Methods for Conducting a Large-Scale GPS-Only Survey of Households

Greg Giaimo & Rebekah Anderson, Ohio Department of Transportation

Laurie Wargelin & Jason Minser, Abt SRBI

13th TRB National Transportation Planning Applications Conference

May 11th, 2011

History

• Cincinnati’s last HIS was conducted in 1995 by MORPACE

• 2010 Model Update – Wanted a new HIS

• GPS survey design chosen due to known problems with travel under-reporting

• Funded through ODOT SPR Research

Research

• Test logistical issues for large scale GPS deployment such as:– Deployment/Attrition/Device Cycling– Recruitment & child diary surveys needed

to supplement GPS data collection– Lack of trip purpose, mode, occupancy, or

cost data from passive GPS devices– Use of a Prompted Recall survey to impute

the trip purpose and mode.– Participation Rates by demographic

category

Survey Method Overview

• Address based sample frame• Internet recruiting option• GPS units for all HH members > 12• Simple diary for children < 12• Obtain home, usual work, school, shop

locations to aid in GPS interpretation• One year “average conditions” data

collection period• Follow on prompted recall survey

Sample

• Recruited 5,564 households• 4,238 recruited households in the 8

County area received GPS units (due to GPS unit losses discussed later)

• Obtained 2,583 complete GPS surveys (not including “no travel” households (61%)

• All households were asked to complete a 1 day Internet Prompted Recall Survey obtaining 601 completes

Survey Complete Definition• All members in a household over 12 years

old (given a GPS unit), completing 1 concurrent day of full GPS recording.

• If a household member did not travel on a day when the other(s) did fully record, it counts as a complete.

• GPS HH completes include households where 4+ persons were assigned a GPS unit and a single household member failed to record complete travel on a concurrent day.

Thoughts on Low Completion Rate• GPS doesn’t lie or forget• Apparently higher recruitment to

complete data completion rates in diary surveys masks incomplete results which result in low trip rates

Sample Frame

• Address-based sample – Allows for oversampling hard to reach households areas such as students and low-income

• Matching addresses to phone numbers (55%) for phone recruiting

• Households with matched phone numbers receive a call within 2 weeks

• Households without a match receive an advance letter and a request to call in for a recruitment interview or complete online

Address-Based Phone Matched vs. Non-Matched

19% of recruits from the matched sample completed the recruitment on-line.

Only 1 phone number (0%) was obtained from the unmatched sample via a return postcard/reply. Internet proved to be the only viable means of obtaining recruits from households without land-based phones.

Completion rates for matched and unmatched sample were equivalent – once recruited.

Unmatched HH’s are 45% of the population but contributed 10% of the final sample indicating the difficulty in achieving contact

Demographics of Internet Responders

Phone Recruits Matched Internet Recruits

Un-Matched Internet Recruits

Contact Person 18-34 Years Old

22% 17% 58%

• Young households are typically under-represented in traditional Household Travel Surveys

• Internet Recruit was able to capture some of these households

• As expected, there are also a higher number of student households in this group.

Survey Time Frame

• Due to the cost of the GPS devices, the survey was be conducted over 1 year to allow more device cycling.

• Implies we obtained “average” vs. “typical” conditions, hence:– Not concerned so much with the

precise days surveyed– More concerned that sample be

maintained consistently month to month

Unit Deployment

100

300

500

700

900

1100

100

300

500

700

900

1100

Deployed Recruited

Deployed 692 938 1021 853 874 743 499 786 667 464 546 360 80

Recruited 463 945 1006 880 798 717 704 726 735 492 484 439 134

A-09 S-09 O-09 N-09 D-09 J-10 F-10 M-10 A-10 M-10 J-10 J-10 A-10

Recruitment Survey

• The recruitment survey collects household demographics for sample control and…– Work/school status – Rostering/Age information to

determine number of GPS devices/Child Diaries

– Home address

Survey Materials

• The recruited households received:– GPS devices (People 13+)– Child diaries (Children under 13)– Individual survey forms:

work/school address, no travel days– Household/Vehicle survey form: 2

most frequented grocery stores, odometer readings

Survey Materials

GPS Device Vs. Diary

• Every member of the household aged 13 and over received a GPS device

• Children 12 and under had a child’s diary which avoided detailed location questions– Place– Mode– Time– Traveled with another

Household Member

Child Diary

3 Day Survey

• This allows for better imputation of destination purposes.

