in this presentation, we will: describe each step the compass model and show comparable steps in...
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In this presentation, we will: Describe each step the Compass model and show comparable steps in the IRM. Compass = What, , Where, How IRM= Who , What, When, Where, How, Why Take a household through these steps and show how the household is treated differently in the two models. - PowerPoint PPT PresentationTRANSCRIPT
In this presentation, we will:
1. Describe each step the Compass model and show comparable steps in the IRM.
• Compass = What, , Where, How• IRM= Who, What, When, Where, How, Why
1. Take a household through these steps and show how the household is treated differently in the two models.
2. Show how the additional complexity of the IRM provides additional sensitivity (we can test and represent more.) Reality Is more complicated than 4 step models can show.
– “Putting on the Glasses”
The New Regional Model - Focus
Big Picture• Effects of development pattern/design
– UGB scenarios– TOD– Urban Centers– “New” Urbanism vs traditional 20th century
suburban patterns– Mixed versus single use
The New Regional Model - Focus
Big Picture• Explicit modeling of bike/ped.• Time of day modeling• Person/household characteristics:
– Age– Gender– Household population composition
• Presence and age of children• Number of workers
The New Regional Model - Focus
Big Picture• Number of vehicles• Work at home• Full induced demand for the first time
– Trip/tour suppression/re-structuring– Trip-length changes– Mode changes– Time of day changes– Path changes
The New Regional Model - Focus
Details for Tekkies• Modeling trips in tours, not separately• Each household and job is given a precise
location (xy point)• Each household/person in the region is
represented individually – PUMS-level data
The New Regional Model - Focus
Details for Tekkies• More / real trip purposes:
– Old model: home-based work, home-based non-work, non-home-based
– New model: work, school, escort, shopping, eat meal, social-recreation, personal business
The New Regional Model - Focus
Bottom Line• The model operates at the level at which
decision actually are made– Usually the person– Occasionally the household
The New Regional Model - Focus
Bottom Line• The model operates at the level at which
decision actually are made– Usually the person– Occasionally the household
The New Regional Model - Focus
Bottom Line• disaggregate modeling means recognizing
that things are different, and describing them as they are:– Person/household type– Tour/trip type– Location– Time of day
The New Regional Model - Focus
Bottom Line• better modeling now – better ability to
improve in the future – better ability to run scenarios– Example – where will the elderly live?– Example – use of hybrid / electric vehicles.
Compassi. Network Processing
ii. Area Type
1. Trip Generationi. Highway/Transit Skims
2. Trip Distribution3. Mode Choice
i. Parking Cost
ii. Time-of-Day
4. Highway/Transit Assignment
1. Population SynthesizerNetwork Skims
Aggregate Mode/Destination Choice Logsum Generator
Mode Choice Logsum Generator
2. Regular Workplace Location Choice
3. Regular School Location Choice
4. Auto AvailabilityIntermediate Stop Logsum Generator
5. Daily Activity Pattern Choice
IRM
Exact Number of Tours Choice Work Tour Destination Type Choice ModelWork-Based Subtour Generation Choice
6. Tour Primary Destination Choice
7. Tour Main Mode Choice8. Tour Time of Day ChoiceIntermediate Stop Generation Choice
Intermediate Stop Location Choice
9. Trip Mode Choice10. Trip Departure Time Choice11. Assignment
How does the model do its job?It answers these questions:
– What kind of people…– In what kinds of households…– Living in what locations...– Working and going to school where and how– Do what kinds of things during their day…– Requiring them to make what kinds of trips…– To what locations…– By what travel modes…– By what paths through the transportation system?– At what times?
How does the model do its job?It answers these questions:
–What kind of people…– In what kinds of households…– Living in what locations…– Working and going to school where and how– Do what kinds of things during their day…– Requiring them to make what kinds of trips…– To what locations…– By what travel modes…– By what paths through the transportation system?– At what times?
?? ?
What do we know about the people in the households in the Compass model?
Answer: nothing.Example Family:Adult - Age?Job status?Adult – Age?Job status?Child – Age?Student status?RelationshipTo adults?
