RAD-LAD: Rule and Language Grounded Autonomous Driving in Real-Time
We present LAD, a real-time language--action planner with an interruptible architecture that produces a motion plan in a single forward pass (~20 Hz) or generates textual reasoning alongside a motion plan (~10 Hz). LAD is fast enough for real-time closed-loop deployment, achieving ~3x lower latency than prior driving language models while setting a new learning-based state of the art on nuPlan Test14-Hard and InterPlan. We also introduce RAD, a rule-based planner designed to address structural limitations of PDM-Closed. RAD achieves state-of-the-art performance among rule-based planners on nuPlan Test14-Hard and InterPlan. Finally, we show that combining RAD and LAD enables hybrid plannin...
| Authors | Anurag Ghosh, Srinivasa Narasimhan, Manmohan Chandraker et al. |
|---|---|
| Primary category | cs.RO |
| Published | 30 March 2026 |
| Last updated at source | 31 March 2026 |
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