2 citations · 5 across the 16 of their papers we have counts for
16 papers
CAVE: Crowdsourcing Passing-By Vehicles for Reliable In-Vehicle Edge Computing
Jiahe Cao, Qiang Liu, Dawei Chen +1
In-vehicle edge computing is a much anticipated paradigm to serve ever-increasing computation demands originated from the ego vehicle, such as passenger entertainments. In this pap…
KI-GAN: Knowledge-Informed Generative Adversarial Networks for Enhanced Multi-Vehicle Trajectory Forecasting at Signalized Intersections
Chuheng Wei, Guoyuan Wu, Matthew J. Barth +3
Reliable prediction of vehicle trajectories at signalized intersections is crucial to urban traffic management and autonomous driving systems. However, it presents unique challenge…
Unleashing the True Power of Age-of-Information: Service Aggregation in Connected and Autonomous Vehicles
Anik Mallik, Dawei Chen, Kyungtae Han +2
Connected and autonomous vehicles (CAVs) rely heavily upon time-sensitive information update services to ensure the safety of people and assets, and satisfactory entertainment appl…
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…
AdaMap: High-Scalable Real-Time Cooperative Perception at the Edge
Qiang Liu, Yongjie Xue, Yuru Zhang +2
Cooperative perception is the key approach to augment the perception of connected and automated vehicles (CAVs) toward safe autonomous driving. However, it is challenging to achiev…
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.…