Example Family:Mother, Age 33Part Time Service WorkerFather, Age 34Full Time Education WorkerSon, Age 4Pre-School StudentFamily Income : $61,000
What do we know about the people in the households in the IRM?
Answer: Anything included in the Census.
What do we know about individual people in Compass?
Person Data in the IRM
Person IDHousehold ID Age
School Grade Gender
Hours Worked Per Week
Income Earned
Employ Category
556053 321005 29 0 Female 40 23400 Service556054 321006 8 2 Male 1 0 0556055 321007 61 0 Male 16 32500 Retail
Person ID RaceRelationship to Householder
School Grade
Weeks Worked per Year
Marital Status
Poverty Status
Employ Status
556053 Afr American Householder 0 52 Married 0 Full Time556054 White Son 2 0 Single 1 Not556055 Asian Householder 0 32 Single 0 Part Time
How does the model do its job?It answers these questions:
– What kind of people…
–In what kinds of households…– Living in what locations...– Working and going to school where and how– Do what kinds of things during their day…– Requiring them to make what kinds of trips…– To what locations…– By what travel modes…– By what paths through the transportation system?
Household Data in Compass
Household Data in the IRM
Household ID TAZ
Household Income
Number of People
Number of Children
Number in Household Under Age 5
Number in Household age 5 to 15
342652 307020 55000 1 0 0 0342653 307020 51000 2 1 1 0342654 307020 56000 6 4 2 2
Years at Residence Race
Building Size
Number of University Students
Own or Rent
Distance from household to nearest transit stop
Number of Full Time Workers
6 1 1 0 1 0.5 11 3 2 0 0 1 13 2 6 0 1 2 2
How does the model do its job?It answers these questions:
– What kind of people…– In what kinds of households…
–Living in what locations...– Working and going to school where and how– Do what kinds of things during their day…– Requiring them to make what kinds of trips…– To what locations…– By what travel modes…– By what paths through the transportation system?– At what times?
307320
705110301460
202120
202460
307200
703170
307120
307060
704160
307130
302250
306230
705150
202310
301520
202280 307300
301470
705160
202130
307010
301550
307160
202330
307050
307020
705120704170
307150
202250
307220
307040
705100
704130
704060
202150
307180
307140
202260
705140
202140
704100
307260
704120
307230
106170
307330
704030
306020
704050
309010
202270
705180
704110
301450
307280
704070
704180
307240
302240
202320
705170
301510704210
307110
307310
704230
307100
301490
301360
307070
307270
307170
307250
202300
307190
306010301500
704200
301480704090
307290
705130
202290
307090
704080
307030
306210
704220
704190
202470
307080
202340
120th Av e
I-25
Ok, so what do we know about household locations in Compass?Answer: They are located in traffic analysis zones, and…
And what do we know about households in the IRM?
We know a lot more about households in the IRM: why is that
better?• Households with more drivers and workers own
more cars.• Households with more cars make different
choices than households with fewer cars:– They make more tours– And use drive mode for them more often
• Point-level location means we actually know:– Walk distance to/from transit– Walk trip distance– Bike trip distance– Short auto trip distance.
We know a lot more about people in the IRM:
why is that better?• Lots of reasons!
– People tend to work in places where there are a lot of jobs in their field.
– Kids tend to go to school where their older siblings go.
– Workers tend to go to work, students tend to go to school, retired people tend not to do either (etc.)
– People with kids tend to cart them around a lot, and drive doing it.
How does the model do its job?It answers these questions:
– What kind of people…– In what kinds of households…– Living in what locations...
–Working and going to school where and how
– Do what kinds of things during their day…– Requiring them to make what kinds of trips…– To what locations…– By what travel modes…– By what paths through the transportation system?– At what times
405090
406110
412360
412350
412390
405080
412380 412370
412190
412340 412330
412312
412311
412324412207
412204
412208
412203
412209412323
412202412201
412206
412215
412205
412213
412168
412223
412236
412167
412224
412322
412321412214
412211
412221
412222
412212
Civ ic Ce nte r Park
Colfax Av enue
Broa
dway
What do we know about where jobs are in Compass?