• Low additional respondent burden• Better chance to get a completed

day (though this can introduce a self-selection bias)

• Can use additional travel days in disaggregate model estimation

3 Day Survey

• Most HH have 3 days of travel (2.72 days average), little variance by HH size

GPS Logistics

• GPS units returned by:– Depositing in either Fed Ex or US

Postal drop boxes– Calling the project 1-800 number to

arrange a Fed EX or personal courier pick-up

– Follow up phone calls and Internet reminders to arrange courier pick-ups as necessary

Return of GPS Units

• 2,583 households completed the GPS study, for a 60.3% response rate. However, an additional 1,326 recruited household did not receive GPS units, resulting in an overall lower than targeted sample (target equaled 3,000 households)

• Discrepancy points to a need for tighter coordination of recruitment survey conducted by call center and GPS deployment team’s unit availablity.

• By study’s end, 565 of the 833 units deployed were not returned (68%).

• 256 units lost (45%) were assigned to 4+ person households

Deployed / Lost

Unit Recycling

• # times ranged from 1 – 28• Average was 10 times• 7 were returned damaged

Who Lost Units

• Low Income• HH with children

Battery Problems

• Pilot Survey demonstrated battery problems in 18% (22 out of 119 HH called hotline with problems) of HH’s despite unit supposedly having battery life sufficient for 3 day study period

• Despite desire to minimize respondent burden, solution was to include chargers and charging instructions with package

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GPS Data Processing and Imputation

• Issues with GPS survey data that must be resolved:– Lack of purpose/mode/occupancy– GPS signal loss– GPS cold start issues– Misidentification of trip ends based

on dwell time

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GPS Data Imputation and Verification Processing Methodology

• Trip Ends - Uses a set of rules that include movement of the GPS for 2 minutes or more-or lack of movement, or a significant change in speed, extensive manual review required as well

Mode is imputed using the 85th percentile highest speed, acceleration and deceleration, and matching to the street networks and bus/train networks in a GIS.

• Purpose: Uses the frequency and duration of visits, and the match to one of the

collected addresses (home, workplace, school, frequent shops), where available.

• Occupancy: Rule-based procedure for occupancy by family members by matching trips from different family members by time, location, and mode.

Prompted Recall Survey

• 601 households completed a 1-day prompted recall survey to provide information to aid this process.

• One day of a household’s travel appeared online.– Determined by selecting a

household’s complete travel day

Prompted Recall Survey

• The respondent is then asked to verify:– Destinations– Trip Mode– Whether other family members

were on the same trip– Can add/delete stops

Data Imputation

• Trip Purpose– Frequency and duration of visits– Matched address (work, school, grocery)– Parcel data

• Occupancy– Trips by Time, Location and Mode

• Mode– Accel/decel rates, bus routes, stop pattern

and school end for school bus– Bike/auto difficult to distinguish

Imputation Methods

• Mode 59% PR match rate– 15% missed due to poor bus route data– 12% difference due to bad PR response

• Purpose 53% PR match rate– 28% inferred as closely as possible

without PR survey (PR survey gives more detailed categories)

– 9% difference due to bad PR response

Survey Representativeness• Address based sample allowed more

careful control and over-sampling in university and transit access areas

• Where problems were diagnosed the following actions were taken:– Adjust recruitment targets by area– Targeted Non-response refusal

conversion process– Targeted incentives of $15-20 (only had

funds for low income & 0 vehicle HH’s)

