65 citations · 71 across the 8 of their papers we have counts for
8 papers
Hierarchical End-to-End Autonomous Driving: Integrating BEV Perception with Deep Reinforcement Learning
Siyi Lu, Lei He, Shengbo Eben Li +3
End-to-end autonomous driving offers a streamlined alternative to the traditional modular pipeline, integrating perception, prediction, and planning within a single framework. Whil…
Neural Radiance Field in Autonomous Driving: A Survey
Lei He, Leheng Li, Wenchao Sun +5
Neural Radiance Field (NeRF) has garnered significant attention from both academia and industry due to its intrinsic advantages, particularly its implicit representation and novel…
Adaptive Decision-Making for Autonomous Vehicles: A Learning-Enhanced Game-Theoretic Approach in Interactive Environments
Heye Huang, Jinxin Liu, Guanya Shi +3
This paper proposes an adaptive behavioral decision-making method for autonomous vehicles (AVs) focusing on complex merging scenarios. Leveraging principles from non-cooperative ga…
A Risk-aware Planning Framework of UGVs in Off-Road Environment
Junkai Jiang, Zhenhua Hu, Zihan Xie +7
Planning module is an essential component of intelligent vehicle study. In this paper, we address the risk-aware planning problem of UGVs through a global-local planning framework…
DDM-Lag : A Diffusion-based Decision-making Model for Autonomous Vehicles with Lagrangian Safety Enhancement
Jiaqi Liu, Peng Hang, Xiaocong Zhao +2
Decision-making stands as a pivotal component in the realm of autonomous vehicles (AVs), playing a crucial role in navigating the intricacies of autonomous driving. Amidst the evol…
Information Flow Topology in Mixed Traffic: A Comparative Study between "Looking Ahead" and "Looking Behind"
Shuai Li, Haotian Zheng, Jiawei Wang +4
The emergence of connected and automated vehicles (CAVs) promises smoother traffic flow. In mixed traffic where human-driven vehicles (HDVs) also exist, existing research mostly fo…