1 citations · 1 across the 4 of their papers we have counts for
5 papers
CogDrive: Cognition-Driven Multimodal Prediction-Planning Fusion for Safe Autonomy
Heye Huang, Yibin Yang, Mingfeng Fan +3
Safe autonomous driving in mixed traffic requires a unified understanding of multimodal interactions and dynamic planning under uncertainty. Existing learning based approaches stru…
Complementary Learning System Empowers Online Continual Learning of Vehicle Motion Forecasting in Smart Cities
Zirui Li, Yunlong Lin, Guodong Du +5
Artificial intelligence underpins most smart city services, yet deep neural network (DNN) that forecasts vehicle motion still struggle with catastrophic forgetting, the loss of ear…
Escaping Stability-Plasticity Dilemma in Online Continual Learning for Motion Forecasting via Synergetic Memory Rehearsal
Yunlong Lin, Chao Lu, Tongshuai Wu +5
Deep neural networks (DNN) have achieved remarkable success in motion forecasting. However, most DNN-based methods suffer from catastrophic forgetting and fail to maintain their pe…
H2C: Hippocampal Circuit-inspired Continual Learning for Lifelong Trajectory Prediction in Autonomous Driving
Yunlong Lin, Zirui Li, Guodong Du +5
Deep learning (DL) has shown state-of-the-art performance in trajectory prediction, which is critical to safe navigation in autonomous driving (AD). However, most DL-based methods…
InterHub: A Naturalistic Trajectory Dataset with Dense Interaction for Autonomous Driving
Xiyan Jiang, Xiaocong Zhao, Yiru Liu +4
The driving interaction-a critical yet complex aspect of daily driving-lies at the core of autonomous driving research. However, real-world driving scenarios sparsely capture rich…