Framework for Generating Activity-Based Travel Demand Using Aggregated Mobility and Land-Use BigData
summary
A reproducible framework generates individual daily activity–travel plans from aggregated census, vehicle ownership, and building-scale land-use data and enforces building capacity, opening hours and individual travel time budgets. It implements household synthesis, individual disaggregation and diary/schedule generation inside HybridPy/SUMO (contributed tool BitJoin), produces multimodal route plans and fits hourly traffic sensor curves in a Bologna case. The generator runs and matches aggregate vehicle and activity distributions; full micro-simulation validation awaits a faster parallelized simulator.
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chapters (12)
- 0:00Introduction
- 1:04Flat big data challenges
- 3:14Activity-based modeling
- 4:44Modern travel demand challenges
- 6:54Data sources for activities
- 9:05Household generation process
- 11:35Daily activity generation
- 14:30Travel time budget assignment
- 17:01SUMO and HybridPi implementation
- 18:25Bologna simulation results
- 20:31Model status and needs
- 21:13Fast micro-simulation need