以第一作者或通信作者发表论文13篇，其中SCI/EI 11篇 （中科院Top论文8篇），详细论文见谷歌学术：https://scholar.google.com/citations?user=74OTWUEAAAAJ&hl=zh-CN。
[1] Lisheng Jin, Tao Huang (通信作者), et al. Vehicle Trajectory Prediction Based on Driver’s Cognitive Mechanism, IEEE Internet of Things Journal,12(21):45277 - 45287,2025. (中科院2区，Top)
[2]Tao Huang, Rui Fu, Qinyu Sun, et al. Toward Human-vehicle collaboration for automated vehicles: A review and perspective [J]. IEEE Transactions on Intelligent Transportation Systems,26(5):5649 - 5673,2025. (中科院1区，Top)
[3]Tao Huang, Rui Fu, Qinyu Sun, et al. Driver lane change intention prediction based on topological graph constructed by driver behaviors and traffic context for human-machine co-driving system [J]. Transportation Research Part C: Emerging Technologies, 2024, 160: 104497. (中科院1区，Top)
[4]Rui Fu, Tao Huang (通信作者), Mingyue Li, et al. A multimodal deep neural network for prediction of the driver’s focus of attention based on anthropomorphic attention mechanism and prior knowledge [J]. Expert Systems with Applications, 2023, 214: 119157.(中科院1区，Top)
[5]Tao Huang, Rui Fu. Driver distraction detection based on the true driver’s focus of attention [J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(10): 19374-19386. (中科院1区，Top)
[6]Tao Huang, Rui Fu. Prediction of the driver’s focus of attention based on feature visualization of a deep autonomous driving model [J]. Knowledge-Based Systems, 2022, 251: 109006. (中科院1区，Top)
[7]Tao Huang, Rui Fu, Qinyu Sun. Driver’s mobile phone usage detection using guided learning based on attention features and prior knowledge [J]. Expert Systems with Applications, 2022, 206: 117877. (中科院1区，Top)
[8]Tao Huang, Rui Fu, Yunxing Chen, et al. Real-time driver behavior detection based on deep deformable inverted residual network with an attention mechanism for human-vehicle co-driving system [J]. IEEE Transactions on Vehicular Technology, 2022, 71(12): 12475-12488. (中科院2区，Top)
[9]Tao Huang, Rui Fu, Yunxing Chen. Deep driver behavior detection model based on human brain consolidated learning for shared autonomy systems [J]. Measurement, 2021, 179: 109463. (中科院2区)
[10]Tao Huang, Shuanfeng Zhao, et al. Unsupervised monocular depth estimation based on residual neural network of coarse-refined feature extractions for drone [J]. Electronics, 2019, 8(10): 1179.
[11]郭应时,黄涛(通信作者).基于注意力机制的多模态自动驾驶行为决策模型[J].中国公路学报,2022,35(09):141-156.
[12]黄涛,赵栓峰,拜云瑞,等.面向无人机飞控平台的实时道路目标深度神经网络检测方法[J].激光与光电子学进展,2020,57(04):303-311.
[13]赵栓峰,黄涛(通信作者),许倩,等.面向无人机自主飞行的无监督单目视觉深度估计[J].激光与光电子学进展,2020,57(02):145-154.
