Create Detailed Traffic Models and Simulations
summary
Prototype pipeline generates a street network from OpenStreetMap, pulls GTFS and POIs, synthesizes household activity chains with TAPAS, and produces a demand file that runs in Eclipse SUMO via Docker; a Leonberg case creates 218,000 trips for one day, runs in a cloud service with a REST API, and exports visualizations and reports. Automated model build drops effort from months to days but calibration/validation against local counters remains incomplete. Mobility Ops is planned for open sourcing.
AI-written summary · about
chapters (8)
- 0:00Traffic modeling intro
- 4:45SUMO open source sim
- 8:43SUMO scenario from data
- 10:08Demand with Mobility Ops
- 15:52Automate model creation
- 16:37Munich microhubs case
- 19:09Mobility Ops as Eclipse
- 22:54Q&A validation limits
related talks
34mMove Your Crate - How to optimize your mobility
23mDriving Smarter Mobility: From OpenStreetMap to Real-Time Traffic Simulation with SUMO & Godot
13mReimagining Public Transport: An OSM-based Street Supply Tool
16mTidy Transit: Real Life Data Modeling for Public Transportation
22mUnderstanding our cities with FOSS4G- 16mTidy Transit: Real Life Data Modeling for Public Transportation
28mEstimating Traffic Flow to find New Drive Thru Locations
10mSmart Commuting