A Java-based public transport routing engine for Maastricht, integrating real-time GTFS data to compute multi-modal routes and urban accessibility metrics.
MaasNav is a Java application designed for route optimization in Maastricht's public transport system. It integrates Dijkstra’s algorithm to compute the shortest paths for walking, cycling, and public transport while considering real-time GTFS data. The system includes a Java Swing GUI for route visualization and an SQLite database to efficiently manage transit and demographic data.
Additionally, it incorporates an accessibility scoring system that evaluates socio-economic opportunities within different neighborhoods by analyzing nearby amenities and transport connectivity.
✅ Multi-Modal Routing: Computes shortest paths for walking, cycling, and bus routes.
✅ GTFS Data Integration: Processes real-time schedules and stop locations.
✅ Java Swing GUI: Visualizes routes with interactive maps.
✅ Accessibility Scoring: Evaluates neighborhoods based on nearby amenities.
✅ Optimized Performance: Uses heuristics for fast query resolution.
✅ Database Management: Efficient storage using an SQLite relational database.
This project is designed to address key urban mobility and accessibility challenges:
- Is it possible to compute an optimal multi-modal route using Java and GTFS data?
- How does accessibility vary across different regions of Maastricht?
- What impact does urban infrastructure have on public transport efficiency?
- How does our routing engine compare in efficiency against existing solutions?
To start the application, run the MapViewer.java class, located in:
📂 src/java/com/group8/phase1/views/
The Java Swing GUI will launch, allowing users to enter start and destination points.
✅ Code Coverage:
- 89% coverage achieved across all components.
- Automated unit tests were executed using JUnit & JaCoCo.
- Detailed coverage reports are available in the
TestResultsdirectory.
✅ Performance Benchmarks:
- 15% improvement over OpenTripPlanner in travel time estimates.
- Efficiency testing based on predefined multi-modal trip scenarios.
👤 Kaan Basaran
👤 Rares Boghean
👤 Nishan Mistry
👤 Mihnea Şerbănescu
👤 Gvidas Žilinskas