以第一作者或通信作者发表论文13篇，其中SCI/EI 11篇 （中科院Top论文8篇），详细论文见谷歌学术：https://scholar.google.com/citations?user=74OTWUEAAAAJ&hl=zh-CN。
[1] Lisheng Jin, Tao Huang (通信作者), et al. Vehicle Trajectory Prediction Based on Driver’s Cognitive Mechanism, IEEE Internet of Things Journal,12(21):45277 - 45287,2025. (中科院2区，Top)
[2]Tao Huang, Rui Fu, Qinyu Sun, et al. Toward Human-vehicle collaboration for automated vehicles: A review and perspective [J]. IEEE Transactions on Intelligent Transportation Systems,26(5):5649 - 5673,2025. (中科院1区，Top)
[3]Tao Huang, Rui Fu, Qinyu Sun, et al. Driver lane change intention prediction based on topological graph constructed by driver behaviors and traffic context for human-machine co-driving system [J]. Transportation Research Part C: Emerging Technologies, 2024, 160: 104497. (中科院1区，Top)
[4]Rui Fu, Tao Huang (通信作者), Mingyue Li, et al. A multimodal deep neural network for prediction of the driver’s focus of attention based on anthropomorphic attention mechanism and prior knowledge [J]. Expert Systems with Applications, 2023, 214: 119157.(中科院1区，Top)
[5]Tao Huang, Rui Fu. Driver distraction detection based on the true driver’s focus of attention [J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(10): 19374-19386. (中科院1区，Top)
[6]Tao Huang, Rui Fu. Prediction of the driver’s focus of attention based on feature visualization of a deep autonomous driving model [J]. Knowledge-Based Systems, 2022, 251: 109006. (中科院1区，Top)
[7]Tao Huang, Rui Fu, Qinyu Sun. Driver’s mobile phone usage detection using guided learning based on attention features and prior knowledge [J]. Expert Systems with Applications, 2022, 206: 117877. (中科院1区，Top)
[8]Tao Huang, Rui Fu, Yunxing Chen, et al. Real-time driver behavior detection based on deep deformable inverted residual network with an attention mechanism for human-vehicle co-driving system [J]. IEEE Transactions on Vehicular Technology, 2022, 71(12): 12475-12488. (中科院2区，Top)
[9]Tao Huang, Rui Fu, Yunxing Chen. Deep driver behavior detection model based on human brain consolidated learning for shared autonomy systems [J]. Measurement, 2021, 179: 109463. (中科院2区)
[10]Tao Huang, Shuanfeng Zhao, et al. Unsupervised monocular depth estimation based on residual neural network of coarse-refined feature extractions for drone [J]. Electronics, 2019, 8(10): 1179.
[11]郭应时,黄涛(通信作者).基于注意力机制的多模态自动驾驶行为决策模型[J].中国公路学报,2022,35(09):141-156.
[12]黄涛,赵栓峰,拜云瑞,等.面向无人机飞控平台的实时道路目标深度神经网络检测方法[J].激光与光电子学进展,2020,57(04):303-311.
[13]赵栓峰,黄涛(通信作者),许倩,等.面向无人机自主飞行的无监督单目视觉深度估计[J].激光与光电子学进展,2020,57(02):145-154.
以第一作者或通信作者发表论文13篇，其中SCI/EI 11篇 （中科院Top论文8篇），详细论文见谷歌学术：https://scholar.google.com/citations?user=74OTWUEAAAAJ&hl=zh-CN。
[1] Lisheng Jin, Tao Huang (通信作者), et al. Vehicle Trajectory Prediction Based on Driver’s Cognitive Mechanism, IEEE Internet of Things Journal,12(21):45277 - 45287,2025. (中科院2区，Top)
[2]Tao Huang, Rui Fu, Qinyu Sun, et al. Toward Human-vehicle collaboration for automated vehicles: A review and perspective [J]. IEEE Transactions on Intelligent Transportation Systems,26(5):5649 - 5673,2025. (中科院1区，Top)
[3]Tao Huang, Rui Fu, Qinyu Sun, et al. Driver lane change intention prediction based on topological graph constructed by driver behaviors and traffic context for human-machine co-driving system [J]. Transportation Research Part C: Emerging Technologies, 2024, 160: 104497. (中科院1区，Top)
[4]Rui Fu, Tao Huang (通信作者), Mingyue Li, et al. A multimodal deep neural network for prediction of the driver’s focus of attention based on anthropomorphic attention mechanism and prior knowledge [J]. Expert Systems with Applications, 2023, 214: 119157.(中科院1区，Top)
[5]Tao Huang, Rui Fu. Driver distraction detection based on the true driver’s focus of attention [J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(10): 19374-19386. (中科院1区，Top)
[6]Tao Huang, Rui Fu. Prediction of the driver’s focus of attention based on feature visualization of a deep autonomous driving model [J]. Knowledge-Based Systems, 2022, 251: 109006. (中科院1区，Top)
[7]Tao Huang, Rui Fu, Qinyu Sun. Driver’s mobile phone usage detection using guided learning based on attention features and prior knowledge [J]. Expert Systems with Applications, 2022, 206: 117877. (中科院1区，Top)
[8]Tao Huang, Rui Fu, Yunxing Chen, et al. Real-time driver behavior detection based on deep deformable inverted residual network with an attention mechanism for human-vehicle co-driving system [J]. IEEE Transactions on Vehicular Technology, 2022, 71(12): 12475-12488. (中科院2区，Top)
[9]Tao Huang, Rui Fu, Yunxing Chen. Deep driver behavior detection model based on human brain consolidated learning for shared autonomy systems [J]. Measurement, 2021, 179: 109463. (中科院2区)
[10]Tao Huang, Shuanfeng Zhao, et al. Unsupervised monocular depth estimation based on residual neural network of coarse-refined feature extractions for drone [J]. Electronics, 2019, 8(10): 1179.
