5 citations · 17 across the 10 of their papers we have counts for
10 papers
Continual Adaptation for Autonomous Driving with the Mixture of Progressive Experts Network
Yixin Cui, Shuo Yang, Chi Wan +5
Learning-based autonomous driving requires continuous integration of diverse knowledge in complex traffic , yet existing methods exhibit significant limitations in adaptive capabil…
Quantitative Representation of Scenario Difficulty for Autonomous Driving Based on Adversarial Policy Search
Shuo Yang, Caojun Wang, Yuanjian Zhang +4
Adversarial scenario generation is crucial for autonomous driving testing because it can efficiently simulate various challenge and complex traffic conditions. However, it is diffi…
Empirical Analysis of AI-based Energy Management in Electric Vehicles: A Case Study on Reinforcement Learning
Jincheng Hu, Yang Lin, Jihao Li +5
Reinforcement learning-based (RL-based) energy management strategy (EMS) is considered a promising solution for the energy management of electric vehicles with multiple power sourc…
Potential Auto-driving Threat: Universal Rain-removal Attack
Jinchegn Hu, Jihao Li, Zhuoran Hou +3
The problem of robustness in adverse weather conditions is considered a significant challenge for computer vision algorithms in the applicants of autonomous driving. Image rain rem…
Progress and summary of reinforcement learning on energy management of MPS-EV
Jincheng Hu, Yang Lin, Liang Chu +4
The high emission and low energy efficiency caused by internal combustion engines (ICE) have become unacceptable under environmental regulations and the energy crisis. As a promisi…
A novel learning-based robust model predictive control energy management strategy for fuel cell electric vehicles
Shibo Li, Zhuoran Hou, Liang Chu +2
The multi-source electromechanical coupling makes the energy management of fuel cell electric vehicles (FCEVs) relatively nonlinear and complex especially in the types of 4-wheel-d…
Hierarchical Graph Pooling is an Effective Citywide Traffic Condition Prediction Model
Shilin Pu, Liang Chu, Zhuoran Hou +3
Accurate traffic conditions prediction provides a solid foundation for vehicle-environment coordination and traffic control tasks. Because of the complexity of road network data in…
Transfer Learning and Vision Transformer based State-of-Health prediction of Lithium-Ion Batteries
Pengyu Fu, Liang Chu, Zhuoran Hou +3
In recent years, significant progress has been made in transportation electrification. And lithium-ion batteries (LIB), as the main energy storage devices, have received widespread…
Spatial-Temporal Feature Extraction and Evaluation Network for Citywide Traffic Condition Prediction
Shilin Pu, Liang Chu, Zhuoran Hou +3
Traffic prediction plays an important role in the realization of traffic control and scheduling tasks in intelligent transportation systems. With the diversification of data source…
A Transferable Intersection Reconstruction Network for Traffic Speed Prediction
Pengyu Fu, Liang Chu, Zhuoran Hou +3
Traffic speed prediction is the key to many valuable applications, and it is also a challenging task because of its various influencing factors. Recent work attempts to obtain more…