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The paper proposes MR-Traj, a multi-resolution diffusion framework for synthetic trajectory generation in urban systems, which captures complex spatial-temporal dependencies at multiple resolutions and improves performance in fine-grained mobility modeling for downstream tasks.
Zoox expands its robotaxi operations to multiple cities with software enhancements, detailing technical improvements and scaling strategies for commercial deployment.
This paper applies explainable machine learning to mobility trajectories from the NetMob 2025 Data Challenge to assess the 15-minute city concept in Paris, finding that higher local service availability is associated with less car use and more active mobility, though with spatial and demographic heterogeneity.
This paper presents a graph-based traffic signal control interface using a shared graph neural network to assign scores to movements, with deterministic phase construction via incidence matrices. Experiments evaluate transfer across synthetic and city road networks, showing feasibility but sensitivity to distribution shifts.
Google Research published a study in Nature Cities showing that coordinating a small fraction of trips via navigation app interventions can measurably reduce traffic congestion and emissions across entire cities.
STAGformer introduces a spatio-temporal agent graph transformer with linear complexity for bike-sharing demand forecasting, outperforming baselines on NYC and Chicago datasets.
This paper presents an end-to-end analytics framework that transforms raw mobile data into business and urban planning insights, using ETL pipelines, machine learning on Google BigQuery and Vertex AI, and Power BI visualization for decision support.
Electric air taxi companies Joby and Archer are locked in legal battles over espionage and patent infringement, threatening the industry's progress and investor confidence.
REK robots were observed on San Francisco streets undergoing teleoperated testing to collect data on urban mobility challenges.