household travel surveys lessons / issues / plans
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Household Travel Surveys Lessons / Issues / Plans . Presentation to the AMPO Travel Modeling Working Group October 24, 2006 Ron Milone MWCOG/NCRTPB Washington, DC. Dynamics shaping the planning process in the Washington, DC region. Sprawling development continues - PowerPoint PPT PresentationTRANSCRIPT
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Household Travel Surveys Lessons / Issues / Plans
Presentation
to the AMPO Travel Modeling Working Group
October 24, 2006
Ron MiloneMWCOG/NCRTPB
Washington, DC
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Dynamics shaping the planning process in the Washington, DC region
• Sprawling development continues– The Washington region is second to New York for the percentage of
workers with "extreme commutes” – Home buyers trade off lower housing prices with longer commutes
• Public money for new construction limited– Local share of funding for transportation costs is increasing
• Virginia is considering public-private partnership for building HOT lanes– Managed highway pricing is planned in Maryland
• The number of immigrant residents/workers has increased, helping to counter the number of baby boomers who are retiring
• Extensions to the completed 103-mile Metrorail system now planned. Increasing transit service and ‘Smart Growth’ are cited by many as congestion remedies
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Why are HH surveys conducted?
• Sample measurements: Household travel surveys are intended to identify localized relationships between travel ‘desires’ and land use, system, policy factors that can be forecasted
• Household travel surveys are not designed to count demographic and travel quantities with a high level of geographic precision.
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The HH survey is one component of a regional inventory that informs modelsInventory of the transport system (past / present / future)
Networks
Inventory of activity pattern (past / present / future)
Land Use
Inventory of system use Highway Counts / Transit Counts (OB surveys)
Inventory of residential demand:HH Travel SurveyHH Travel Survey
Inventory of non-resident travel marketsExternal, Truck, Taxi, Workplace, Airport, etc., Surveys
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What are the key products?(with respect to modeling)
Household File Person File Vehicle File Trip File
Size Age Model Origin Purpose
Income Gender Make Dest. Purpose
Vehicles Emp. Status Type Primary Mode
Workers No. of Jobs Year Sub modes
Dwelling Type Driver Status Fuel Passengers
Owner/Renter Worker type Miles Driven Travel Costs (Park/Fare/Toll)
Bicycles Starts Begin Time
Stops End Time
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Needs of conventional modelers
• Trip Rates, by purpose– Production-end rates – Attraction-end rates
• Trip Length Frequencies, by purpose, by O-D pattern
• Modal Share, by purpose, by O-D pattern• Time-of-Day profile by purpose, by mode,
by directionality
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How low can the surveys go, with confidence?
• Regional level - Yes• Regional Level,
by socio-economic stata -Yes• State Level - Probably• County Level – Maybe• By Sector – Maybe/No • By TAZ or finer- No
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Organizational Issues• A HH survey is a substantial, yet infrequent
undertaking; it can be a ‘shock-wave’ to the work program
• Identifying funding sources is a challenge • The knowledge/skills requirements are unique• Administration of survey is increasingly being out-
sourced – How well do surveyors know the region?• Interagency cooperation and coordination required• Interfacing with the general public is always a delicate
matter
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Past HH Travel Surveys in Washington, DC
• 1968 Home Interview Survey – Face-to- Face Interviews with an ‘army’ of interviewers– 26,000 Households sampled (1 in 20, 1 in 33) – 6 Jurisdictions
• 1987/88 Home Interview Survey – Mail / CATI combination (conducted by MPO)– 8,000 Households sampled (1 in 166) – 8 Jurisdictions
• 1994 Spring/Fall Home Interview Survey– Mail / CATI combination (conducted by consultant)– 4,800 Households sampled (1 in 300) – 13 jurisdictions
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Trends Impacting Surveys • Study area is steadily expanding• Cost of data collection is increasing • Sample sizes are steadily decreasing• Ability to collect data by telephone- increasingly difficult
– Cell phone market share increasing – Telephone ‘land line’ market share decreasing – Telephone screening technology improving
• Modeling requirements/complexity is increasing• Policy questions being asked are ahead of tools• Surveys, in general, are saturating the area • Privacy, confidentiality, and identity theft are growing
concerns
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Essential HH Survey Goals
• Appropriate capture and selection of HHs– representation of socio-economic markets – adequate capture of the ‘minority’ modes
• Minimizing non-response• Minimizing under-reporting of travel• Maximizing Location Accuracy• Data that’s valid and ‘clean’
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Survey Implementation Process• Planning• Survey Design
– Assemble background data: Census STF1-4, CTPP, PUMS– Formulate survey approach, sampling procedures, – Design instrument(s)
• Field Implementation– Pretesting, data collection
• Data Preparation– Coding, cleaning, compiling
• Data Analysis– Analyzing, Reporting, Using
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Non-Response• The main concern: bias in the data• Response rate for 1994 HTS: 38%
– 50 % Recruitment: unusable telephone numbers: fax machines, nonresident units, unoccupied units, etc.
