The SANDAG Activity The SANDAG Activity-Based Based Travel Travel Model Model Institute of Traffic Engineers Luncheon Presentation April 1, 2010
Mar 02, 2016
The SANDAG ActivityThe SANDAG Activity--Based Based Travel Travel ModelModel
Institute of Traffic Engineers Luncheon PresentationApril 1, 2010
Institute of Traffic Engineers Luncheon April 1, 2010
Trip-Based Model Overview
662
341
PiZone
Trip Productions (Pi)
182
821
AjZone
Trip Attractions (Aj)
1001882Total Aj
6611552
347271
TotalPi
21
FromZone
To ZoneTrips(Tijm)
Mode
25Transit
30Auto
Trips(Tijmr)
Route
7Route B
18Route A
Trip Generation Trip Distribution Mode ChoiceMode Choice Trip Assignment
Institute of Traffic Engineers Luncheon April 1, 2010
Criticisms of Trip-Based Models
• Lack of Behavioral Fidelity– The only model based on actual decision-making theory is mode
choice (in most model systems)• Aggregation Bias
– No information on non-home-based trips– Each additional market segment (socio-economic category, trip
purpose, time period) significantly increases runtime• Lack of Policy Responsiveness
– Time-of-day shifts– Socio-economic changes– Induced travel
Institute of Traffic Engineers LuncheonApril 1, 2010
What is an Activity-Based Travel Model?
• Travel is a derived demand – it results for the need for people to engage in activities outside the home.
• Activity-based travel models attempt to replicate how people decide:– whether to travel– where to travel to– when to travel– how to travel
• Activity-based travel models are based on behavioral decision-making theory
• This makes them more suited to address policies that affect how people make travel decisions than trip-based models
Institute of Traffic Engineers Luncheon April 1, 2010
Activity-Based Travel Models
• Model travel by individuals– All important socio-economic characteristics are tracked
explicitly – Micro-simulation used
• Model trips as part of tours– A series of trips beginning and ending at home or work (anchor
locations)– Primary destination, intermediate stops– No more non-home-based trips!!
• Schedule tours into available time-windows– Consistent daily activity patterns that replicate survey data
Complex Planning Issues Addressed with AB Models
• Affects of transport policies on time-use• Demographic changes & equity analysis• Demand management policies (HOV, pricing)• Changes in accessibilities• Better interface with traffic simulation models• Telecommuting• Global transportation policies & taxation• Evacuation planning
Institute of Traffic Engineers Luncheon April 1, 2010
Institute of Traffic Engineers Luncheon April 1, 2010
ABM: Tours and Trips
Home-Based Work Trip
Non-Home-BasedTrip
Home-BasedOther Trip
Non-Home-Based Trip
Non-Home-Based Trip
Zone 1 Zone 3
Zone 2
Zone 4
Work TourPrimary
Destination
IntermediateStop
Origin
Work-Based Tour
Origin PrimaryDestination
HH # Per # Tour # Purp OriginTAZ
Destin.TAZ
Outbound Stop1 TAZ
Return Stop1 TAZ
Mode Sub-tour
Sub-TourDestin.
1023 1 1 Work 1 3 0 2 Transit Yes 4
Data View:
Institute of Traffic Engineers Luncheon April 1, 2010
Activity-Based Models: Mode Consistency
Zone 1 Zone 3
Zone 2
Zone 4
Work Tour Work-Based Tour
Bus to Work = Drive alone not available for lunch
Institute of Traffic Engineers Luncheon April 1, 2010
Activity-Based Model: Micro-simulation
• A synthetic population is created that represents the actual population
• Travel is explicitly modeled for each person/household• Monte Carlo simulation is used instead of fractional
probability aggregation: Discrete choices made for each traveler
• Results are aggregated and:– Assigned to transport networks– Compiled into reports
Institute of Traffic Engineers Luncheon April 1, 2010
Activity-Based Model For San Diego
• 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)•Logit formulations for choice models•Sensitive to a wide range of socio-economic variables, transportation costs/accessibilities, and land-use changes•Java-based package for model implementation
Institute of Traffic Engineers Luncheon April 1, 2010
Activity-Based Models In the United States
NYSan Francisco
Seattle
ColumbusDenver
Atlanta
Sacramento
Bay Area
Developed by PBDeveloped by others
Oregon
Ohio
San Diego
Lake Tahoe
CT-RAMP Family
PhoenixLos Angeles
(Atlanta model co-developed with MTC)
Institute of Traffic Engineers Luncheon April 1, 2010
12 12
Joint Non-Mandatory Tours
1. Population Synthesis
2. Long-term
4. Daily
5. Tour level
6. Trip level
2.1. Usual workplace / school
4.1. Person pattern type & Joint Tour Indicator
Mandatory Non-mandatory Home
4.2.1. Frequency
4.2.2. TOD4.3.1. Frequency
4.3.2. Party
4.3.3. Participation
4.3.4. Destination
4.3.5. TOD
5.1. Tour mode 5.2. Stop frequency 5.3. Stop location
6.1. Trip mode
6.2. Auto parking
Individual Mandatory Tours
Individual Discretionary
Tours
4.5.1. Frequency
4.5.2. Destination
4.5.3. TOD
Available time budgetResidual time
6.3. Assignment
4.6.1. Frequency
At-work sub-tours
4.6.2. Destination
4.6.3. TOD
3.1. Free Parking Eligibility3. Mobility 3.3. Transponder Ownership3.2. Car ownership
Allocated Tours
4.4.1. Frequency
4.4.3. Destination
4.4.4. TOD
4.4.2. Allocation
5.4. Stop Departure
Joint(household level)
Institute of Traffic Engineers Luncheon April 1, 2010
A relevant cartoon…
Institute of Traffic Engineers Luncheon April 1, 2010
Activity TypesTYPE PURPOSE DESCRIPTION CLASSIFICATION ELIGIBILITY
1 Work[1] 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)
Choice
Drive-Alone Free
Drive-Alone Pay
Shared 2 Free
Shared 2 Pay
Shared 3+ Free
Shared 3+ Pay
Walk Bike
Walk-Local Walk-BRT
Walk-Express Walk-LRT
Walk-Commuter
Rail
Drive-Alone Shared-Ride 2 Shared-Ride 3+
Non-Motorized
Walk-Transit
TransitAuto
Drive-Local Drive-BRT
Drive-Express Drive-LRT
Drive-Commuter
Rail
Drive-Transit
Modes
• Explicit toll versus non-toll choice• Explicit treatment of line-haul transit modes
Institute of Traffic Engineers Luncheon April 1, 2010
Treatment of Space: TAZs and MGRAs
Institute of Traffic Engineers Luncheon April 1, 2010
•About 10 MGRAs to 1 TAZ
•32k MGRAs Tot.
