This project was a significant component of my master's thesis, undertaken in direct connection with the SIMRA initiative. The primary goal of SIMRA is to significantly enhance the safety of cyclists in their daily traffic encounters, recognizing them as one of the most vulnerable groups on the road, second only to pedestrians. To address this, the initiative launched a mobile application in 2019 that allows cyclists to track their routes. Crucially, the app can then automatically interpret and mark "near-miss" incidents encountered during these rides. My specific task within this project was to evaluate these reported incidents by correlating them with daily traffic times. This analysis aimed to identify recurring patterns of danger and, subsequently, to assess the effectiveness of various infrastructure measures based on the app's collected data. To achieve this, I utilized OpenStreetMap (OSM) as a rich data source for spatial evaluation with PostgreSQL. The calculated "dangerous score" for different street segments is then dynamically displayed using Deck.GL, featuring clear markers and color-weighted street segments within an Angular frontend. To efficiently communicate the extensive OSM grid data between the Angular frontend and the Spring backend, a Docker shared volume was implemented. Furthermore, to significantly improve performance, the coloring data for over 120,000 streets is meticulously cached in Redis, ensuring a smooth and responsive user experience.
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PostgreSQL
Docker
Redis
Java
Spring
TypeScript
Nx Workspace
Tailwind
Angular
Bootstrap
Mapbox