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A field experiment in Yokohama (Japan) reveals that a macroscopic fundamental diagram (MFD) linking space-mean flow, density and speed exists on a large urban area. The experiment used a combination of fixed detectors and floating vehicle probes as sensors. It was observed that when the somewhat chaotic scatter-plots of speed vs. density from individual fixed detectors were aggregated the scatter nearly disappeared and points grouped neatly along a smoothly declining curve. This evidence suggests, but does not prove, that an MFD exists for the complete network because the fixed detectors...

This brief note shows how to solve Sudoku puzzles by hand. It is targeted to the Sudoku player who can solve intermediate and hard puzzles but sometimes fails on the extremely difficult.

This article introduces a statistical method to estimate trips origin and destination locations from a masked trip data set. The estimation method uses trip features, the graph of the network, and publicly accessible external information on the realtime congestion status to find the most probable trips origin and destination based on a Bayesian approach, Markov Chain rule, and rank aggregation method. A case study of Porto, Portugal assesses the performance of the statistical estimation method by comparing the estimated location with the centroids of reported locations and with the actual...

We introduce (U)NFV, a modular neural network architecture that generalizes classical finite volume (FV) methods for solving hyperbolic conservation laws. Hyperbolic partial differential equations (PDEs) are challenging to solve, particularly conservation laws whose physically relevant solutions contain shocks and discontinuities. FV methods are widely used for their mathematical properties: convergence to entropy solutions, flow conservation, or total variation diminishing, but often lack accuracy and flexibility in complex settings. Neural Finite Volume addresses these limitations by...