Answer: they are in traffic analysis zones, and…
What do we know about where jobs are in the IRM?
Job Data in Compass
Job Data in the IRM
Building ID Legal NameEmployment Type
Number of Employees Address
115497 Colorado State Glass and Mirror Retail 9 1120 Cooke Ct18663 Lookin Good Day Spa Service 2 6662 W 38th Ave
115498 Bruner Consulting Inc Service 1 1117 Alder Way
Building ID X Coordinate Y Coordinate Wages115497 5689090 4572891 $62,300
18663 4089972 57890849 $5,200115498 5575757 2890798 $6,700
What do we know about schools in Compass?
And about Schools in the IRM?
We know a lot more in the IRM:why is that better?
• Tie the kind of job people have to the kind of company and its location.
• We know precisely how far the company is from the transit stop.
• Non-university students tend to go school in their home school district.
• We know precisely how far the school is from each home.
How does the model do its job?It answers these questions:
– What kind of people…– In what kinds of households…– Living in what locations...– Working and going to school where and how
–Do what kinds of things during their day…
–Requiring them to make what kinds of trips…
– To what locations…– By what travel modes…– By what paths through the transportation system?– At what times?
What do we know about what people do during their day in Compass?
• Number of work trips by households in the zone.
• Number of other kinds of trips made by households in the zone.
Table 13: Final HBW Trip Production Rates Household Size Income Group
1 2 3 4 5+ Low (Less than $15,000) 0.515 1.339 1.339 1.339 2.575 Middle ($15,000 - $74,999) 1.236 1.854 2.060 2.266 2.575 High ($75,000 or more) 0.927 1.854 2.472 2.472 2.060 Source: PRD_HB_R.asc TransCAD file dated 10/22/2003
Table 14: Final HNW Trip Production Rates
Household Size Income Group 1 2 3 4 5+
Low (Less than $15,000) 1.272 2.438 4.982 4.982 4.982 Middle ($15,000 - $74,999) 1.378 3.392 4.876 7.526 10.282 High ($75,000 or more) 1.590 2.968 4.876 9.540 10.282 Source: PRD_HB_R.asc TransCAD file dated 10/22/2003
Table 15: Final NHB Trip Production Rates
Household Size Income Group 1 2 3 4 5+
Low (Less than $15,000) 0.784 0.784 2.912 2.912 2.912 Middle ($15,000 - $74,999) 1.344 2.576 2.912 3.808 3.584 High ($75,000 or more) 2.240 3.248 4.256 4.816 5.936 Source: PRD_HB_R.asc TransCAD file dated 10/22/2003
Compass Trip RatesNote also: only three types of trips- Home-Based Work, Home-Based Non-Work, and Non-Home Based
What do we know in the IRM?
• Mostly about things they do when they leave the house:– Exception: we know if they work at home.
• Out-of-home activities: work, school, shop, eat meal, socialize, escort others, personal business.
Doing what? Primary reason for going out
Just making a stop along the way
Working x
Going to school
Shopping
Escorting others x
Socializing
Eating out x
Personal business
IRM Activities in the Day
HOMEDAY CARE
PARK AND RIDE
WORKRESTAURANT
Walk
TOUR-BASED MODEL1 home-based work tour• 1 work- based meal tour• 2 intermediate serve passenger
stops
TRIP-BASED MODEL• 4 non-home based trips• Two home-based other trips• NHB trip poorly handled...
