Activity-Based Model For Atlanta (Day 1) by Guy Rousseau, Atlanta Regional Commission

1. Activity-Based Model For Atlanta (Day 1)by Guy Rousseau, Atlanta Regional Commission • Based on the CT-RAMP (Coordinated Travel – Regional Activity-based Modeling Platform) Family of Activity-Based Travel Demand Models • Main features: • Explicit intra-household interactions • Continuous temporal dimension (Half-hourly time periods) • Integration of location, time-of-day, and mode choice models • Java-based package for AB model implementation

2. Features of CT-RAMP for ARC • Combination of best features of developed AB models: • Fully disaggregate micro-simulation of daily patterns • Consistent treatment of travel tours • Addresses specific planning needs of ARC: • Dynamic / changing population • Toll facilities and managed lanes • Innovations: • Intra-household interactions • Toll choice • “Available” time influences travel generation • Parking location choice

3. Treatment of Space • 2027 TAZs • TAZs subdivided into transit accessibility: • Short walk (1/3 mi) • Long walk (2/3 mi) • No walk (> 2/3 mi) • All origins and destinations identified by TAZ and sub-zone • 6081 total alternatives in destination choice

4. ARC ABM Evolution / History • 2001 -> 2002: Household Travel Survey Data Collection & Analysis • 2003  2006 • Models estimated, population synthesizer developed (as presented @ ITM 2006 in Austin TX) • 2007  2008 • Model implementation, calibration started • 2009  2010 • Calibration/validation completed, documentation, deployment at ARC, and sensitivity testing • 2011 • Enhanced data reporting and visualization of outputs

5. Person Types

6. Activity Types

7. Treatment of Time • Time-of-day choice models work on hourly periods • AM and Midday skims used in choice models • Output trips assigned by 5 time periods for highway, 3 for transit

8. Treatment of Modes • Explicit toll versus non-toll choice in mode choice • Local versus Premium (express bus, BRT, rail) transit

9. Implementation Design Goals • Overnight run time  Model Relevance • Around 12 to 16 hours • Requires distributed processing and threading via Cube Cluster • Commodity hardware  Minimize total lifetime cost • Hardware available today from common vendors; reasonably priced • Easy to Setup and Use  Staff acceptance • Not too complicated to setup, run, debug, etc

11. Hardware and Software Setup • Three Windows Server 2003 64bit Machines: • Dual Quad Core Intel Xeon X5570 2.93 GHz with Hyper-Threading  16 threads • 32 GB of RAM • Cube Voyager + 8 seat Cube Cluster license • Total cost ~ $30,000 in 2009

12. Hardware and Software Setup • 64 bit OS for large memory addresses • 64 bit Java for CT-RAMP • 32 bit Java to integrate with Cube’s native matrix I/O DLL • Cube Base for the GUI • Cube Voyager + Cluster for running the model, assignment, etc • Java CT-RAMP software • 64 bit R for reporting/visualization

13. Overall System Setup • Cube runs the show and calls all Java processes • User starts the remote processes on the 2nd and 3rd machine (for now) • Everything talks to one mapped network folder location

14. Model ValidationHighway Trip-Based Model Activity-Based Model

15. New Measures

16. New Measures Persons Not At Home by TAZ

17. New Measures Persons by TAZ

18. New Measures

19. Activity-Based Model (Java, Cube) ABM Visualization & Reporting System Database(SQL Server) Custom Analysis Data Access Layer (IIS, ASP.Net) Visualization Dashboard(Flash) Reports(Excel)

20. ABM VIZ – Time Use • New time use (person activity over the day) • Can select different person types (the above is showing Full-time workers)

21. Radar Charts