Preliminary Evaluation of Cellular Origin- Destination Data as a Basis for Forecasting Non-Resident...

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

3

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


Exogenous trip markets:• External trip-ends• Through trips• Taxi trips • University/School trips• Visitor/Tourist trips• Airport Passenger trips

5

Selected AirSage Parameters


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


• 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?


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)


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


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


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


Total AirSage Trips vs. Modeled Motorized Person Trips

0.00

0.50

1.00

1.50

2.00

2.50

3.00

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


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

0

10

20

30

40

50

60

0 2 4 6 8 10

AirS

age

HB-

Prod

uctio

ns (t

hous

ands

)

Zonal Households (thousands)

y = 5.5805x + 3045.1R² = 0.9049

0

50

100

150

200

250

0 10 20 30 40 50District Level Households (thousands)

AirS

age

HB

Pro

ducti

ons (

thou

sand

s)

- 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


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

0

10

20

30

40

50

0 10 20 30 40 50 60

AirS

age

HBW

Att

racti

ons (

thou

sand

s)

Zonal Employment (thousands)

y = 1.1596x + 1881.1R² = 0.8757

0

20

40

60

80

100

120

0 20 40 60 80 100District Level Employment (thousands)

AirS

age

HBW

Att

racti

ons (

thou

sand

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)


0

200

400

600

800

1,000

1,200

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


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35.00%

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1994 External Auto Survey

AirSage 2014

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35.00%

40.00%

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AirSage 2014

HBW Trips Daily Trips

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AirSage non-resident trip-ends


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


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


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


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)

Preliminary Evaluation of Cellular Origin- Destination Data as a Basis for Forecasting Non-Resident...

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