[11]郭应时,黄涛(通信作者).基于注意力机制的多模态自动驾驶行为决策模型[J].中国公路学报,2022,35(09):141-156.
[12]黄涛,赵栓峰,拜云瑞,等.面向无人机飞控平台的实时道路目标深度神经网络检测方法[J].激光与光电子学进展,2020,57(04):303-311.
[13]赵栓峰,黄涛(通信作者),许倩,等.面向无人机自主飞行的无监督单目视觉深度估计[J].激光与光电子学进展,2020,57(02):145-154.
以第一作者或通信作者发表论文13篇，其中SCI/EI 11篇 （中科院Top论文8篇），详细论文见谷歌学术：https://scholar.google.com/citations?user=74OTWUEAAAAJ&hl=zh-CN。
[1] Lisheng Jin, Tao Huang (通信作者), et al. Vehicle Trajectory Prediction Based on Driver’s Cognitive Mechanism, IEEE Internet of Things Journal,12(21):45277 - 45287,2025. (中科院2区，Top)
[2]Tao Huang, Rui Fu, Qinyu Sun, et al. Toward Human-vehicle collaboration for automated vehicles: A review and perspective [J]. IEEE Transactions on Intelligent Transportation Systems,26(5):5649 - 5673,2025. (中科院1区，Top)
[3]Tao Huang, Rui Fu, Qinyu Sun, et al. Driver lane change intention prediction based on topological graph constructed by driver behaviors and traffic context for human-machine co-driving system [J]. Transportation Research Part C: Emerging Technologies, 2024, 160: 104497. (中科院1区，Top)
[4]Rui Fu, Tao Huang (通信作者), Mingyue Li, et al. A multimodal deep neural network for prediction of the driver’s focus of attention based on anthropomorphic attention mechanism and prior knowledge [J]. Expert Systems with Applications, 2023, 214: 119157.(中科院1区，Top)
[5]Tao Huang, Rui Fu. Driver distraction detection based on the true driver’s focus of attention [J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(10): 19374-19386. (中科院1区，Top)
[6]Tao Huang, Rui Fu. Prediction of the driver’s focus of attention based on feature visualization of a deep autonomous driving model [J]. Knowledge-Based Systems, 2022, 251: 109006. (中科院1区，Top)
[7]Tao Huang, Rui Fu, Qinyu Sun. Driver’s mobile phone usage detection using guided learning based on attention features and prior knowledge [J]. Expert Systems with Applications, 2022, 206: 117877. (中科院1区，Top)
[8]Tao Huang, Rui Fu, Yunxing Chen, et al. Real-time driver behavior detection based on deep deformable inverted residual network with an attention mechanism for human-vehicle co-driving system [J]. IEEE Transactions on Vehicular Technology, 2022, 71(12): 12475-12488. (中科院2区，Top)
[9]Tao Huang, Rui Fu, Yunxing Chen. Deep driver behavior detection model based on human brain consolidated learning for shared autonomy systems [J]. Measurement, 2021, 179: 109463. (中科院2区)
[10]Tao Huang, Shuanfeng Zhao, et al. Unsupervised monocular depth estimation based on residual neural network of coarse-refined feature extractions for drone [J]. Electronics, 2019, 8(10): 1179.
[11]郭应时,黄涛(通信作者).基于注意力机制的多模态自动驾驶行为决策模型[J].中国公路学报,2022,35(09):141-156.
[12]黄涛,赵栓峰,拜云瑞,等.面向无人机飞控平台的实时道路目标深度神经网络检测方法[J].激光与光电子学进展,2020,57(04):303-311.
[13]赵栓峰,黄涛(通信作者),许倩,等.面向无人机自主飞行的无监督单目视觉深度估计[J].激光与光电子学进展,2020,57(02):145-154.
