7 citations · 11 across the 6 of their papers we have counts for
7 papers
LLM-Driven Scenario-Aware Planning for Autonomous Driving
He Li, Zhaowei Chen, Rui Gao +4
Hybrid planner switching framework (HPSF) for autonomous driving needs to reconcile high-speed driving efficiency with safe maneuvering in dense traffic. Existing HPSF methods ofte…
Coop-WD: Cooperative Perception with Weighting and Denoising for Robust V2V Communication
Chenguang Liu, Jianjun Chen, Yunfei Chen +5
Cooperative perception, leveraging shared information from multiple vehicles via vehicle-to-vehicle (V2V) communication, plays a vital role in autonomous driving to alleviate the l…
Reinforcement Learned Distributed Multi-Robot Navigation with Reciprocal Velocity Obstacle Shaped Rewards
Ruihua Han, Shengduo Chen, Shuaijun Wang +4
The challenges to solving the collision avoidance problem lie in adaptively choosing optimal robot velocities in complex scenarios full of interactive obstacles. In this paper, we…
Adaptive Environment Modeling Based Reinforcement Learning for Collision Avoidance in Complex Scenes
Shuaijun Wang, Rui Gao, Ruihua Han +3
The major challenges of collision avoidance for robot navigation in crowded scenes lie in accurate environment modeling, fast perceptions, and trustworthy motion planning policies.…
Runtime Safety Assurance for Learning-enabled Control of Autonomous Driving Vehicles
Shengduo Chen, Yaowei Sun, Dachuan Li +3
Providing safety guarantees for Autonomous Vehicle (AV) systems with machine-learning-based controllers remains a challenging issue. In this work, we propose Simplex-Drive, a frame…
Capture Uncertainties in Deep Neural Networks for Safe Operation of Autonomous Driving Vehicles
Liuhui Ding, Dachuan Li, Bowen Liu +5
Uncertainties in Deep Neural Network (DNN)-based perception and vehicle's motion pose challenges to the development of safe autonomous driving vehicles. In this paper, we propose a…
Joint Multi-Object Detection and Tracking with Camera-LiDAR Fusion for Autonomous Driving
Kemiao Huang, Qi Hao
Multi-object tracking (MOT) with camera-LiDAR fusion demands accurate results of object detection, affinity computation and data association in real time. This paper presents an ef…