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

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

Treatment of Space

Hall

Fulton

Carroll

Bartow

Cobb

Coweta

Henry

Gwinnett

Walton

Cherokee

DeKalb

Newton

Paulding

Forsyth

Fayette

Douglas

Spalding

Barrow

Clayton

Rockdale

¯

• 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

Person Types

NUMBER PERSON-TYPE AGE WORK STATUS

SCHOOL STATUS

1 Full-time worker 18+ Full-time None

2 Part-time worker 18+ Part-time None

3 Non-working adult 18 – 64 Unemployed None

4 Non-working senior 65+ Unemployed None

5 College student 18+ Any College +

6 Driving age student 16-17 Any Pre-college

7 Non-driving student 6 – 16 None Pre-college

8 Pre-school 0-5 None None

Activity TypesTYPE PURPOSE DESCRIPTION CLASSIFICATION ELIGIBILITY

1 Work Working at regular workplace or work-related activities outside the home.

Mandatory Workers and students

2 University College + Mandatory Age 18+

3 High School Grades 9-12 Mandatory Age 14-17

4 Grade School Grades K-8 Mandatory Age 5-13

5 Escorting Pick-up/drop-off passengers (auto trips only).

Maintenance Age 16+

6 Shopping Shopping away from home. Maintenance 5+ (if joint travel, all persons)

7 Other Maintenance Personal business/services, and medical appointments.

Maintenance 5+ (if joint travel, all persons)

8 Social/Recreational Recreation, visiting friends/family.

Discretionary 5+ (if joint travel, all persons)

9 Eat Out Eating outside of home. Discretionary 5+ (if joint travel, all persons)

10 Other Discretionary Volunteer work, religious activities.

Discretionary 5+ (if joint travel, all persons)

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 transitNUMBER DESCRIPTION BEGIN TIME END TIME

1 Early 3:00 A.M. 5:59 A.M.

2 A.M. Peak 6:00 A.M. 9:59 A.M.

3 Midday 10:00 A.M. 2:59 P.M.

4 P.M. Peak 3:00 P.M. 6:59 P.M.

5 Evening 7:00 P.M. 2:59 A.M.

Treatment of Modes

• Explicit toll versus non-toll choice in mode choice• Local versus Premium (express bus, BRT, rail) transit

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

33

1400

24

170

2100

36

170

4200

52

173

437

8795

25

112

6

80

165

9

75

310

13

75

100

970

0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000

Network Prep, Truck Model, Initial Skims

II Demand with CT-Ramp (33% Sample)

Convert Trip Lists to Demand Matrices

Highway & Transit Assignment & Skimming

II Demand with CT-Ramp (50% Sample)

Convert Trip Lists to Demand Matrices

Highway & Transit Assignment & Skimming

II Demand with CT-Ramp (100% Sample)

Convert Trip Lists to Demand Matrices

Highway & Transit Assignment & Skimming

Highway Assignment (AM, PM, MD, NT)

Total

ARC ABM Run Times (min)

No Threading/Distribution (8 processors, 16GB RAM, 1 Computer)

Threaded and Distributed (24 processors, 48GB RAM, 3 computers)

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

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

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

Model ValidationHighway

Trip-Based Model Activity-Based Model

New Measures

New Measures

Persons Not At Home by TAZ

New Measures

Persons by TAZ

New Measures

ABM Visualization & Reporting System

Activity-Based Model(Java, Cube)

Activity-Based Model(Java, Cube)

Database(SQL Server)

Database(SQL Server)

VisualizationDashboard

(Flash)

VisualizationDashboard

(Flash)

Reports(Excel)

Reports(Excel)

Data Access Layer(IIS, ASP.Net)

Data Access Layer(IIS, ASP.Net)

Custom AnalysisCustom Analysis

ABM VIZ – Time Use

• New time use (person activity over the day)• Can select different person types (the above is showing Full-time workers)

Radar Charts