的车位选择方法 . | 福州大学学报（自然科学版） , 2024 , 52 (1) , 61-68 . |
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A novel hierarchical direct yaw moment controller is designed to enhance the lateral stability of the four-wheel-drive electric vehicle. The adaptive sliding mode control (ASMC) technique in the upper-layer controller is employed to compute an additional yaw moment. The lower-layer controller distributes this yaw moment into each independent wheel by utilizing model predictive control allocation (MPCA). The proposed MPCA aims to mitigate the performance deterioration induced by in-wheel motor dynamics and optimize the power consumption stemming from the additional yaw moment. Co-simulation and hardware-in-the-loop (HIL) test is conducted to verify the performance of the proposed controller. Validation results show that the proposed hierarchical ASMC-MPCA controller outperforms the sliding mode control MPCA (SMC-MPCA) and the integrated nonlinear model predictive control (NMPC) with the lowest root-mean-square errors ( RMSE s ) of yaw rate, sideslip angle, lateral deviation, and lowest power consumption. Additionally, the chattering phenomenon in SMC-MPCA can be suppressed effectively by adaptively estimating the parameter uncertainties. The proposed ASMC-MPCA controller also consumes less computational resources than the NMPC and SMC-MPCA, which indicates that the ASMC-MPCA is more suitable for an automotive onboard controller. The comparison between hierarchical and integrated controller frameworks also shows that the hierarchical framework is more suitable for production vehicles under non-powerful vehicle control units.
Keyword ：
Adaptive sliding mode control Adaptive sliding mode control direct yaw moment direct yaw moment four-wheel driving electric vehicle four-wheel driving electric vehicle lateral stability lateral stability model predictive control allocation model predictive control allocation power consumption power consumption
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| GB/T 7714 | Ao, Di , Wong, Pak Kin , Huang, Wei . Model predictive control allocation based on adaptive sliding mode control strategy for enhancing the lateral stability of four-wheel-drive electric vehicles [J]. | PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING , 2023 , 238 (6) : 1514-1534 . |
| MLA | Ao, Di et al. "Model predictive control allocation based on adaptive sliding mode control strategy for enhancing the lateral stability of four-wheel-drive electric vehicles" . | PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING 238 . 6 (2023) : 1514-1534 . |
| APA | Ao, Di , Wong, Pak Kin , Huang, Wei . Model predictive control allocation based on adaptive sliding mode control strategy for enhancing the lateral stability of four-wheel-drive electric vehicles . | PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING , 2023 , 238 (6) , 1514-1534 . |
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为提高复杂环境下自动垂直泊车的安全性和成功率,提出一种基于多项式曲线优化的垂直泊车路径规划方法和跟踪控制策略.首先,基于直线-圆弧路径下逆向泊车的方法,计算垂直泊车可行起始点范围.其次,综合考虑车辆位置结构和道路边界约束,以多项式为基函数、泊车终点姿态角最小为目标,建立多约束非线性规划路径函数模型,利用粒子群算法求解垂直泊车路径.最后,结合模糊神经网络控制方法,设计路径跟踪控制器.构建Simulink/CarSim仿真模型,对所提路径规划方法和跟踪策略进行仿真,结果验证了所提泊车路径规划和跟踪控制策略的可行性和有效性.
