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Use of Multiple Forms of GPS Data for Understanding Travel Behavior


With the high costs associated with primary data collection, methods to improve the use and accessibility of data already being collected will benefit many. Global Positioning System (GPS) data are a good example of significant amounts of data that are collected and stored and may have multiple uses beyond existing estimates of speed and travel times i.e., asset management, both in real-time and for analyzing trends or changes over time. GPS data are also being collected, sometimes at significant cost, to supplement travel behavior surveys of households and goods movements. Some researchers are evaluating uses of GPS data collected for one purpose that could be re-processed for a second purpose. These opportunities present options for cost savings because the data already exist and the cost is primarily due to the processing necessary to maintain confidentiality of the raw data and support the second purpose. Benefits of increased use of existing GPS data will accrue to transportation analysts in traffic operations, long range transportation planning, air quality and climate change analysts, and energy infrastructure planners. Challenges to increased use of GPS data include processing the data for different purposes, reaching consensus on spatial data accuracy while maintaining confidentiality and combining these data with other data to infer behavioral relationships.


To supplement existing travel behavior programs with spatial travel data collected by GPS users.


There are at least three specific benefits that could be generated by using GPS data from multiple sources for understanding travel behavior including:

● Accuracy – GPS data are inherently more accurate for obtaining travel data for an individual than travel diaries completed by a person because the GPS can record every location every second while the individual is traveling. Travelers who complete diaries of their travel may forget to record a trip, may inaccurately represent a location, may record the wrong time or may record the wrong trip. As long as the GPS is operational and designed for the proper spatial and temporal resolution, the data are accurate.

● Sample Size – GPS data may provide a significantly larger sample than other data sources because the sample size depends on the number of users and can be collected every day over many years rather than for a limited sample size over a one or two day period.

● Cost – Household travel surveys can cost millions for a regional or state agency to collect enough data for a statistically accurate sample and it is this fact that limits sample size for these studies. GPS data has the potential to provide larger sample sizes at a significantly lower cost, but they will not replace all data currently being collected for household travel surveys. Some (but not all) of these missing data items may be inferred by combining GPS data with other data sources to infer missing data.

The usefulness of these GPS data to understand travel behavior needs to be explored to evaluate the degree to which inferred data is accurate, and the cost for GPS data being collected for other purposes (vendors are discussing these pricing options as they consider the market). In addition, it will be useful to consider how GPS data can support specific travel behavior choices and whether these data could support model estimation, calibration, validation or application.

Related Research:

Historically, travel behavior relationships were developed through the use of household travel surveys. In recent years, some of these have been supplemented with a GPS survey that provides a parallel data collection effort of a particular household or vehicle. On a separate track, some vendors have developed travel data from probe vehicles with GPS capabilities. In addition, other vendors are collecting and analyzing data from GPS devices sold to individuals or installed on cell phones. These types of data collection efforts are described below.

Household Travel Surveys

Household travel surveys provide potential for combined data collection benefiting multiple end users. Current efforts could be better coordinated with each other and with activities in different areas. The National Household Travel Survey (NHTS) is undertaken about every 5 years and for the past 40 years has traced national and regional travel behavior patterns on a national level. Many states and Metropolitan Planning Organizations (MPOs) have contributed funds for an add-on sample of the NHTS rather than conducting their own survey. This is a good example of the efficiencies and usefulness of coordination. In California, the statewide travel survey is being coordinated with MPO surveys so that survey design can be consistent among the surveys. Another challenge for states and MPOs conducting travel behavior surveys is sporadic funding. The American Community Survey (ACS) began using an ongoing survey methodology in 2005 and is producing single and multi-year population estimates from these data. Some states and MPOs are considering an ongoing survey, rather than a once-a-decade survey, to alleviate this funding issue.

GPS Household Travel Surveys

In recent years, the use of GPS devices has matured to the point where they can be effectively used to assist traditional surveys to assess missed trips on the part of the respondent, with multiple MPOs now having utilized this new approach. In Australia, they have been used as the sole survey device and tracked respondent travel behaviors over long periods of time as compared to the more typical travel day survey. GPS surveys can collect precise positioning of the respondent, returning coordinates, altitude, acceleration, deceleration as well as dwell time. GPS surveys when coupled with highly accurate Geographic Information System (GIS) networks for travel modeling can easily show flow activity on the network. Several agencies have recently incorporated the GPS-instrumented vehicle technique into studies on congestion pricing (in order to address both concerns with traffic management and means to pay for infrastructure improvements).

