may 20, 2015 estimation of destination choice models using small sample sizes and cellular phone...
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![Page 1: May 20, 2015 Estimation of Destination Choice Models using Small Sample Sizes and Cellular Phone Data Roberto O. Miquel Chaitanya Paleti Tae-Gyu Kim, Ph.D](https://reader035.vdocuments.mx/reader035/viewer/2022081603/56649ea05503460f94ba2f22/html5/thumbnails/1.jpg)
May 20, 2015
Estimation of Destination Choice Models using Small Sample Sizes and Cellular Phone Data
Roberto O. MiquelChaitanya PaletiTae-Gyu Kim, Ph.D.
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Acknowledgements
• North Carolina Department of Transportation• Wilmington MPO
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Introduction
• Travel Demand Model for Wilmington, NC
• Total Population ~ 260,000• Total Area ~ 405 Sq mi• Visitor Attractions:
Downtown and Beaches
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Introduction …
• This enhanced model features:– Extended area– Refined TAZ system– Visitor model– Time-of-day components– Destination choice model
• No recent travel survey data• North Carolina NHTS Add-
on – Small sample size• Cellular Phone Data for
Origin-Destination
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Cellular Phone Data
• Identify study area origin-destination flows by trip purpose• Identify visitor trip movements in study area• Identify internal-external trip movements• Identify external-external trip movements• Calibrate Wilmington’s trip distribution models.
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Cellular Phone Data Sample
• One month of data (July)• 475,506 unique devices• 38,761 residents • 5.1% sample rate
• Visitors and residents• Daily trip tables• Directional purposes
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Resident Origin-Destination Flows
OW (Trips > 50)
HW (Trips > 50)
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Visitor Origin-Destination FlowsOO (Trips > 50)
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Destination Choice Model
• Destination choice for trip distribution• Model estimated using
– NHTS data for trip ends – no recent survey data– LEHD data for household earnings– Household characteristics and generalized cost skims from the
MPO model• NHTS Trips records – few Home Based Trips
Trip Purpose # Records
Home Based Work Trips 31
Home Based Shopping Trips 67
Home Based Other trips 107
Non Home Based Trips 212
205 records
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Destination Choice Model: Methodology
• 4 different trip purposes:– Home Based Work Trips ( HBW)– Home Based Shopping Trips (HBS)– Home Based Other (HBO) – Non Home Based Trips (NHB)
• Single equation incorporating different trip purposes
• 11 destination alternatives (out of 601 TAZs) – 10 randomly selected and actual destination choice – for model estimation
Exogenous variables and Interaction variables tying in different trip purposes
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Destination Choice Model: Methodology …
• Generalized cost=Time + Vehicle Operating Cost(VOC) + Toll Price
• Destination choice additionally accounts for:– Employment – Income– Earnings– Children
• Iterative technique - model estimation• Results validated using trip tables from cellular phone data
Labi and Sinha, 2011
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Destination Choice Model Results
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Model Validation
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 590
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HBW_TLD_Time
AirSageModel
Duration of Trips (min)
Perc
ent o
f Trip
s
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Model Validation
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 590
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HBO_TLD_Time
AirSageModel
Duration of Trips (min)
Perc
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Model Validation
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 590
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NHB_TLD_Time
AirSageModel
Duration of Trips (min)
Perc
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f Trip
s
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Summary and Conclusions
• Use of cellular phone data set helps to establish confidence in estimating a model using a small sample
• Very short trips revealed in the cellular phone data set seem consistent with behavior estimated from the NHTS
• Estimating destination choice models from small samples is not ideal, but is possible
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Thank You
Chaitanya PaletiCDM SmithRaleigh, NC
Roberto Miquel, AICPCDM SmithRaleigh, NC
Tae-Gyu Kim, Ph.D.NCDOT
Raleigh, [email protected]