Ruikang Luo
Orcid: 0000-0002-0939-4275
According to our database1,
Ruikang Luo
authored at least 20 papers
between 2020 and 2024.
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Bibliography
2024
LC-RSS: A Lane-Change Responsibility-Sensitive Safety Framework Based on Data-Driven Lane-Change Prediction.
IEEE Trans. Intell. Veh., January, 2024
2023
AST-GIN: Attribute-Augmented Spatiotemporal Graph Informer Network for Electric Vehicle Charging Station Availability Forecasting.
Sensors, February, 2023
Missing Traffic Data Imputation with a Linear Generative Model Based on Probabilistic Principal Component Analysis.
Sensors, 2023
Proceedings of the 36th Canadian Conference on Artificial Intelligence, 2023
2022
STGIN: A Spatial Temporal Graph-Informer Network for Long Sequence Traffic Speed Forecasting.
CoRR, 2022
Dense-TNT: Efficient Vehicle Type Classification Neural Network Using Satellite Imagery.
CoRR, 2022
AST-GIN: Attribute-Augmented Spatial-Temporal Graph Informer Network for Electric Vehicle Charging Station Availability Forecasting.
CoRR, 2022
A SUMO Framework for Deep Reinforcement Learning Experiments Solving Electric Vehicle Charging Dispatching Problem.
CoRR, 2022
Lane Change Intent Prediction Based on Multi-Channel CNN Considering Vehicle Time-Series Trajectory.
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2022
Coupling Urban Road Travel Time and Traffic Status from Vehicle Trajectories by Gaussian Distribution.
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2022
An Incremental Map Matching Approach with Speed Estimation Constraints for High Sampling Rate Vehicle Trajectories.
Proceedings of the 17th IEEE International Conference on Control & Automation, 2022
Proceedings of the 17th International Conference on Control, 2022
A Scenario Encoding Model for Long-Term Lane-Change Prediction Using Self-Organizing Map.
Proceedings of the 17th International Conference on Control, 2022
GraphSAGE-Based Generative Adversarial Network for Short-Term Traffic Speed Prediction Problem.
Proceedings of the 17th International Conference on Control, 2022
Reinforcement Learning Method with Dynamic Learning Rate for Real-Time Route Guidance Based on SUMO.
Proceedings of the 17th International Conference on Control, 2022
MetaCNN: A New Hybrid Deep Learning Image-based Approach for Vehicle Classification Using Transformer-like Framework.
Proceedings of the 5th International Conference on Computer Science and Software Engineering, 2022
2021
Deep Learning Approach for Long- Term Prediction of Electric Vehicle (EV) Charging Station Availability.
Proceedings of the 24th IEEE International Intelligent Transportation Systems Conference, 2021
Proceedings of the Third IEEE International Conference on Cognitive Machine Intelligence, 2021
2020
Proceedings of the 16th International Conference on Control, 2020
Traffic Signal Transition Time Prediction Based on Aerial Captures during Peak Hours.
Proceedings of the 16th International Conference on Control, 2020