4 papers
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…
ConvoyLLM: Dynamic Multi-Lane Convoy Control Using LLMs
Liping Lu, Zhican He, Duanfeng Chu +3
This paper proposes a novel method for multi-lane convoy formation control that uses large language models (LLMs) to tackle coordination challenges in dynamic highway environments.…
CLIP-SENet: CLIP-based Semantic Enhancement Network for Vehicle Re-identification
Liping Lu, Zihao Fu, Duanfeng Chu +2
Vehicle re-identification (Re-ID) is a crucial task in intelligent transportation systems (ITS), aimed at retrieving and matching the same vehicle across different surveillance cam…
EPN: An Ego Vehicle Planning-Informed Network for Target Trajectory Prediction
Saiqian Peng, Duanfeng Chu, Guanjie Li +2
Trajectory prediction plays a crucial role in improving the safety of autonomous vehicles. However, due to the highly dynamic and multimodal nature of the task, accurately predicti…