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Jev with Foresight: Safe Language-Guided Autonomous Driving via a Language World Model

1 reports1 reporting sourcesUpdated 5 days ago

Overview

Event synthesis

This research presents Jev-AD, which integrates a typed decision model with a language world model to predict vehicle trajectories over two seconds for safer autonomous driving. In simulated highway merging scenarios involving 500 car episodes, the system reduced the collision rate from 26.0% to 2.4% while maintaining a decision latency of 0.25 seconds per action and achieving passenger intent in 93% of free-form command trials. When evaluated on 500 replayed real-world NGSIM episodes, the collision rate decreased from 48.2% to 2.8%, and the world model successfully foresaw 93% of dangerous actions.

Generated from attributed reports · Updated 5 days ago

Event evidence and corrections

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Reported quantity · decision time per action: 0.25 other · Basis not reported
Supporting report

“or every candidate action how nearby vehicles move over the next two seconds. Code turns these predictions into foreseen consequences, which Jev compares instead of inferring them from coordinates. In simulated highway merging (500 car-episodes), this foresight lowers the same decision model's collision rate from 26.0% to 2.4% at 0.25 seconds per decision, and Jev-AD achieves the passenger's intent in 93% of free-for”

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11/5
  1. arXiv Robotics — research abstractsSignal
    Jev with Foresight: Safe Language-Guided Autonomous Driving via a Language World Model

    This research presents Jev-AD, which integrates a typed decision model with a language world model to predict vehicle trajectories over two seconds for safer autonomous driving. In simulated highway merging scenarios involving 500 car episodes, the system reduced the collision rate from 26.0% to 2.4% while maintaining a decision latency of 0.25 seconds per action and achieving passenger intent in 93% of free-form command trials. When evaluated on 500 replayed real-world NGSIM episodes, the collision rate decreased from 48.2% to 2.8%, and the world model successfully foresaw 93% of dangerous actions.

Event coverage history

Current attention 3·Peak within the comparable range 10(2026-11-05 06:00 UTC)·Change within the comparable range over 24 hours -49%

02.557.5102026-11-0506:002026-11-0521:002026-11-0613:002026-11-0704:00

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