以第一作者或通信作者发表论文13篇，其中SCI/EI 11篇 （中科院Top论文8篇），详细论文见谷歌学术：https://scholar.google.com/citations?user=74OTWUEAAAAJ&hl=zh-CN。
[1] Lisheng Jin, Tao Huang (通信作者), et al. Vehicle Trajectory Prediction Based on Driver’s Cognitive Mechanism, IEEE Internet of Things Journal,12(21):45277 - 45287,2025. (中科院2区，Top)
[2]Tao Huang, Rui Fu, Qinyu Sun, et al. Toward Human-vehicle collaboration for automated vehicles: A review and perspective [J]. IEEE Transactions on Intelligent Transportation Systems,26(5):5649 - 5673,2025. (中科院1区，Top)
[3]Tao Huang, Rui Fu, Qinyu Sun, et al. Driver lane change intention prediction based on topological graph constructed by driver behaviors and traffic context for human-machine co-driving system [J]. Transportation Research Part C: Emerging Technologies, 2024, 160: 104497. (中科院1区，Top)
[4]Rui Fu, Tao Huang (通信作者), Mingyue Li, et al. A multimodal deep neural network for prediction of the driver’s focus of attention based on anthropomorphic attention mechanism and prior knowledge [J]. Expert Systems with Applications, 2023, 214: 119157.(中科院1区，Top)
[5]Tao Huang, Rui Fu. Driver distraction detection based on the true driver’s focus of attention [J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(10): 19374-19386. (中科院1区，Top)
[6]Tao Huang, Rui Fu. Prediction of the driver’s focus of attention based on feature visualization of a deep autonomous driving model [J]. Knowledge-Based Systems, 2022, 251: 109006. (中科院1区，Top)
[7]Tao Huang, Rui Fu, Qinyu Sun. Driver’s mobile phone usage detection using guided learning based on attention features and prior knowledge [J]. Expert Systems with Applications, 2022, 206: 117877. (中科院1区，Top)
[8]Tao Huang, Rui Fu, Yunxing Chen, et al. Real-time driver behavior detection based on deep deformable inverted residual network with an attention mechanism for human-vehicle co-driving system [J]. IEEE Transactions on Vehicular Technology, 2022, 71(12): 12475-12488. (中科院2区，Top)
[9]Tao Huang, Rui Fu, Yunxing Chen. Deep driver behavior detection model based on human brain consolidated learning for shared autonomy systems [J]. Measurement, 2021, 179: 109463. (中科院2区)
[10]Tao Huang, Shuanfeng Zhao, et al. Unsupervised monocular depth estimation based on residual neural network of coarse-refined feature extractions for drone [J]. Electronics, 2019, 8(10): 1179.
[11]郭应时,黄涛(通信作者).基于注意力机制的多模态自动驾驶行为决策模型[J].中国公路学报,2022,35(09):141-156.
[12]黄涛,赵栓峰,拜云瑞,等.面向无人机飞控平台的实时道路目标深度神经网络检测方法[J].激光与光电子学进展,2020,57(04):303-311.
[13]赵栓峰,黄涛(通信作者),许倩,等.面向无人机自主飞行的无监督单目视觉深度估计[J].激光与光电子学进展,2020,57(02):145-154.
以第一作者或通信作者发表论文13篇，其中SCI/EI 11篇 （中科院Top论文8篇），详细论文见谷歌学术：https://scholar.google.com/citations?user=74OTWUEAAAAJ&hl=zh-CN。
[1] Lisheng Jin, Tao Huang (通信作者), et al. Vehicle Trajectory Prediction Based on Driver’s Cognitive Mechanism, IEEE Internet of Things Journal,12(21):45277 - 45287,2025. (中科院2区，Top)
[2]Tao Huang, Rui Fu, Qinyu Sun, et al. Toward Human-vehicle collaboration for automated vehicles: A review and perspective [J]. IEEE Transactions on Intelligent Transportation Systems,26(5):5649 - 5673,2025. (中科院1区，Top)
[3]Tao Huang, Rui Fu, Qinyu Sun, et al. Driver lane change intention prediction based on topological graph constructed by driver behaviors and traffic context for human-machine co-driving system [J]. Transportation Research Part C: Emerging Technologies, 2024, 160: 104497. (中科院1区，Top)
[4]Rui Fu, Tao Huang (通信作者), Mingyue Li, et al. A multimodal deep neural network for prediction of the driver’s focus of attention based on anthropomorphic attention mechanism and prior knowledge [J]. Expert Systems with Applications, 2023, 214: 119157.(中科院1区，Top)
[5]Tao Huang, Rui Fu. Driver distraction detection based on the true driver’s focus of attention [J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(10): 19374-19386. (中科院1区，Top)
[6]Tao Huang, Rui Fu. Prediction of the driver’s focus of attention based on feature visualization of a deep autonomous driving model [J]. Knowledge-Based Systems, 2022, 251: 109006. (中科院1区，Top)
[7]Tao Huang, Rui Fu, Qinyu Sun. Driver’s mobile phone usage detection using guided learning based on attention features and prior knowledge [J]. Expert Systems with Applications, 2022, 206: 117877. (中科院1区，Top)
[8]Tao Huang, Rui Fu, Yunxing Chen, et al. Real-time driver behavior detection based on deep deformable inverted residual network with an attention mechanism for human-vehicle co-driving system [J]. IEEE Transactions on Vehicular Technology, 2022, 71(12): 12475-12488. (中科院2区，Top)
[9]Tao Huang, Rui Fu, Yunxing Chen. Deep driver behavior detection model based on human brain consolidated learning for shared autonomy systems [J]. Measurement, 2021, 179: 109463. (中科院2区)
[10]Tao Huang, Shuanfeng Zhao, et al. Unsupervised monocular depth estimation based on residual neural network of coarse-refined feature extractions for drone [J]. Electronics, 2019, 8(10): 1179.
