3 papers
cs.AI2026
NSF-HRPT: Neural Semantic Field meets Hierarchical Risk Perception Tree for Safety-Critical Scenario Assessment
Yu Zhao, Jiangyu Pan, Tao Hu +4
The ability to accurately assess and anticipate risks in safety-critical scenarios is crucial for autonomous driving systems. While existing research has made progress in collision…
cs.SE2024
RoadGen: Generating Road Scenarios for Autonomous Vehicle Testing
Fan Yang, You Lu, Bihuan Chen +2
With the rapid development of autonomous vehicles, there is an increasing demand for scenario-based testing to simulate diverse driving scenarios. However, as the base of any drivi…
cs.LG2024
Accelerating the Evolution of Personalized Automated Lane Change through Lesson Learning
Jia Hu, Mingyue Lei, Haoran Wang +2
Personalization is crucial for the widespread adoption of advanced driver assistance system. To match up with each user's preference, the online evolution capability is a must. How…