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Atlanta Travel Forecasting Methods:

Traditional Trip-Based&

Activity-Based Model

TMIP Webinar, July 14, 2010

Guy Rousseau, Modeling Manager, Atlanta Regional CommissionGuy Rousseau, Modeling Manager, Atlanta Regional Commission

, y ,

Travel Demand Forecasting @ ARCTravel Demand Forecasting @ ARCWhere Do We Start?Where Do We Start?

E i ti /Pl d

L d U &

TravelBehavior

Existing/PlannedTransportation

System

Land Use &Socio-EconomicCharacteristics

The TravelDemand

Model Set

(The Black Box)

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ARCs Trip Generation

6 Trip Purposes:

Home-Based Work Home-Based Shopping Home-Based Grade School

Home Based University Home-Based University Home-Based Other Non-Home Based

ARCs Trip Production

IS NOT Cross-Classification, its Logit Why? Allows more independent variables:

Household size (1, 2, 3, 4+) Household income (

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ARCs Trip Attraction

Developed from Household Travel Survey & W k l E t bli h t S& Workplace Establishment Survey

Features an Attraction Share Model based on 4 market segments: Households without cars Households with cars < workersHouseholds with cars < workers Low income hshlds with # cars >= # workers High income hshlds with # cars >= # workers

ARCs Trip Distribution

Still using Gravity Model, but looking into D ti ti Ch iDestination Choice

Makes use of Topographic Penalty to compensate for area bias created by a river crossing

The topo penalty is a lump sum of time in The topo penalty is a lump sum of time in minutes (2 to 3) added to the composite time of interzonal times for all zone pairs on opposite sides of the river

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ARCs Mode Choice Fully Nested Logit Structure

ARCs Air Passenger Model Mode Choice Structure

Non-residents

Non Auto

Dropped Off Rental Car

Transit Taxi

Residents

Non Auto

Transit TaxiDrive Self Dropped Off

Private Auto

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ARC Commercial Vehicle & Truck Modelbased on

FHWA 13-BinVehicle Classification

1: 2/3 Wheels 2: Automobiles 3: 2 Axle/4 TireTrucks

4: Buses

5: 2 Axle/6 TireTrucks

6: 3 Axle Single Unit Trucks

7: 4+ Axle Single Unit Trucks

8: 4 or Less Axles Single Trailer Trucks

9: 5 Axles Single Trailer Trucks

10: 6 or More Axles Single Trailer Trucks

11: 5 or Less Axles Multiple Trailer Trucks

12: 6 Axles Multiple Trailer Trucks

13: 7 or More AxlesMultiple Trailer Trucks

91 External Stations (2024 + 91 = 2115 total taz)

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Atlanta Traffic Distribution By Hour

6 53%6.71%

7.33%

7.82%

6.69%7.00%

8.00%

9.00%

4.61%

6.53%

5.83%

4.89%4.75%5.09%

5.60%6.01%

5.12%

4.04%

3.40%

2.60%

5.49%

3.00%

4.00%

5.00%

6.00%

Perc

enta

ge o

f Tra

ffic

2000 Percent

1999 Percent

2 Year Average

1.14%

0.71%0.51%

0.76%

1.95%

60%

1.89%

0.54%0.00%

1.00%

2.00%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Hours in a Day

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TheThe 44--StepStep ProcessProcessARC Travel Demand ForecastingARC Travel Demand Forecasting

Land Use, Population & Employment

Traffic Analysis

Zones (TAZ's)

Trip Generation

Land Use Models

Trip Distribution

Mode and Path Choice

TransitAssignments

Modal Trip Tables

Travel Pattern Surveys

Auto OccupancyP/A to O/D

Transportation Facilities &

Performance

Highway and Transit

NetworksSkim Trees HighwayAssignments

Vehicle Emission Estimates

Speeds in = Speeds Out

?

No Yes

Demand

Scenario 1

Demand

Scenario 1a

ARC Model Applications: Using Radar Graphs to Visualize Performance Measures

Mode Share

Congestion

AccessibilityMode Share

Congestion

Accessibility

Scenario 2 Scenario 2bDemand

Mode Share

Congestion

Accessibility

Demand

Mode Share

Congestion

Accessibility

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ARCs Activity-Based Model Provides results similar to 4-step trip

based modelOk th h b th ith ABM? Ok, so then why bother with an ABM?

Because ARCs ABM provides additional details, more info about travel patterns & market segments

ABM allows to answer questions the 4-ABM allows to answer questions the 4step model is not capable to provide

For internal use only, not for official purposes, hence dual/parallel track of models

ARC Activity-Based Modeling System

Based on the CT-RAMP1 family of ABMs developed in New York, NY, Columbus OH (MORPC) and others

- Explicit intra-household interactions - Continuous temporal dimension (Hourly time periods)- Integration of location, time-of-day, and mode choice models- Java-based package for AB model implementation

Implemented with the existing Cube-based networks, GUI and ancillary models (external model, truck model, assignments, etc)

1Coordinated Travel-Regional Activity-Based Modeling Platform

Households: 1.7 million in 2005, 2.7 million in 2030

Model development parallel effort with MTC

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Synthesized Population: Person Age Share

Age 65-79

Age 80+ 2030

2005

Age 12-15

Age 16-17

Age 18-24

Age 25-34

Age 35-49

Age 50-64

0% 5% 10% 15% 20% 25% 30%

Age 0-5

Age 6-11

Share

Trip-Based Model Mode Share Compared to ABM Mode Share

80%

90%

30%

40%

50%

60%

70%

HBW

HBO

NHB

0%

10%

20%

WLKL WLKP DRVL DRVP SOV HOV WLKL WLKP DRVL DRVP SOV HOV

Trip-Based Model Activity-Based Model

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Line Boardings: Trip Based Model Versus ABM

AM SOV Free:Trip Length Frequency Distributions

400000

450000

150000

200000

250000

300000

350000

Freq

uenc

y

TBM

ABM

0

50000

100000

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51Distance

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VMT by Time Period

70,000,000

80,000,000

30,000,000

40,000,000

50,000,000

60,000,000

VMT

Trip Concept3

ABM Concept 3

0

10,000,000

20,000,000

AM MD PM NT

ARCs ABM Year 2005 Volume/Count Scatterplot

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What Sort of Performance Measures & Visuals are Possible with an Activity-Based Model?

ABM results in a complete activity diary for all p y yARC residents

A wealth of activity/travel results

Just about any custom report/query/visual is iblnow possible

Performance Measures also available by Age, Gender & Household Types

Mean Delay, Peak Period Travel

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Travelers By Age

Persons Not At Home By TAZ and Hour

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Persons By TAZ and Hour

Questions / Comments

Guy Rousseau (404 463-3274) grousseau@atlantaregional.comg @ g

Atlanta Regional Commission40 Courtland Street, NEAtlanta, Georgia 30303www.atlantaregional.comg

Acknowledgements: PBS&J, AECOM, Parsons Brinckerhoff, John Bowman, Mark Bradley, Bill Allen