[11]郭应时,黄涛(通信作者).基于注意力机制的多模态自动驾驶行为决策模型[J].中国公路学报,2022,35(09):141-156.
[12]黄涛,赵栓峰,拜云瑞,等.面向无人机飞控平台的实时道路目标深度神经网络检测方法[J].激光与光电子学进展,2020,57(04):303-311.
[13]赵栓峰,黄涛(通信作者),许倩,等.面向无人机自主飞行的无监督单目视觉深度估计[J].激光与光电子学进展,2020,57(02):145-154.
以第一作者或通信作者发表论文13篇，其中SCI/EI 11篇 （中科院Top论文8篇），详细论文见谷歌学术：https://scholar.google.com/citations?user=74OTWUEAAAAJ&hl=zh-CN。
[1] Lisheng Jin, Tao Huang (通信作者), et al. Vehicle Trajectory Prediction Based on Driver’s Cognitive Mechanism, IEEE Internet of Things Journal,12(21):45277 - 45287,2025. (中科院2区，Top)
[2]Tao Huang, Rui Fu, Qinyu Sun, et al. Toward Human-vehicle collaboration for automated vehicles: A review and perspective [J]. IEEE Transactions on Intelligent Transportation Systems,26(5):5649 - 5673,2025. (中科院1区，Top)
[3]Tao Huang, Rui Fu, Qinyu Sun, et al. Driver lane change intention prediction based on topological graph constructed by driver behaviors and traffic context for human-machine co-driving system [J]. Transportation Research Part C: Emerging Technologies, 2024, 160: 104497. (中科院1区，Top)
[4]Rui Fu, Tao Huang (通信作者), Mingyue Li, et al. A multimodal deep neural network for prediction of the driver’s focus of attention based on anthropomorphic attention mechanism and prior knowledge [J]. Expert Systems with Applications, 2023, 214: 119157.(中科院1区，Top)
[5]Tao Huang, Rui Fu. Driver distraction detection based on the true driver’s focus of attention [J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(10): 19374-19386. (中科院1区，Top)
[6]Tao Huang, Rui Fu. Prediction of the driver’s focus of attention based on feature visualization of a deep autonomous driving model [J]. Knowledge-Based Systems, 2022, 251: 109006. (中科院1区，Top)
[7]Tao Huang, Rui Fu, Qinyu Sun. Driver’s mobile phone usage detection using guided learning based on attention features and prior knowledge [J]. Expert Systems with Applications, 2022, 206: 117877. (中科院1区，Top)
[8]Tao Huang, Rui Fu, Yunxing Chen, et al. Real-time driver behavior detection based on deep deformable inverted residual network with an attention mechanism for human-vehicle co-driving system [J]. IEEE Transactions on Vehicular Technology, 2022, 71(12): 12475-12488. (中科院2区，Top)
[9]Tao Huang, Rui Fu, Yunxing Chen. Deep driver behavior detection model based on human brain consolidated learning for shared autonomy systems [J]. Measurement, 2021, 179: 109463. (中科院2区)
[10]Tao Huang, Shuanfeng Zhao, et al. Unsupervised monocular depth estimation based on residual neural network of coarse-refined feature extractions for drone [J]. Electronics, 2019, 8(10): 1179.
[11]郭应时,黄涛(通信作者).基于注意力机制的多模态自动驾驶行为决策模型[J].中国公路学报,2022,35(09):141-156.
[12]黄涛,赵栓峰,拜云瑞,等.面向无人机飞控平台的实时道路目标深度神经网络检测方法[J].激光与光电子学进展,2020,57(04):303-311.
[13]赵栓峰,黄涛(通信作者),许倩,等.面向无人机自主飞行的无监督单目视觉深度估计[J].激光与光电子学进展,2020,57(02):145-154.
