5 citations · 5 across the 3 of their papers we have counts for
4 papers
DISC: Dataset for Analyzing Driving Styles In Simulated Crashes for Mixed Autonomy
Sandip Sharan Senthil Kumar, Sandeep Thalapanane, Guru Nandhan Appiya Dilipkumar Peethambari +3
Handling pre-crash scenarios is still a major challenge for self-driving cars due to limited practical data and human-driving behavior datasets. We introduce DISC (Driving Styles I…
Improving Generalization of Transfer Learning Across Domains Using Spatio-Temporal Features in Autonomous Driving
Shivam Akhauri, Laura Zheng, Tom Goldstein +1
Practical learning-based autonomous driving models must be capable of generalizing learned behaviors from simulated to real domains, and from training data to unseen domains with u…
Improving Robustness of Learning-based Autonomous Steering Using Adversarial Images
Yu Shen, Laura Zheng, Manli Shu +3
For safety of autonomous driving, vehicles need to be able to drive under various lighting, weather, and visibility conditions in different environments. These external and environ…
Enhanced Transfer Learning for Autonomous Driving with Systematic Accident Simulation
Shivam Akhauri, Laura Zheng, Ming Lin
Simulation data can be utilized to extend real-world driving data in order to cover edge cases, such as vehicle accidents. The importance of handling edge cases can be observed in…