Tours Generated in the IRM
Doing what? Primary reason for going out
Just making a stop along the way
Working x
Going to school
Shopping X
Escorting others
Socializing
Eating out x
Personal business
IRM Activities in the Day
HOME WORK
STORE
TOUR-BASED MODEL• 1 home-based work tour• 1 shopping stop
TRIP-BASED MODEL• 1 home-based work trip• 1 non-home-based trip• 1 home-based non work trip
Tours Generated in the IRM
Doing what? Primary reason for going out
Just making a stop along the way
Working
Going to school X
Shopping
Escorting others
Socializing
Eating out
Personal business
IRM Activities in the Day
passenger
HOME DAY CARE
13 TOTAL TRIPS BY HOUSEHOLD:1 HOME-BASED WORK5 HOME-BASED NON-WORK7 NON-HOME BASED:
TOUR-BASED MODEL• 1 school tour
TRIP-BASED MODEL• 2 home-based non work trips
TOTAL TOURS BY INDIVIDUAL:WOMAN: 1 HOME BASED WORK TOUR
1 WORK-BASED MEAL TOUR 2 SERVE PASSENGER STOPS
MAN: 1 HOME BASED WORK TOUR 1 SHOPPING STOP
CHILD: 1 HOME-BASED SCHOOL TOUR
Tours Generated in the IRM
Why is it better that the IRM is more detailed in describing why
people travel?• Able to depict how changes in
demographics, like a larger older population, can cause different amounts and types of travel.
• Able to represent how much accessibility and mixed use density a person’s home zone has to other locations impact the amount of travel they do.
How does the model do its job?It answers these questions:
– What kind of people…– In what kinds of households…– Living in what locations...– Working and going to school where and how– Do what kinds of things during their day…– Requiring them to make what kinds of trips…
–To what locations…– By what travel modes…– By what paths through the transportation system?– At what times?
Table 23: Final HBW Trip Attraction Rates by Income Group
Income Group
Trip Attraction Rate per:
HouseholdProduction / DistributionEmployee
RetailEmployee
ServiceEmployee
Low (Less than $15,000) 0.003 0.027 0.082 0.070
Middle ($15,000 - $74,999) 0.020 0.787 0.916 0.776
High ($75,000 or more) 0.014 0.269 0.250 0.440
Total 0.037 1.083 1.248 1.286
Source: ATTHBW_R.asc TransCAD file dated 10/22/2003Notes: 1 Total rates shown only for comparison with models from other regions.
To what location do people go to do the activities? In Compass, the trip attractions and productions are used to predict trip origins and destinations.
n
kkikik
jijijiij
AFK
AFKPT
1
Tij = trips between TAZ i and TAZ jPi = productions in TAZ iAj = attractions in TAZ jKij = “K-factor” adjustment between TAZ i and TAZ jFij = “friction factor” between TAZ i and TAZ ji = production TAZj = attraction TAZn = total number of TAZs
In Trip-based models, the gravity model predicts the number of trips from origin to destination based on the number of productions in the origin zone and attractions in the destination zone.
Friction Factors are calibrated so that modeled trip length frequency distributions match observed trip length frequency distributions.
Trip Distribution Output: O-D matrix
Compass model outputFrom Trip Distribution:
Home-Based Work Trips from Zone 307020
Compass model outputFrom Trip Distribution:
Home-Based Non-Work Trips from Zone 307020
Tour origin
Tour destination
Where does the woman go during her day? The IRM destination choice models could predict the following for the woman:
The IRM destination choice models could predict the following for the man:
Why is it better how destinations are chosen in the IRM?
• Can test how desirable a location is by how easy it is to get there by all modes including transit.
• Can test how mixed use density causes a destination to be more desirable
• Can test how a person chooses destinations close to their usual work or school zone.
How does the model do its job?It answers these questions:
– What kind of people…– In what kinds of households…– Living in what locations...– Working and going to school where and how– Do what kinds of things during their day…– Requiring them to make what kinds of trips…– To what locations…
–By what travel modes…– By what paths through the transportation system?– At what times?
How does mode choice work in Compass?
• Each trip purpose has a model (HBW, HBNW, NHB.)
• All trips between each zone-pair are treated as being identical.
• Trips that are really in the same tour know nothing about each other.
• Outputs are trip tables by mode by purpose (and by income for HBW.)
Compass mode choice output: O-D Trips by Mode
HOME DAY CARE
PARK AND RIDE
WORKRESTAURANT
Drive- SR2
Drive to Transit
Walk
Example IRM Mode Choices for the Woman
HOME WORK
STORE
Drive Alone
Example IRM Mode Choices for the Man
passenger
HOME DAY CARE
Drive- SR2
Example IRM Mode Choices for the Child
Why is the IRM better at representing mode choice?
