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Wenqi Lu
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年份
Short-term prediction of lane-level traffic speeds: A fusion deep learning model
Y Gu, W Lu, L Qin, M Li, Z Shao
Transportation research part C: emerging technologies 106, 1-16, 2019
1602019
An improved Bayesian combination model for short-term traffic prediction with deep learning
Y Gu, W Lu, X Xu, L Qin, Z Shao, H Zhang
IEEE Transactions on Intelligent Transportation Systems 21 (3), 1332-1342, 2020
1412020
A model of traffic accident prediction based on convolutional neural network
W Lu, D Luo, M Yan
2017 2nd IEEE international conference on intelligent transportation …, 2017
722017
A hybrid model for lane-level traffic flow forecasting based on complete ensemble empirical mode decomposition and extreme gradient boosting
W Lu, Y Rui, Z Yi, B Ran, Y Gu
IEEE Access 8, 42042-42054, 2020
442020
Lane-level traffic speed forecasting: a novel mixed deep learning model
W Lu, Y Rui, B Ran
IEEE Transactions on Intelligent Transportation Systems 23 (4), 3601 - 3612, 2022
322022
Intelligent back-looking distance driver model and stability analysis for connected and automated vehicles
Z Yi, W Lu, L Xu, X Qu, B Ran
Journal of Central South University 27 (11), 3499-3512, 2020
212020
Traffic speed forecasting for urban roads: A deep ensemble neural network model
W Lu, Z Yi, R Wu, Y Rui, B Ran
Physica A: Statistical Mechanics and its Applications 593, 126988, 2022
152022
A dynamic control method for cavs platoon based on the MPC framework and safety potential field model
L Li, J Gan, X Qu, W Lu, P Mao, B Ran
KSCE Journal of Civil Engineering 25 (5), 1874-1886, 2021
142021
Efficient deep learning based method for multi‐lane speed forecasting: a case study in Beijing
W Lu, Z Yi, W Liu, Y Gu, Y Rui, B Ran
IET Intelligent Transport Systems 14 (14), 2073-2082, 2020
132020
A bidirectional car-following model considering distance balance between adjacent vehicles
Z Yi, W Lu, X Qu, J Gan, L Li, B Ran
Physica A: Statistical Mechanics and its Applications 603, 127606, 2022
92022
A deep learning framework for cycling maneuvers classification
Y Gu, Z Shao, L Qin, W Lu, M Li
IEEE Access 7, 28799-28809, 2019
82019
Displacement data imputation in urban internet of things system based on tucker decomposition with l2 regularization
L Li, X Lin, H Liu, W Lu, B Zhou, J Zhu
IEEE Internet of Things Journal 9 (15), 13315-13326, 2022
72022
An attention-based approach for traffic conditions forecasting considering spatial-temporal features
L Tao, Y Gu, W Lu, X Rui, T Zhou, Y Ding
2020 IEEE 5th International Conference on Intelligent Transportation …, 2020
72020
TD3LVSL: A lane-level variable speed limit approach based on twin delayed deep deterministic policy gradient in a connected automated vehicle environment
W Lu, Z Yi, Y Gu, Y Rui, B Ran
Transportation Research Part C: Emerging Technologies 153, 104221, 2023
62023
Short-term forecasting of supply-demand gap under online car-hailing services based on deep learning
GU Yuan-li, LI Meng, RUI Xiao-ping, LU Wen-qi, W Shuo
Journal of Transportation Systems Engineering and Information Technology 19 …, 2019
62019
Learning Car-Following Behaviors for a Connected Automated Vehicle System: An Improved Sequence-to-Sequence Deep Learning Model
W Lu, Z Yi, B Liang, Y Rui, B Ran
IEEE Access 11, 28076-28089, 2023
52023
Controlling the connected vehicle with bi-directional information: improved car-following models and stability analysis
Z Yi, W Lu, X Qu, L Li, P Mao, B Ran
Sensors 21 (24), 8322, 2021
52021
Improving the safe operation of platoon lane changing for connected automated vehicles: A novel field-driven approach
R Wu, L Li, W Lu, Y Rui, B Ran
Applied Sciences 11 (16), 7287, 2021
52021
Deploying roadside unit efficiently in VANETs: A multi-objective delay-based optimization strategy using Lagrangian relaxation
B Liang, W Lu, B Ran
IEEE Transactions on Intelligent Transportation Systems, 2023
32023
Target encirclement of moving ride-hailing vehicle under uncertain environment: A multi-vehicle mutual rescue model
D Luo, J Wang, W Lu, L Chen, Z Gao, J Dong
Computers & Operations Research 146, 105901, 2022
32022
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