– 76% Retrieval: refusals, no telephone contact made, language problems, <50% HH members responded.
• Who are non-responders?– Low income groups– Telephone ‘screeners’– People who just are not home: high mobility groups! – People who are home, but do not travel – They don’t feel
‘applicable’ to a travel survey• Item non-response: income, age
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How to Deal with Non-Response
• HH non-reponse:– Ignore it (if sample size is sufficient without non-
respondents)– Assumption: Non-respondents are similar to
respondents (!) • Item non-response:
– Impute values (Hot Decking) – Is a reasonable fix if the non-respondent population is
different from respondent population– ‘Nearest-neighbor’ approach – uses like socio-
economic and personal characteristics to ‘fill in’ item non-response and to adjust trip weights
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Data Cleaninglogical, rational, and reasonable models require like data
Question: How much time/effort is needed to clean data?
Answer: How much time do you have?• 1994 HTS: 1.5 -2.0 person-years• What’s involved (cleaning HH/Trip/Person files):
– one-way Frequencies – range/distribution– Cross-tabulations: logical /consistent/coherent– Trip-chaining: logical timing & sequence of trip
itinerary– Address Matching: the big one – Validating against other data sources
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Plans: 2007 Household Travel Survey
• Project Director: Robert Griffiths, Technical Services Director, COG/TPB
• Travel and Activity Survey – 10,000 HH• In-Vehicle GPS add–on – 250 households • Planned Survey Design
– Address – based sample from USPS carrier route lists, as opposed to Telephone/Random-Digit-Dial(RDD)-based
• Circumvents telephone-related issues cited above• Better control of uniform geographic capture, that is not ensured
using RDD method• Differential sampling rates by area type• All households with deliverable mail address in sample, except
those on ‘do-not-mail’ list (3%)
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Sampling
• 22 jurisdictions (modeled area)• Frame – mail carrier routes• Segmentation:
– ‘Inner Ring‘ Jurisdictions • High density/mixed use areas (over-sampled to
ensure capture of ‘minority’ modes (transit, ride share, walk, bicycle)
• Low Density areas– ‘Outer Ring’ Jurisdictions
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Data Collection
• Initial mailing– Minimal household, person, vehicle
characteristics asked• Follow-up telephone recruitment• Telephone/Internet travel-activity data
retrieval (respondent’s option) • Real-time geocoding used
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Pilot Test (in progress)
• Assessing coverage of proposed mail route sample as opposed to RDD sample
• Assessing the effect of financial incentives• Assessing interview method response
rates • Testing conversion methods for non-
respondents / non-response follow-up survey
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Pilot Test … continued
• Vehicle GPS add-on survey will be tested– will be used to assess under-reporting or over-
reporting of trip making.• The assignment of “observed’ vehicle trips from the survey
has historically resulted in an under-estimation of VMT.• Short non-work trips are typically under-reported, and so trip
rates are usually increased to make up for the difference.• Is this the right thing to do? Other possible sources of error:
– Commercial Vehicle trips not well reflected– External trips not well reflected– Error in Observed VMT
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Schedule
• Pilot Test Evaluation: Now• Main Survey: November 2006 – January
2008– Survey will be collected throughout the 13
month period.
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Conclusions on HH Surveys
• Vital for formulating variable relationships in the work
• But one piece of the data puzzle• Typically lag behind the questions being
asked • Subject to problems relating to non-
response, under-reporting, geographic coverage, modal coverage
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Conclusions …
• Modelers should be involved at the ‘front-end’ of survey design & development– Is the information obtained appropriate?– Are questions asked in the best way? – What are the limitations of the survey?
• Sources of error abound, data is imperfect• Technology must continually be exploited
to address issues
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Read more about the Washington Household Travel Survey
www.mwcog.org/hts