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TRANSPORTATION PROGRAMS
Building a Database for Estimation of an Advanced Activity-Based Travel Model
from the NHTSPetya Maneva (Presenter), Vladimir Livshits
Maricopa Association of Governments (MAG), Phoenix, AZAichong Sun (PAG), Tuscon, AZ
Peter Vovsha, Surabhi GuptaParsons Brinckerhoff, New York, NY
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Survey Time Line
Mar-08 Apr-08
May-08 Jun-08
Jul-08 Aug-08
Sep-08 Oct-08
Nov-08 Dec-08
Jan-09 Feb-09
Mar-09
Sept.
Oct.
Nov. 2008
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7,068 HH,Single dayWeekday Travel5,067 HH(615 incomplete)10,956 Persons41,444 Trips
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Quality Checks: Half-Tour and Tour Mode
Mode Which Trips? Half- Tour Mode
Tour Mode
Unknown Some Trips on Half-Tour Can Identify Can Identify
All Trips on Half-Tour Can not identify
From other half-tour (Symmetry)
All Trips on Tour Can not identify
Can not identify
Known, Not Available
Some or All Trips Not Available
Not Available
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Quality Check: Start/End at Home
Start/End Example Validity Remark
Start not from Home
Trip from Airport/Outside of Region
Valid reason
Missing previous Trip Invalidreason
FrequentCase
End not at Home
Trip to Airport/ Outside of Region
Valid reason
Missing last trip Invalidreason
FrequentCase
Completeness of tours in terms of starting and ending at home; the following cases are distinguished:
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Consistency of time-related tour attributes Missing Departure / Arrival Trip Time Conflicting trip/activity time chain
Arrival time before departure time Moving backward in daily schedule
Unrealistic reported trip duration vs. mode-specific skims from model
Fullness of trip destination coding Missing/unknown destination zones Destination outside the modeled region
(intercity trips)
Quality Checks
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Identify HH members age less than 5 years Extract joint trips of other HH members with
kids under 5 years reported Is trip part of fully and partially joint tours ?
Fully Joint Tour – same trip information Partially Joint Tour - identify drop off or pick up?
Drop-off – set destination purpose to school* Pick-up – set origin purpose to school*
Imputed Trips = 1,961, Tours = 828
Imputing Trips for Household Members – under 5 years
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Consistency of reported joint activities
Resolving data conflicts and creating a consistent entire-household pattern was developed and applied.
Impute Trips for Adults Only for Fully Joint Tours No conflict of schedule with other
reported trips 292 trips, 127 Tours imputed
Joint Activities
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Daily Tour Rate by Person Type
AFTER SYNTHESIZING TRIPS
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Logical checks Jobs (for worker occupation) available in Work
location TAZ? Workers are classified by 5 occupation categories
Sales, marketing Clerical, administrative, retail, Production, construction, farming, transport Professional, managerial, technical Personal care or services
Jobs in each TAZ are classified by 2-digit NAICScodes (26 categories) – correspond to 5 occupation categories
Students – student type (k-8, high school, college) vs. enrollment
Reconcile Trip Recordswith Land Use at Destination
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Sampling: Conduct interviews by cell phone and Internet Better represent respondents by age Better represent Hispanics
What Can Be Improved
Household Ethnicity 2008 NHTS Weighted 2008 ACS
Hispanic 10.50% 30.87%
White 77.50% 58.63%
Black/African American 4.60% 4.10%
American Indian 2.90% 1.86%
Asian/Pacific Islander 1.10% 2.86%
Other, Refused, etc. 3.40% 1.68%
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Tours by Purpose & Aggregate Mode (MAG/PAG NHTS)
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Completeness of Trip Records
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70%
75%
80%
85%
90%
95%
100%
Valid Mode Closed Tour Valid Time ValidPrimary
Destination
All Valid SymmetricMode
MAG/PAG
CMAP
MTC
ARC
SANDAG
Completeness of Tour Records
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Good quality overall: Reasonable trip & tour rates per person &
HH comparable to other regions Validity and completeness of trip records
at the level of other surveys or better Can be used for development of advanced
ABM but requires processing & imputations
Conclusions - MAG/PAGNHTS Survey
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Thank you!
Questions?
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Good quality overall: Reasonable trip & tour rates per person & HH comparable
to other regions Validity and completeness of trip records at the level of
other surveys or better Can be used for development of advanced ABM but requires
processing & imputations Lessons learned:
Incomplete HHs with missing persons – valid survey criteria Very small sample of transit users Children under 5 are not included Inconsistencies between joint travel records (GPS,
automatic logic checks) Many problems can be fixed by subsequent manual quality
control, analysis, complementary data collection and imputation
Conclusions - MAG/PAGNHTS Survey
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Logical checks: Non-Mandatory trips by purpose
Employment or Other Land Use Shopping Maintenance Eating
Out Visiting Discretionary
Retail √ √ √ √
Information √
Real Estate, Renting, Leasing √
Health Care, Social Assistance √ √
Arts, Entertainment √ √
Accommodation, Food Services √ √ √
Public Admin √
# Households √ √
Reconcile Trip Recordswith Land Use at Destination
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Daily Tour Rate by Person Type
No Travel Reported for Children under 5 years
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SAN DIE GO (SANDAG)
ATLANTA (ARC)
BAY AREA (MTC)
CHICAGO(CMAP)
PHOENIX –TUCSON
(MAG/PAG)NHTS
Survey Year 2006 2001 2000 2007-08 2008
#HHs 3,651 8,069 15,064 14,315 7,068
#Days 1 2 2 1-2 1
Cross-Region Comparison
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Analysis of discrepancies & fixes (manual): Geocoding errors Problem with Land Use data Survey coding errors
Worker job type Student type definition
Reconcile Trip Recordswith Land Use at Destination
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Data Processing
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Person Type Work School University Others
Full-time worker 2,834 0 4 2,176
Part-time worker 482 0 0 1,048
University student 102 0 249 251
Non-worker 64 4 5 2,636
Retiree 19 0 0 3,046
Driving school child 28 232 0 151
Pre-driving school child 3 1,016 0 616
Pre-school child 0 88 0 53
Tours by Purpose & Person Type (MAG/PAG NHTS)
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Analysis of discrepancies and fixes (manual): Survey mode coding errors Compare reported trip duration to skims
Trip Duration = β*Skim
PAG skims are a bit too fast; Revision is underway
Geocoding fixes for availability of Express/Rapid Bus
Reconcile Trip Records with Level-of-Service (LOS) Skims
Trip Mode β (MAG) β (PAG)Highway 1.01 1.15Transit (Bus) 0.85 1.20
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Logical checks: Availability of reported mode
Transit IVT = 0 (by mode) Drive option for person under 16 yrs
Unrealistic reported trip duration vs. mode-specific skims from model
Number of records by modes No valid observations for Commuter
Rail & Urban Rail Very few cases for Express/Rapid bus
Reconcile Trip Records with Level-of-Service (LOS) Skims
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Tours by Purpose & Mode (MAG/PAG NHTS)
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0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.09
0.1
Under 5 years
5 to 9 years
10 to 14
years
15 to 17
years
18 and 19
years
20 years
21 years
22 to 24
years
25 to 29
years
30 to 34
years
35 to 39
years
40 to 44
years
45 to 49
years
50 to 54
years
55 to 59
years
60 and 61
years
62 to 64
years
65 and 66
years
67 to 69
years
70 to 74
years
75 to 79
years
80 to 84
years
85 years and over
Variation in Respondent Age Distribution 2008 ACS2008 NHTS
Per
cen
tag
e
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