arbitration graphs 1autonomous driving 1learned planning 1motion planning 1rule-based planning 1safety verification 1
From the 1 of 5 linked papers with an AI index.
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cs.RO2026
Mosaic: An Extensible Framework for Composing Rule-Based and Learned Motion Planners
Nick Le Large, Marlon Steiner, Lingguang Wang +4
Mosaic is a framework that combines rule‑based and learned motion planners using arbitration graphs, separating trajectory verification from selection to improve safety and perform…
cs.RO2026
Learning High-Level Decision Making with an Interaction-Aware Attention-Based Network in Autonomous Driving
Marcelo Contreras, Willi Poh, Christoph Stiller +1
Reliable learning-based high-level decision making for lane changes and speed control in automated driving must accommodate dynamically sized inputs due to varying scene traffic fl…
cs.RO2026
Human-Aided Trajectory Planning for Automated Vehicles through Teleoperation and Arbitration Graphs
Nick Le Large, David Brecht, Willi Poh +3
Teleoperation enables remote human support of automated vehicles in scenarios where the automation is not able to find an appropriate solution. Remote assistance concepts, where op…