Keyword ：
垂直泊车 垂直泊车 多项式曲线 多项式曲线 跟踪控制 跟踪控制 路径规划 路径规划
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| GB/T 7714 | 江铭 , 彭育辉 , 黄炜 et al. 多项式曲线优化的垂直泊车路径规划与跟踪 [J]. | 福州大学学报（自然科学版） , 2023 , 51 (1) : 76-82 . |
| MLA | 江铭 et al. "多项式曲线优化的垂直泊车路径规划与跟踪" . | 福州大学学报（自然科学版） 51 . 1 (2023) : 76-82 . |
| APA | 江铭 , 彭育辉 , 黄炜 , 徐德强 . 多项式曲线优化的垂直泊车路径规划与跟踪 . | 福州大学学报（自然科学版） , 2023 , 51 (1) , 76-82 . |
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This paper studies the distributed consensus protocol for the connected vehicle platoon with heterogeneous time-varying delays and switching topologies. A third-order dynamics model with powertrain inertial lag is proposed to characterize the node longitudinal dynamics of vehicles in platoon. A novel distributed adaptive consensus protocol considering the time-varying delays and the random switched inter-vehicular communication topologies is designed to stabilize the heterogeneous vehicle platoon in the presence of external disturbance. The delay-range-dependent approach is used to deal with the system heterogeneous time-varying delays by considering the characteristics of the heterogeneous platoon. Directed graphs are adopted to describe the accessible information flow among vehicles. The necessary and sufficient conditions for the unified closed-loop vehicle platoon system are derived by using matrix analysis and Lyapunov-Krasovskii approach. Numerical simulations demonstrate the proposed method is effective.
Keyword ：
Connected vehicles Connected vehicles delay-range-dependent approach delay-range-dependent approach Delays Delays distributed consensus control distributed consensus control Linear matrix inequalities Linear matrix inequalities Switches Switches switching topology switching topology time-varying delay time-varying delay Time-varying systems Time-varying systems Topology Topology Vehicle dynamics Vehicle dynamics Vehicle platoon Vehicle platoon
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| GB/T 7714 | Yu, Guokuan , Wong, Pak Kin , Huang, Wei et al. Distributed Adaptive Consensus Protocol for Connected Vehicle Platoon With Heterogeneous Time-Varying Delays and Switching Topologies [J]. | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS , 2022 , 23 (10) : 17620-17631 . |
| MLA | Yu, Guokuan et al. "Distributed Adaptive Consensus Protocol for Connected Vehicle Platoon With Heterogeneous Time-Varying Delays and Switching Topologies" . | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 23 . 10 (2022) : 17620-17631 . |
| APA | Yu, Guokuan , Wong, Pak Kin , Huang, Wei , Zhao, Jing , Wang, Xian-Bo , Yang, Zhi-Xin . Distributed Adaptive Consensus Protocol for Connected Vehicle Platoon With Heterogeneous Time-Varying Delays and Switching Topologies . | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS , 2022 , 23 (10) , 17620-17631 . |
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为提高自动驾驶汽车在不同车速下轨迹追踪精度、行驶稳定性和控制器的自适应能力,设计一种基于余弦相似度和变预测时域的轨迹追踪控制器.基于线性时变模型预测控制(model predictive control,MPC)轨迹追踪控制器,提出以矩阵的余弦相似度来度量历史状态和实际状态两个矩阵的差异程度,确定预测模型的优化节点,采用模糊控制对预测时域和控制时域进行优化.进行计算机仿真对比试验,结果表明:与线性时变MPC控制器相比,可在线优化MPC控制器在不同车速下的轨迹追踪精度和车辆稳定性均有明显的提升.
Keyword ：
余弦相似度 余弦相似度 模型预测控制 模型预测控制 模糊控制 模糊控制 自动驾驶汽车 自动驾驶汽车 轨迹追踪 轨迹追踪
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| GB/T 7714 | 钟聪 , 彭育辉 , 黄炜 . 采用余弦相似度和变预测时域的汽车轨迹追踪控制 [J]. | 福州大学学报（自然科学版） , 2022 , 50 (6) : 803-810 . |
| MLA | 钟聪 et al. "采用余弦相似度和变预测时域的汽车轨迹追踪控制" . | 福州大学学报（自然科学版） 50 . 6 (2022) : 803-810 . |
| APA | 钟聪 , 彭育辉 , 黄炜 . 采用余弦相似度和变预测时域的汽车轨迹追踪控制 . | 福州大学学报（自然科学版） , 2022 , 50 (6) , 803-810 . |
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