Chao Lu
Orcid: 0000-0001-7517-2868Affiliations:
- Beijing Institute of Technology, School of Mechanical Engineering, China
- University of Leeds, UK (PhD 2015)
According to our database1,
Chao Lu
authored at least 38 papers
between 2017 and 2024.
Collaborative distances:
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Bibliography
2024
Object-Level Attention Prediction for Drivers in the Information-Rich Traffic Environment.
IEEE Trans. Ind. Electron., June, 2024
Continual Interactive Behavior Learning With Traffic Divergence Measurement: A Dynamic Gradient Scenario Memory Approach.
IEEE Trans. Intell. Transp. Syst., March, 2024
2023
Fusion of Gaze and Scene Information for Driving Behaviour Recognition: A Graph-Neural-Network- Based Framework.
IEEE Trans. Intell. Transp. Syst., August, 2023
Driver-Specific Risk Recognition in Interactive Driving Scenarios Using Graph Representation.
IEEE Trans. Veh. Technol., April, 2023
Rethinking Trajectory Prediction in Real-World Applications: An Online Task-Free Continual Learning Perspective.
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2023
A Learning-Based Controller for Trajectory Tracking of Autonomous Vehicles in Complex and Uncertain Scenarios.
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2023
Towards Online Risk Assessment for Human-Robot Interaction: A Data-Driven Hamilton-Jacobi-Isaacs Reachability Approach.
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2023
2022
Instance-Level Knowledge Transfer for Data-Driven Driver Model Adaptation With Homogeneous Domains.
IEEE Trans. Intell. Transp. Syst., 2022
A Hierarchical Framework for Interactive Behaviour Prediction of Heterogeneous Traffic Participants Based on Graph Neural Network.
IEEE Trans. Intell. Transp. Syst., 2022
Integrated Path Planning for Unmanned Differential Steering Vehicles in Off-Road Environment With 3D Terrains and Obstacles.
IEEE Trans. Intell. Transp. Syst., 2022
Personalized Driver Braking Behavior Modeling in the Car-Following Scenario: An Importance-Weight-Based Transfer Learning Approach.
IEEE Trans. Ind. Electron., 2022
Leveraging Multi-stream Information Fusion for Trajectory Prediction in Low-illumination Scenarios: A Multi-channel Graph Convolutional Approach.
CoRR, 2022
An Ensemble Learning Framework for Vehicle Trajectory Prediction in Interactive Scenarios.
Proceedings of the 2022 IEEE Intelligent Vehicles Symposium, 2022
Adaptive Decision Making at the Intersection for Autonomous Vehicles Based on Skill Discovery.
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2022
2021
Lateral and Longitudinal Driving Behavior Prediction Based on Improved Deep Belief Network.
Sensors, 2021
Prediction of Pedestrian Spatiotemporal Risk Levels for Intelligent Vehicles: A Data-driven Approach.
CoRR, 2021
Life-Long Multi-Task Learning of Adaptive Path Tracking Policy for Autonomous Vehicle.
CoRR, 2021
2020
Early Recognition of Driving Intention for Lane Change Based on Recurrent Hidden Semi-Markov Model.
IEEE Trans. Veh. Technol., 2020
Importance Weighted Gaussian Process Regression for Transferable Driver Behaviour Learning in the Lane Change Scenario.
IEEE Trans. Veh. Technol., 2020
Transfer Learning for Driver Model Adaptation in Lane-Changing Scenarios Using Manifold Alignment.
IEEE Trans. Intell. Transp. Syst., 2020
A Cooperative Driving Strategy Based on Velocity Prediction for Connected Vehicles With Robust Path-Following Control.
IEEE Internet Things J., 2020
Driver Behavior Modelling at the Urban Intersection via Canonical Correlation Analysis.
CoRR, 2020
Proceedings of the IEEE Intelligent Vehicles Symposium, 2020
Hierarchical Reinforcement Learning Combined with Motion Primitives for Automated Overtaking.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2020
2019
Virtual-to-Real Knowledge Transfer for Driving Behavior Recognition: Framework and a Case Study.
IEEE Trans. Veh. Technol., 2019
A Time-Efficient Approach for Decision-Making Style Recognition in Lane-Changing Behavior.
IEEE Trans. Hum. Mach. Syst., 2019
A Personalized Behavior Learning System for Human-Like Longitudinal Speed Control of Autonomous Vehicles.
Sensors, 2019
Transferable Driver Behavior Learning via Distribution Adaption in the Lane Change Scenario.
Proceedings of the 2019 IEEE Intelligent Vehicles Symposium, 2019
Proceedings of the 2019 IEEE Intelligent Transportation Systems Conference, 2019
Proceedings of the 2019 IEEE Intelligent Transportation Systems Conference, 2019
A Comparative Study on Transferable Driver Behavior Learning Methods in the Lane-Changing Scenario.
Proceedings of the 2019 IEEE Intelligent Transportation Systems Conference, 2019
2018
Hybrid-Learning-Based Classification and Quantitative Inference of Driver Braking Intensity of an Electrified Vehicle.
IEEE Trans. Veh. Technol., 2018
IEEE Trans. Veh. Technol., 2018
Learning and Generalizing Motion Primitives From Driving Data for Path-Tracking Applications.
Proceedings of the 2018 IEEE Intelligent Vehicles Symposium, 2018
Development and Evaluation of Two Learning-Based Personalized Driver Models for Pure Pursuit Path-Tracking Behaviors.
Proceedings of the 2018 IEEE Intelligent Vehicles Symposium, 2018
Transfer Learning for Driver Model Adaptation via Modified Local Procrustes Analysis.
Proceedings of the 2018 IEEE Intelligent Vehicles Symposium, 2018
2017
Proceedings of the IEEE Intelligent Vehicles Symposium, 2017
Speed and steering angle prediction for intelligent vehicles based on deep belief network.
Proceedings of the 20th IEEE International Conference on Intelligent Transportation Systems, 2017