preliminary evaluation of cellular origin- destination data as a basis for forecasting non-resident...
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Preliminary Evaluation of Cellular Origin-Destination Data as a Basis for Forecasting Non-Resident Travel
15th TRB National Transportation Planning Applications ConferenceMay 19, 2015Atlantic City, New Jersey
Ronald MiloneMetropolitan Washington Council of Governments (MWCOG)National Capital Region Transportation Planning Board (TPB)
Evaluation of Cellular O-D Data - 15th TRB Applications Conference2
Overview
Why cellular O-D data? Specifications of the data purchased Evaluation of data with respect to
Travel model outputs Land activity External traffic counts
Observations and impressions
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TPB modeled area
Evaluation of Cellular O-D Data - 15th TRB Applications Conference
2015 Population: 7 Million2013 VMT: 158 MillionArea: 6,800 Sq. milesZones: 3,722 TAZsAvg. Zone Area: 1.85 sq miMaj. Jurisdictions: 22Travel Model: V2.3.57
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Exogenous trip markets in the travel model
Evaluation of Cellular O-D Data - 15th TRB Applications Conference
Exogenous trip markets:• External trip-ends• Through trips• Taxi trips • University/School trips• Visitor/Tourist trips• Airport Passenger trips
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Selected AirSage Parameters
Evaluation of Cellular O-D Data - 15th TRB Applications Conference
Survey Period: April, 2014Selected Days: Typical Weekdays (Tue. through Thur.)Geography: 3,675 Internal TAZs, 12 External ShedsO-D Purposes: Nine (9):
Combinations of home, work, and otherResidence Classes: Six (6):
-Resident Worker -Home Worker -Inbound Commuter -Outbound Commuter -Short-Term Visitor -Long-Term Visitor
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External catchment areas
Evaluation of Cellular O-D Data - 15th TRB Applications Conference
• Geography used for summarizing external and through trips
• 12 External catchment areas (or “sheds”)
• Jurisdiction-based
• Designed around 47 external stations
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What IS a mobile device trip?
Evaluation of Cellular O-D Data - 15th TRB Applications Conference
Aggregate market flow Individual trip-makers are unknown HH characteristics of traveler are unknown
Possibly a combination of linked and unlinked trips Vehicle type /mode of travel is unknown Path of O-D is unknown Subject to cellular signal detection
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Assumed equivalency of AirSage trip coding and modeled purposes (P-A format)
Evaluation of Cellular O-D Data - 15th TRB Applications Conference
AirSage Resident StatusAirSage Resident Home Inbound Outbound Short-Term Long-Term
Purpose Class Worker Worker Commuter Commuter Visitor VisitorHome-Work Home-Based-Work (HBW)Work-Home* Non-ResidentHome-Home (Non-Modeled)Home-Other Home-Based Non-Work (HBNW)Other-Home*Work-WorkWork-Other Non-Home-Based Work-Related (NHW)Other-WorkOther-Other Non-Home-Based Non-Work-Related (NHO)* - Origin/Destination TAZs are transposed
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Comparison of internal trips by purpose: AirSage trips vs. TPB modeled motorized person trips
Evaluation of Cellular O-D Data - 15th TRB Applications Conference
2015 TPB Modeled 2014 AirSage Diff.Purpose I-I Motor. Person Trips Cellular Trips (AirSage - Model) % Diff.HBW 3,991,335 5,546,469 1,555,134 39.0%HB NonWork 10,333,543 10,324,649 -8,894 -0.1%
HB Subtotal 14,324,878 15,871,118 1,546,240 10.8%
NH Work 1,664,922 1,667,905 2,983 0.2%NH Non-Work 3,332,298 1,411,836 -1,920,462 -57.6%
NH Subtotal 4,997,220 3,079,742 -1,917,478 -38.4%
Total 19,322,098 18,950,860 -371,238 -1.9%
-Overall number of AirSage trips and modeled person trips is about equal-Number, share of AirSage HB trips is higher than modeled trips-Number, share of AirSage NH-trips is lower than modeled trips
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Comparison of internal trip lengths by purpose:AirSage trips vs. TPB modeled motorized person trips
Evaluation of Cellular O-D Data - 15th TRB Applications Conference
2015 Modeled Psn. Trips 2014 AirSage Trips Difference (AS-Model)Trip Length % Trip Length % Trip Length %
Purpose (mi) Intra-Zonals (mi) Intra-Zonals (mi) Intra-ZonalsHBW 15.3 4.2% 13.0 0.4% -2.3 -3.8%HB NonWork 6.4 21.9% 8.0 27.5% 1.6 5.5%
HB Subtotal 8.8 17.0% 9.7 18.0% 0.9 1.0%
NH Work 7.5 25.3% 9.4 22.0% 1.9 -3.3%NH Non-Work 5.2 26.0% 9.7 18.2% 4.5 -7.9%
NH Subtotal 5.9 25.8% 9.5 20.2% 3.6 -5.6%
Total 8.1 19.3% 9.6 18.4% 1.5 -0.9%
-Overall trip lengths and intra-zonal percentages are consistent-Overall HB trip lengths are consistent, but HBW trips are shorter-Overall AirSage NH trips are longer that the modeled NH trips
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Jurisdictional daily trip flows:AirSage trips vs. modeled person trips
Evaluation of Cellular O-D Data - 15th TRB Applications Conference
Total AirSage Trips vs. Modeled Motorized Person Trips
0.00
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0.00 0.50 1.00 1.50 2.00 2.50 3.00
