Modeling Urban Walking Risk Using Spatial-Temporal Machine Learning
Modeling Urban Walking Risk requires more than just Dijkstra’s algorithm. In this deep dive, I explore how the StreetSense project uses Uber’s H3 indexing, cyclical time encoding, and XGBoost with Tweedie regression to predict neighborhood-level pedestrian safety. Stop relying on raw coordinates and start building context-aware navigation systems.