Search Results for author:
Found 4 papers, 2 papers with code
Situation Awareness for Driver-Centric Driving Style Adaptation
Furthermore, we found that feature encoders pretrained on our dataset lead to more precise driving behavior modeling.
Exploring the Influence of Driving Context on Lateral Driving Style Preferences: A Simulator-Based Study
Despite the increased research focus on driving styles, there remains a need for comprehensive studies investigating how variations in the driving context impact the assessment of automated driving functions.
Self-Perception Versus Objective Driving Behavior: Subject Study of Lateral Vehicle Guidance
Ensuring a safe and comfortable ride experience is vital for the widespread adoption of autonomous vehicles, as mismatches in driving styles between humans and autonomous systems can impact passenger confidence.
CARLANE: A Lane Detection Benchmark for Unsupervised Domain Adaptation from Simulation to multiple Real-World Domains
Unsupervised Domain Adaptation demonstrates great potential to mitigate domain shifts by transferring models from labeled source domains to unlabeled target domains.
Ranked #1 on
Domain Adaptation
on MuLane