Survey Representativeness• Control Strata include:

– Household Size– Workers– Vehicle Availability– Lifecycle (university student, with

children, without children, retired)– Income Quartile– Transit Accessibility

Representativeness bySampling Areas

Recruit Received Recruit Received Frequency PercentTransit 1041 812 18.7% 19.2% 359 15.0%University 571 446 10.3% 10.5% 268 11.2%Other 3952 2980 71.0% 70.3% 1764 73.8%TOTAL 5564 4238 100.0% 100.0% 2391 100.0%

Recruit Complete

Percent Percent PercentTransit 10.39% 11.24% 3.77%University 5.17% 22.52% -11.31%Other 84.44% 66.24% 7.53%TOTAL 100.00% 100.00%

% Difference Completes/

TargetSampling Target W/ OversampleSampling Plan

• University proved hard to get even when targeted

Representativeness byHH Size/Workers

• Basically good, but 1 person and 0 worker less likely to complete prompted recall survey

Representativeness byIncome/Vehicles

• Low income/0 vehicle, while recruited tended to provide poor data and not complete the prompted recall survey

Representativeness byLife Cycle

• Successful in reducing over-representation of retiree’s but they tended to not complete the prompted recall survey

Results-Trips

• 2536 Households Provided Complete Data• 4548 GPS Respondents• 12362 Person-Days of GPS Data

• 5.72 Trips/Person Age 13+/Day– 3.9 Trips/Day 1995 Cincinnati HIS

• 10.24 Trips/Household Age 13+/Day – 9.8 Trips/Day 1995 Cincinnati HIS

• Child diary data yet to be added, this will increase trip rates

Results-Trip Length

• Average Trip Length– 6.88 miles– 13 minutes 18 seconds

• Each person travels per day– 39.28 miles– 1 hour 16 minutes

• Each household travels per day– 105.09 miles– 6 hours 10 minutes

Results-Mode

• Initial GPS inference classified too many vehicles in congestion as buses and bikes

Results-Purpose

• Initial GPS inference issues:– Search radius for geocoded work location may be

too small, also people often work at locations other than usual

– Pick Up/Drop Off often too short to identify from GPS trace

– Spurious mode changes due to entering congestion

Benefits of GPS

• This study’s focus is on ability of GPS to match traditional survey results

• Somewhat silent on the benefits:– Measured, accurate trip rates– Good arrival/departure time data– Good travel time data– Routing data

Lessons Learned

• GPS unit attrition is high, ramping up/ramping down the survey effort with occasional unit replacement is necessary to maintain a constant sample rate by month

• Need 1000 GPS units to achieve 3000 complete 1 day travel surveys in a year

• Higher incompletion rate for recruited households due to nature of GPS surveys being measured rather than reported, but need to plan for this when planning recruitment numbers

Lessons Learned

• Additional work is needed on imputing secondary trip characteristics

• Multiple days of travel are obtained with little extra respondent burden, this data can be used for estimating daily disaggregate models and for providing day to day information for new model forms

Lessons Learned

• Better coordination between recruitment and GPS unit availability is needed

• Incentivize each step of the process (recruit/GPS/PR) rather than one incentive payment

• Certain types of recruited households less able to complete the technical tasks necessary to complete a GPS survey

Lessons Learned

• ODOT will only use this method in future

• May move some demographic/usual location questions to recruitment to shrink survey package size

• May try simplified diary (like child survey) for all HH members in lieu of prompted recall

Contacts

• Greg Giaimo – ODOT – 614-752-5738greg.giaimo@dot.state.oh.us

• Rebekah Anderson – ODOT – 614-752-5735rebekah.anderson@dot.state.oh.us

• Andrew Rohne – OKI – 513-621-6300arohne@oki.org

• Laurie Wargelin – Abt SRBI – 248-348-5190l.wargelin@srbi.com

• Peter Stopher – PlanTranspeter@stophers.net.au