Home▸AI & Machine Learning▸Traffic Congestion Predictor 2D — Kalman Filter Live

Traffic Congestion Predictor 2D — Kalman Filter Live

A top-down 2D road view driving the same genuine predict/update Kalman filter as the 3D version: watch it fuse noisy simulated sensor readings live to estimate and predict road-segment traffic speed.

AI & Machine Learning2DModerate60 FPS📱 Mobile-adapted⇄ 3D version

This 2D companion runs the exact same two-state Kalman filter as the 3D original — real predict/update matrix math, Joseph-form covariance update, adjustable process noise Q and measurement noise R — but shows it over a flat top-down road instead of an orbiting 3D scene, so the sign, lanes and live chart stay legible at any size.

⚙ Under the hood

Live 2-state Kalman filter (speed, trend) fusing noisy simulated sensor readings over a top-down 2D road view, with congestion injection, sensor dropout, and a multi-step-ahead prediction chart.

kalman filterstate estimationsensor fusionkalman gainprocess noisemeasurement noisepredict-update cycle

2D · HTML5 Canvas 2D · 60 FPS target · runs fully client-side, no install