Publications (24)
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…
A Unified Candidate Set with Scene-Adaptive Refinement via Diffusion for End-to-End Autonomous Driving
Zhengfei Wu, Shuaixi Pan, Shuohan Chen +2
End-to-end autonomous driving is increasingly adopting a multimodal planning paradigm that generates multiple trajectory candidates and selects the final plan, making candidate-set…
Tire Force Estimation in Intelligent Tires Using Machine Learning
Nan Xu, Hassan Askari, Yanjun Huang +2
The concept of intelligent tires has drawn attention of researchers in the areas of autonomous driving, advanced vehicle control, and artificial intelligence. The focus of this pap…
A Safe and Efficient Self-evolving Algorithm for Decision-making and Control of Autonomous Driving Systems
Shuo Yang, Liwen Wang, Yanjun Huang +1
Autonomous vehicles with a self-evolving ability are expected to cope with unknown scenarios in the real-world environment. Take advantage of trial and error mechanism, reinforceme…
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…
ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving
Renju Feng, Ning Xi, Duanfeng Chu +6
This paper presents ARTEMIS, an end-to-end autonomous driving framework that combines autoregressive trajectory planning with Mixture-of-Experts (MoE). Traditional modular methods…
Joint Sparse Representations and Coupled Dictionary Learning in Multi-Source Heterogeneous Image Pseudo-color Fusion
Long Bai, Shilong Yao, Kun Gao +5
Considering that Coupled Dictionary Learning (CDL) method can obtain a reasonable linear mathematical relationship between resource images, we propose a novel CDL-based Synthetic A…
Tire Slip Angle Estimation based on the Intelligent Tire Technology
Nan Xu, Yanjun Huang, Hassan Askari +1
Tire slip angle is a vital parameter in tire/vehicle dynamics and control. This paper proposes an accurate estimation method by the fusion of intelligent tire technology and machin…
CURVE: Learning Causality-Inspired Invariant Representations for Robust Scene Understanding via Uncertainty-Guided Regularization
Yue Liang, Jiatong Du, Ziyi Yang +2
Scene graphs provide structured abstractions for scene understanding, yet they often overfit to spurious correlations, severely hindering out-of-distribution generalization. To add…
A Systematic Survey of Control Techniques and Applications in Connected and Automated Vehicles
Wei Liu, Min Hua, Zhiyun Deng +10
Vehicle control is one of the most critical challenges in autonomous vehicles (AVs) and connected and automated vehicles (CAVs), and it is paramount in vehicle safety, passenger co…
A Safety-Oriented Self-Learning Algorithm for Autonomous Driving: Evolution Starting from a Basic Model
Shuo Yang, Caojun Wang, Zhenyu Ma +2
Autonomous driving vehicles with self-learning capabilities are expected to evolve in complex environments to improve their ability to cope with different scenarios. However, most…
SKANet: A Cognitive Dual-Stream Framework with Adaptive Modality Fusion for Robust Compound GNSS Interference Classification
Zhihan Zeng, Yang Zhao, Kaihe Wang +7
As the electromagnetic environment becomes increasingly complex, Global Navigation Satellite Systems (GNSS) face growing threats from sophisticated jamming interference. Although D…
Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects
Yixin Cui, Haotian Lin, Shuo Yang +3
The rapid evolution of large language models in natural language processing has substantially elevated their semantic understanding and logical reasoning capabilities. Such profici…
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…
Safe Control and Learning Using Generalized Action Governor
Peiyuan Fang, Weiqi Zhang, Lu Xiong +7
This paper introduces the Generalized Action Governor (AG), a supervisory scheme that augments a nominal closed-loop system with the capability to enforce state and input constrain…
GEMINUS: Dual-aware Global and Scene-Adaptive Mixture-of-Experts for End-to-End Autonomous Driving
Chi Wan, Yixin Cui, Jiatong Du +5
End-to-end autonomous driving requires adaptive and robust handling of complex and diverse traffic environments. However, prevalent single-mode planning methods attempt to learn an…
JSR-GFNet: Jamming-to-Signal Ratio-Aware Dynamic Gating for Interference Classification in future Cognitive Global Navigation Satellite Systems
Zhihan Zeng, Hongyuan Shu, Kaihe Wang +6
The transition toward cognitive global navigation satellite system (GNSS) receivers requires accurate interference classification to trigger adaptive mitigation strategies. However…
AgentSchool: An LLM-Powered Multi-Agent Simulation for Education
Yulei Ye, Wenhao Li, Zhong Wen +23
Despite the rapid deployment of LLMs into classrooms, validating educational AI remains uniquely intractable: interventions act on developing learners whose cognitive and social tr…
Driving in Corner Case: A Real-World Adversarial Closed-Loop Evaluation Platform for End-to-End Autonomous Driving
Jiaheng Geng, Jiatong Du, Xinyu Zhang +3
Safety-critical corner cases, difficult to collect in the real world, are crucial for evaluating end-to-end autonomous driving. Adversarial interaction is an effective method to ge…
A Safe Self-evolution Algorithm for Autonomous Driving Based on Data-Driven Risk Quantification Model
Shuo Yang, Shizhen Li, Yanjun Huang +1
Autonomous driving systems with self-evolution capabilities have the potential to independently evolve in complex and open environments, allowing to handle more unknown scenarios.…
Co-MTP: A Cooperative Trajectory Prediction Framework with Multi-Temporal Fusion for Autonomous Driving
Xinyu Zhang, Zewei Zhou, Zhaoyi Wang +3
Vehicle-to-everything technologies (V2X) have become an ideal paradigm to extend the perception range and see through the occlusion. Exiting efforts focus on single-frame cooperati…
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…