•All origins and destinations located at MGRA level
•Highway assignments still use TAZs
Transit Network, Stops and Access Points
Institute of Traffic Engineers Luncheon April 1, 2010
•About 2,500 transit access points (stops)
• Stop-to-stop skims (TransCAD)
•All transit boardings/alights located at TAPs
Transit Paths
Institute of Traffic Engineers Luncheon April 1, 2010
• On-the-fly path-building from origin MGRA, to boarding TAP, to alighting TAP, to destination MGRA
Institute of Traffic Engineers Luncheon April 1, 2010
Tour Destination, Time-of-Day, Mode, Stop Location
1. Select Primary Destination
2. Select Departure/Arrival Period
4. Select Stop Location
3. Select Primary Mode
Institute of Traffic Engineers Luncheon April 1, 2010
Time-Use Concept
5 23
1-Work
7-17
5-6 18-19 2-Discret
20-23
Recalculate residual time windows
Institute of Traffic Engineers Luncheon April 1, 2010
Tour-Based Model Output
HID PID TID PUR MOD SB SA OTAZ DTAZ S1TAZ S2TAZ TLOR TLDS1 1 1 2 1 0 1 943 987 0 964 1 3 1 1 2 1 2 1 0 943 731 856 0 3 3 1 2 1 4 1 0 0 943 952 0 0 1 2 1 3 1 2 4 1 1 943 565 698 982 1 2
Household Data, Person Data, Tour/Trip List
Other SummariesMaps, Graphics
Trip Tables
Assignment
Work Trip Frequency Distribution:Auto Ownership 1, Income Group 1-2
Estimated vs. Observed
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
5 8 11 14 17 20 23 26 29 32 35 38 41 44 47 50 53 56 59
Peak Highway Travel Time (minutes)
Freq
uenc
y ObservedEstimated
¯
Institute of Traffic Engineers Luncheon April 1, 2010
What Sort of Measures/Visuals are Now Possible?
• ABM results in a complete activity diary for all SANDAG residents– A wealth of activity/travel results– Just about any custom report/query/visual is now possible
• Scenario Testing– Capacity improvements– HOV, HOT lane scenarios– Cordon Pricing– Land-use policies– New Starts– Equity Analysis
• Example Outputs
Institute of Traffic Engineers Luncheon April 1, 2010
Tracing of Activities/Tours
Institute of Traffic Engineers Luncheon April 1, 2010
Mode Share by Person Type
Travelers By Age
15
30
90
45
60
75
0
Institute of Traffic Engineers Luncheon April 1, 2010
Persons Not At Home By TAZ and Hour
Institute of Traffic Engineers Luncheon April 1, 2010
Persons By TAZ and Hour (Daytime Population)
Institute of Traffic Engineers Luncheon April 1, 2010
Mean Delay Peak Period Travel
Institute of Traffic Engineers Luncheon April 1, 2010
Time Spent Traveling by Income & Person Type
Institute of Traffic Engineers Luncheon April 1, 2010
Institute of Traffic Engineers Luncheon April 1, 2010
1. Population Synthesis
2. Long-term
4. Daily
6. Trip level (4-Step Models)
2.1. Usual workplace / school
4.1. Person pattern type
Mandatory Non-mandatory Home
4.2.1. Frequency
Individual Mandatory Tours
4.6.1a. Frequency
At-work sub-tours
3. Mobility 3.2a. Car ownership
Individual Non-Mandatory Tours4.5.1a. Frequency & Purpose
5. Tour level5.2a. Stop frequency & Purpose
Daily Trip Productions By Purpose
Trip Distribution
Mode Choice
Trip Assignment
Year 1 (2009):
Simplified activity-based travel generation models estimated, implemented, and calibrated
Model Development Schedule
Institute of Traffic Engineers Luncheon April 1, 2010
• Year 2 (2010)– On-board survey data available– Tour mode choice, time-of-day choice, destination choice
• Year 3 (2011)– Trip-level models estimated, implemented – Toll transponder ownership – Employer-provided parking and parking lot choice
• Year 4 (2012)– Special market models (visitors, air passengers, special events)– PECAS (land-use model) integration– Model validation
Institute of Traffic Engineers Luncheon April 1, 2010
Questions and Discussion
Joel [email protected]