Methods for conducting a large scale gps only survey of households
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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.

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

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Methods for conducting a large scale gps only survey of households

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

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

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

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

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

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

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

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

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

Demographics of Internet Responders

  • 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

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

Unit Deployment


Recruitment survey

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

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 materials1

Survey Materials


Gps device vs diary

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 anotherHousehold Member


Child diary

Child Diary


3 day survey

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 survey1

3 Day Survey

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


Gps logistics

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

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

Deployed / Lost


Unit recycling

Unit Recycling

# times ranged from 1 – 28

Average was 10 times

7 were returned damaged


Who lost units

Who Lost Units

  • Low Income

  • HH with children


Battery problems

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


Gps data processing and imputation

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


Gps data imputation and verification processing methodology

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

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 survey1

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

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

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

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 representativeness1

Survey Representativeness

  • Control Strata include:

    • Household Size

    • Workers

    • Vehicle Availability

    • Lifecycle (university student, with children, without children, retired)

    • Income Quartile

    • Transit Accessibility


Representativeness by sampling areas

Representativeness bySampling Areas

  • University proved hard to get even when targeted


Representativeness by hh size workers

Representativeness byHH Size/Workers

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


Representativeness by income vehicles

Representativeness byIncome/Vehicles

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


Representativeness by life cycle

Representativeness byLife Cycle

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


Results trips

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

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

Results-Mode

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


Results purpose

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

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

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 learned1

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 learned2

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 learned3

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

Contacts

  • Greg Giaimo – ODOT – 614-752-5738

    [email protected]

  • Rebekah Anderson – ODOT – 614-752-5735

    [email protected]

  • Andrew Rohne – OKI – 513-621-6300

    [email protected]

  • Laurie Wargelin – Abt SRBI – 248-348-5190

    [email protected]

  • Peter Stopher – PlanTrans

    [email protected]


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