Peng Chen
Orcid: 0000-0002-8076-8989Affiliations:
- Beihang University, School of Transportation Science and Engineering, Beijing, China
According to our database1,
Peng Chen
authored at least 18 papers
between 2017 and 2024.
Collaborative distances:
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Bibliography
2024
IEEE Trans. Veh. Technol., March, 2024
Integration of Decision-Making and Motion Planning for Autonomous Driving Based on Double-Layer Reinforcement Learning Framework.
IEEE Trans. Veh. Technol., March, 2024
2023
A Secure Trajectory Planning Method for Connected Autonomous Vehicles at Mining Site.
Symmetry, November, 2023
RailDepth: A Self-Supervised Network for Railway Depth Completion Based on a Pooling-Guidance Mechanism.
IEEE Trans. Instrum. Meas., 2023
Lateral Motion Control for Obstacle Avoidance in Autonomous Driving Based on Deep Reinforcement Learning.
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2023
Optimization-Based Trajectory Planning for Autonomous Driving at Mining Area with Irregular Boundary.
Proceedings of the International Conference on Frontiers of Artificial Intelligence and Machine Learning, 2023
2022
FarNet: An Attention-Aggregation Network for Long-Range Rail Track Point Cloud Segmentation.
IEEE Trans. Intell. Transp. Syst., 2022
Object Classification Based on Enhanced Evidence Theory: Radar-Vision Fusion Approach for Roadside Application.
IEEE Trans. Instrum. Meas., 2022
2021
Semantic-Level Maneuver Sampling and Trajectory Planning for On-Road Autonomous Driving in Dynamic Scenarios.
IEEE Trans. Veh. Technol., 2021
A Particle Filter-Based Approach for Vehicle Trajectory Reconstruction Using Sparse Probe Data.
IEEE Trans. Intell. Transp. Syst., 2021
2020
Cycle-Based End of Queue Estimation at Signalized Intersections Using Low-Penetration-Rate Vehicle Trajectories.
IEEE Trans. Intell. Transp. Syst., 2020
Reliable shortest path finding in stochastic time-dependent road network with spatial-temporal link correlations: A case study from Beijing.
Expert Syst. Appl., 2020
2019
Modeling arterial travel time distribution by accounting for link correlations: a copula-based approach.
J. Intell. Transp. Syst., 2019
Trajectory Reconstruction Using Automated Vehicles Motion Detection Data: A Hybrid Approach Integrating Wiedemann Model and Cellular Automation.
Proceedings of the 2019 IEEE Intelligent Transportation Systems Conference, 2019
An Adaptive Control Method for Arterial Signal Coordination Based on Deep Reinforcement Learning.
Proceedings of the 2019 IEEE Intelligent Transportation Systems Conference, 2019
2018
The α-reliable path problem in stochastic road networks with link correlations: A moment-matching-based path finding algorithm.
Expert Syst. Appl., 2018
2017
A hybrid deep learning approach for urban expressway travel time prediction considering spatial-temporal features.
Proceedings of the 20th IEEE International Conference on Intelligent Transportation Systems, 2017