AirS
age
Dai
ly T
rips (
mill
ions
)
TPB Model: Motorized Daily Person Trips (millions)
-Overall daily trip flows at jurisdiction levels agree reasonably -AirSage flows within large suburban jurisdiction are less than modeled flows
Line of Perfect Agreement
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AirSage total Home-Based productions vs. households: TAZ level versus district level
Evaluation of Cellular O-D Data - 15th TRB Applications Conference
AirSage 2014 TAZ Level HB-Productions vs. 2014 Rnd8.3 HHs
AirSage 2014 District Level HB-Productions vs. 2014 Rnd8.3 HHs
y = 4.3751x + 1215.4R² = 0.615
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0 2 4 6 8 10
AirS
age
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uctio
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hous
ands
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Zonal Households (thousands)
y = 5.5805x + 3045.1R² = 0.9049
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0 10 20 30 40 50District Level Households (thousands)
AirS
age
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Pro
ducti
ons (
thou
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- Logical TAZ level correlation exists, but scatter is considerable- Data aggregation to the district level reduces data noise
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AirSage HBW attractions vs. employment:TAZ level versus district level
Evaluation of Cellular O-D Data - 15th TRB Applications Conference
AirSage 2014 Zonal HBW Attractions vs. 2014 Rnd8.3 Jobs
AirSage 2014 District Level HBW Attractions vs. 2014 Rnd8.3 Jobs
y = 0.7971x + 624.81R² = 0.5375
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0 10 20 30 40 50 60
AirS
age
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racti
ons (
thou
sand
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Zonal Employment (thousands)
y = 1.1596x + 1881.1R² = 0.8757
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20
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0 20 40 60 80 100District Level Employment (thousands)
AirS
age
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Att
racti
ons (
thou
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s)
-Correlation logical, but weak at the TAZ level-Data aggregation at the district level reduces data noise (again)
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2014 AirSage external/through trips vs. 2013 traffic counts (1000s)
Evaluation of Cellular O-D Data - 15th TRB Applications Conference
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200
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2013_Count 2014 AS Extl&Thru Trips
-General distribution pattern is reasonable-Overall AirSage crossings at external cordon exceed counts by 30%
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Distribution (%) of E-I trips by jurisdiction:AirSage vs. 1994 Auto External Survey
Evaluation of Cellular O-D Data - 15th TRB Applications Conference
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
35.00%
DC
Mtg PG Ar
l
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How
AnnA
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KG
1994 External Auto Survey
AirSage 2014
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
35.00%
40.00%
DC
Mtg PG Ar
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Alex FF
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How
AnnA
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1994 External Auto Survey
AirSage 2014
HBW Trips Daily Trips
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AirSage non-resident trip-ends
Evaluation of Cellular O-D Data - 15th TRB Applications Conference
Principal generators: 3 commercial airports & Union
Station Tourist attractions
Monuments, museums Government buildings National Zoo Special attractors
Verizon Center National Harbor Annapolis Harbor
Historic Sites Mega shopping centers
Evaluation of Cellular O-D Data - 15th TRB Applications Conference17
Findings:
Cellular O-D trips vs. modeled person trips: Global trips and trip lengths compare reasonably Trips by modeled purpose show differences
Cellular O-D trips correlate logically with land activity, but: Inconsistencies are evident at the TAZ level of analysis Aggregation to the district level dampens the noise
Evaluation of Cellular O-D Data - 15th TRB Applications Conference18
Findings:
Cellular O-D external and through trips: Cellular trip patterns appear reasonable Cellular trips crossing the external cordon exceeds
counts by 30% Ability to “ground-truth” O-D movements by ground
counts is limited
Cellular non-resident (visitor) trip generators appear consistent with expectations
Evaluation of Cellular O-D Data - 15th TRB Applications Conference19
Final thoughts
Cellular O-D data is highly sampled, but it’s different from modeling data that planners normally use
Cellular O-D data has inherent uncertainty: Household characteristics of travelers Mode of travel Path choice
The use of this data in practice hinges on: Understanding how cellular data is different Addressing uncertainties (travel mode in particular)