2 papers
cs.RO2026
A Large-Language-Model Supported Personalized Driving Framework for Lane Change in Highway Scenarios
Dong Bi, Yongqi Zhao, Paul Kovacevic +4
Personalized driving can improve the user acceptance of automated driving systems. However, existing methods still provide limited support for translating natural-language driving…
cs.RO2026
Automated Digital Twin Construction for Highway Scenarios Using LiDAR Point Clouds and OpenStreetMap
Yongqi Zhao, Dong Bi, Paul Kovacevic +4
Accurate road environment modeling is fundamental to the simulation and validation of automated driving systems. However, constructing road maps in standardized formats such as ASA…