Mt-KaRRi is a highly scalable ride-pooling dispatcher that achieves millisecond-scale response times for millions of requests, supporting unprecedented-scale urban simulations.
Arterial Vehicle Trajectory Re- construction by Integrating Driving Behaviour Pattern Recognition
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
K-means clustering on 1219 Argoverse 2 deceleration events identifies four stable modes with bootstrap ARI 0.897, and an early HistGradientBoosting classifier reaches macro-F1 0.758 with modest scene-context gains.
citing papers explorer
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Advancing Dynamic Ride-Pooling Simulation -- A Highly Scalable Dispatcher
Mt-KaRRi is a highly scalable ride-pooling dispatcher that achieves millisecond-scale response times for millions of requests, supporting unprecedented-scale urban simulations.
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Urban Deceleration Behavior Modes Under Scene Context: An Early-Kinematic Classifier from Argoverse 2 Multi-Agent Trajectories
K-means clustering on 1219 Argoverse 2 deceleration events identifies four stable modes with bootstrap ARI 0.897, and an early HistGradientBoosting classifier reaches macro-F1 0.758 with modest scene-context gains.