• Has bike and walk modes as a choice• Represents how Origin and destination
employment density impacts a person’s mode choice
• Represents how a person’s auto availability impacts mode choice
• Allows school tours and work-based subtours to have different mode choices than other tours (Compass just has home-based other)
How does the model do its job?It answers these questions:
– What kind of people…– In what kinds of households…– Living in what locations...– Working and going to school where and how– Do what kinds of things during their day…– Requiring them to make what kinds of trips…– To what locations…– By what travel modes…– By what paths through the transportation system?
–At what times?
When do trips occur?
CompassVery Simple Model:Time-of-Day Factors
For Example, 68% of Home-Based Work Tours, arrive at work from 6:30 am –9:00 am.
0
10,000
20,000
30,000
40,000
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60,000
70,000
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Time Period
Expa
ned
Vehi
cle
Hour
s Tr
avel
ed
OP1 AM1 AM3AM2 OP3OP2 OP4 OP1PM3PM2PM1
Compass: Time-of-Day Factors applied (based on total observed vehicles hours observed in each period)
Compass Model Time of Day Outputs: O-D Trips by Time of Day
IRM Time of Day Models
• Tour time-of-day:– Predicts start and end of tour– Higher priority tours run first, block out times
of day not available to lower priority toursTour time-of-day:
• Trip time-of-day:– Predicts departure time from each stop– In-transit time known, so serves as departure
time and duration model
HOME DAY CARE
PARK AND RIDE
WORKRESTAURANT
time Time
time
Example IRM Mode Choices for the Woman
Why are the IRM time of day models better?
• Can better represent time-shifting due to congestion
• Can represent how changes in demographics impact time of day choices, i.e. more retired people means less congestion peaking
• Can represent how a person’s mode choice impacts what time of day they travel, i.e. I can’t take the bus until 3:15 PM
Tour ID Person ID Tour PurposeTour Origin Point ID
Tour Destination Point ID Tour Mode
Tour Destination Arrival Time
Tour Destination Departure Time
541298 127804 Work 987130 1384689 Drive to Transit 8:00 AM 5:00 PM541299 127804 Restaurant 1384689 1578908 Walk 12:00 PM 1:00 PM541300 127805 School 987130 693920 Shared Ride 2 7:00 AM 6:00 PM541898 127806 Work 987130 578925 Drive Alone 8:00 AM 5:00 PM
Example Tour Outcomes for the Family : Purpose, Origin, Destination Mode, Time of Day
Finally, in both the IRM and Compass models the choices of where to go, when, by what mode are
assigned to the networks. Example AM Peak Highway Flows:
The woman drives with the child to the daycare down 120th, then takes the bus route 122X to Civic Center, and walks from the station to work down Broadway.
Key Model Differences
• Trip/tour generation sensitivity.• Time-of-day sensitivity.• Development pattern sensitivity.• Modeling of non-motorized modes and
walk access to transit.• Trips connected in tours.• Person-level decisions made at the person
level – using many person characteristics.
Scenario Sensitivity Examples- Why the IRM is better?
How does putting on the glasses help us see better?
• Effects of aging population or other changes in demographics.
• Effects of neighborhood “gentrification.”• Enhanced EJ evaluation.• Better evaluation of “induced demand.”• “Peak spreading” effects.• Effects of transit-oriented development.• Effect of built environment on Bike and Ped
Movement
Walk Mode SharesExample Output
Bike Mode SharesExample Output
Factors that make a trip more likely to use walk/bike modes
Factors that make a trip less likely to use walk/bike modes
PERSON CHARACTERISTICS•No car in Household•Fewer cars than drivers•Low income•University student•Meal or Social Trip Purpose
BUILT ENVIRONMENT•Mixed use origin/destination•Intersection density•CBD destination•Residential density
PERSON CHARACTERISTICS•High income•Age over 50•Female•Preschool age•Driving age HS student
BUILT ENVIRONMENT•Rural origin•Long walk/bike time
A Bit on Status
• All models estimated (around 50 or so.)• Database design complete.
– Suzanne Childress will talk more about this.• Software 2/3 complete.
– Jen Malm will talk more about this.