2 citations · 5 across the 12 of their papers we have counts for
6 papers · 1 filter
LaMPilot: An Open Benchmark Dataset for Autonomous Driving with Language Model Programs
Yunsheng Ma, Can Cui, Xu Cao +9
Autonomous driving (AD) has made significant strides in recent years. However, existing frameworks struggle to interpret and execute spontaneous user instructions, such as "overtak…
Driving through the Concept Gridlock: Unraveling Explainability Bottlenecks in Automated Driving
Jessica Echterhoff, An Yan, Kyungtae Han +3
Concept bottleneck models have been successfully used for explainable machine learning by encoding information within the model with a set of human-defined concepts. In the context…
Real-time Learning of Driving Gap Preference for Personalized Adaptive Cruise Control
Zhouqiao Zhao, Xishun Liao, Amr Abdelraouf +4
Advanced Driver Assistance Systems (ADAS) are increasingly important in improving driving safety and comfort, with Adaptive Cruise Control (ACC) being one of the most widely used.…
Interaction-Aware Personalized Vehicle Trajectory Prediction Using Temporal Graph Neural Networks
Amr Abdelraouf, Rohit Gupta, Kyungtae Han
Accurate prediction of vehicle trajectories is vital for advanced driver assistance systems and autonomous vehicles. Existing methods mainly rely on generic trajectory predictions…
MDAR: Multi-View Multi-Scale Driver Action Recognition with Vision Transformer
Yunsheng Ma, Liangqi Yuan, Amr Abdelraouf +4
Ensuring traffic safety and preventing accidents is a critical goal in daily driving, where the advancement of computer vision technologies can be leveraged to achieve this goal. I…
CEMFormer: Learning to Predict Driver Intentions from In-Cabin and External Cameras via Spatial-Temporal Transformers
Yunsheng Ma, Wenqian Ye, Xu Cao +4
Driver intention prediction seeks to anticipate drivers' actions by analyzing their behaviors with respect to surrounding traffic environments. Existing approaches primarily focus…