Probe Vehicle GPS Surveys

Probe vehicle surveys have similarly proliferated due to GPS technology advancements and can provide an alternate assessment of network transit times and speed calculations. System operators require real-time reporting of vehicle speeds and the presence of vehicles within the stream to resolve incidents and improve roadway performance. Companies involved in Intelligent Transportation System (ITS) work and in-vehicle navigation systems desire this same information in order to provide intelligent traffic routing, accurate travel time predictions and information to help drivers avoid traffic jams. Air quality analysts also benefit from data on temporal and seasonal variation of speeds and operating states for the different types of vehicles on the roadway.

The I-95 Corridor Coalition Vehicle Probe Survey provides one example of using personal cellular telephones to identify light-duty vehicle travel. This survey is testing cellular probe technology and validating the data streams from onboard Bluetooth devices communicating with roadside receivers. INRIX, the vendor for this project, has also produced several reports using the travel times and speeds to illustrate vehicular stream performance as well as constructed a national dataset.

Similar surveys can use GPS-enabled cell phones to collect transit time and speeds in sections and point locations for traffic engineering needs such as signalization regimes. The technology has been taken further in trucks, where devices log the GPS travel profile as well as operation data from the vehicle information system. The American Transportation Research Institute and the Federal Highway Administration have examined such data as a means for assessing speed as a performance measure. CALMAR is another firm aggregating truck GPS/data bus information.

GPS Device Data

There are a number of vendors (TomTom, AirSage, OnStar, Google, etc.) that compile GPS data from their own devices or from GPS software installed on cell phones. These data have the advantage of very large sample sizes and broad geographic and temporal coverage. The challenge is with the confidentiality aspects of the data, thus making it more difficult to merge these data with outside sources on demographics, land use, etc. There is currently an open question about the validation of these data to ensure that it is representative of the full population.

GPS device data have been used to data to develop travel time and speed estimates for corridors or regions. In some cases, these have also been used to identify origin-destination patterns for travelers. Additional uses of these data could include inferring patterns of mode choice (based on speed and route), trip-making (numbers of trips and tours), trip purpose (based on origin and destination land uses), time of day choice and route choice.


Task 1 – Review existing data collection efforts

Review existing data collection efforts from planning, operations, private and administrative sources, as well as recent advancements in passive data collection. This should include data collection for all modes (walk, bike, transit, auto) and vehicle classifications (autos, trucks). This should also include review of wherever GPS data has been utilized as part of a household travel survey, with these efforts documented. Determine the value of combining and repurposing these existing sources to meet the range of traditional and emerging needs. Identify the cost and confidentiality limitations on private sector data sources. Review the data uses of all types of GPS data collection activities. * *

Task 2 – Literature review

Research current uses of GPS data for understanding various aspects of travel behavior (trips, destinations, purposes, modes, routes, times, etc.). Identify promising studies of passive data collection for transportation planning or operational projects. Describe data sources and methods to process the data used in research.

Task 3 – Examine methods to merge GPS

traditional data sources

Examine the methods involved with integrating GPS technology and other data sources to meet the needs of the diverse planning, operation, engineering, and research stakeholders. Identify the types of inferred data that may be generated by merging datasets. Document how standards, meta-data, common data architectures, and other data management strategies have facilitated data sharing and integration. Test these methods using a sample data set and validate the results to identify whether the method is accurate.

Task 4 – Address privacy concerns

Evaluate ways to address privacy concerns from integrating GPS and diary survey data while maintaining the ability to use the data for analyses. (Note that modeling, simulation and calibration of analysis engines often require availability of data in its native form).

Task 5 – Recommendations for implementation

Recommend an approach to implementation with the following components:

● Integrate available passive data collection with established data sources. Highlight cost-effectiveness and limitations of available data sources compared with GPS household travel surveys.

● Determine how GPS and traditional survey data should be interrelated, integrated, formatted, collected and stored for planning purposes.

● Strike an appropriate balance between privacy protection and data accessibility.


This project will assess the usefulness and cost-effectiveness of using GPS data collected for other purposes to understand travel behavior. The project will result in the identification of potential GPS data sources, methods to process and/or combine these data with available data sources to extend its usefulness, proposed solutions to the balance between data privacy and accessibility, and recommendations for implementation.

Sponsoring Committee:AED20, Urban Transportation Data and Information Systems
Research Period:12 - 24 months
Source Info:Catherine T. Lawson
University at Albany
Elaine Murakami
FHWA Office of Planning

Maren Outwater
Resource Systems Group. Inc

Jonette Kreideweis
Minnesota DOT
Date Posted:10/27/2010
Date Modified:09/22/2017
Index Terms:Global Positioning System, Travel behavior, Data collection, Real time information, Accessibility, Traffic data, Travel costs, Mode choice,
Cosponsoring Committees: 
Data and Information Technology
Planning and Forecasting
Transportation (General)

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