Transportation Data Collection through Mobile Phones – Transforming Transit Data Surveys

A Memo to the Federal Highway Administration and National Household Travel Survey

Executive Summary

The use of mobile-based travel surveys has significantly reduced survey implementation costs and the burden on users compared with traditional phone and paper diaries, and is revolutionizing transportation surveying methodologies.  In order to provide consistent, comprehensive and user-friendly data regarding transportation patterns, a mobile-based application can be employed which collects information passively, requires minimal user interaction, and decreases surveying and analysis costs.  It is recommended that the Federal Highway Administration (FHWA) transition the National Household Travel Survey (NHTS) to be administered significantly through mobile-based responses which will help to lower costs, increase participation and frequency, and improve data availability and transparency.


Detailed travel data is essential in establishing an understanding of how people move within and between cities and regions.  Current survey methods and data gathering techniques are inefficient and fail to leverage the capacity of improved telecommunications infrastructure.  The use of GPS enables users to receive and transmit real-time spatial data, surpassing the ability of phone or paper-based surveys in capturing travel patterns, options, and preferences.  Most critically, mobile-based surveying platforms greatly reduce the man-hours and input required for the travel survey administration, and thus significantly reducing costs associated with data collection and interpretation.

Conventional travel survey methodologies require burdensome collection of detailed activity travel information which can be inaccurate and/or incomplete based on the tools and processes that are used. GPS-based surveys have been widely implemented beginning with a proof-of-concept study conducted for the U.S. Federal Highway Administration in Lexington, Kentucky in 1996 (Travel Forecasting Resource, 2014).  Since this time, GPS-based household travel surveys have incorporated the data into traditional surveying models which still require significant user input and participation in either paper, phone, or web-based recall surveys.

The FHWA implements the NHTS every 5-7 years, administering surveys to a base sample of over 25,000 people.  The survey put out for a bid and contracted by data collection and analysis firms – most recently and frequently by Westat (2001, 2009, 2015).  The survey is conducted through mail, internet, GPS and telephone collection modes, with incentives to increase respondent participation.  The data collection takes approximately a year to conduct, and several months for the analysis and documentation.  Similarly, states can opt-in to more intensive surveying for their region at additional cost.  The NHTS provides general national level information and local/regional information to states which opt-in.  Alternatively states may conduct independent surveying.  In 2012, MassDOT released the Massachusetts Travel Survey study, a comprehensive review of demographic and travel behavior characteristics of MA citizens (MassDOT, 2012).  The project included traditional household surveys[1] in conjunction with an independent GPS tracking measure, contracted to the independent research firm NuStats, Inc.  The firm spent thousands of hours calling potential participants and conducting registration and pre-survey questionnaires.

These surveys, while comprehensive in nature, cost taxpayers millions of dollars for what can now be done more efficiently and effectively through mobile phones.  NuStats has evolved their services to incorporate this advantage of mobile data collection through their NuTripX application, and greater competition in addition to open access programming should significantly drive down costs and barriers to transportation surveying.

Although smartphone-based transportation surveys are in the primary stages of development and implementation, mobile devices enable trip data to be collected both passively and accurately, leveraging the capacity of GPS with travel-detection algorithms to automatically map and identify trip information (Cynthia Chen, 2010).  The relatively simple user interface and experience which is provided by a GPS-enabled smartphone allows for all necessary travel data to be collected passively and/or provided by a prompted recall at the end of the trip.  The process for this methodology both reduces user input and improves the accuracy of trip information such as purpose, locations, etc.

To increase the accuracy of transportation data and user travel preferences, mobile devices can be employed to evaluate travel based on speed, locations, time of day, distance, and weather.  The raw data is processed and interpreted to collect the mode of travel, route, preferences, and alternatives.  Minimal user input is required, enabling the user to provide only relevant and uncaptured data such as alternative choices or preferences, needs, etc.  The most significant benefit of mobile-based transportation surveys, however, is the elimination of costs associated with traditional surveying methods which require phone and paper-based interviews and data collection sessions.   While research has indicated that recall surveys which incorporate some interaction with the surveyor and participant have the highest completion rates (by phone or mail), these interactions significant increase the implementation cost and time burden of both parties as compared with web or phone-based recall surveys.

Mobile Data Collection Instruments and Services

MIT’s Future Mobility Survey

“The Future Mobility Survey (FMS) is a smartphone-based prompted-recall travel survey that aims to support data collection initiatives for transport modelling purposes” (Cottrill, 2013).  The program, available for Android and iOS users, includes an online travel diary interface and data analysis algorithms for processing the data into locations and travel modes.

In the FMS, user information is collected in four stages: registration, pre-diary, activity diary, and exit survey.  In the registration phase, the user provides basic household information including age, gender, education, household members, and contact information.  In the pre-diary survey, participants provide more detailed household information including socio-economic data, vehicle ownership and mode preferences.  In the activity diary, participants must validate the activity mode information that is extrapolated by the FMS phone application.  And finally in the exit survey users provide feedback on the survey platform and final household and preference information.  For the end user, the surveys can all be done by a mobile device with web access and the FMS application.

The FMS developers have continued to refine the algorithms and background intelligence of the platform to better interpret and process the users’ activity locations and modes of travel between them, differentiating between different modes, user preferences and habits.  The combination of automated intelligence and prediction software with user verification steps provides accurate and detailed data with minimal user input.  FMS’s phone-based platform and provides pragmatic insights into the development of similar platforms and approaches for travel/activity surveys, and is a model for future surveying and travel data collection.


First demonstrated in 2012, NuTripX is a web application product for communicating and interacting with survey respondents and achieving high response rates and data (NuStats LLC, 2014).  The platform is a mapping tool designed for web-based data collection and offers real-time geocoding, mapping features, a routing function, data verification and validation.  NuTripX functions on mobile devices and enables real-time validation of accuracy and robustness of records.

Federal Highway Administration’s Role

The FHWA conducts the National Household Travel Survey (NHTS) and additional attitudinal-based surveys which determine activity and behavior-based data about transportation at the national, local and regional levels.  Initiatives by the FHWA to evaluate and predict the behaviors of citizens and visitors is critical to supporting effective and sustainable travel opportunities.  In a rapidly evolving transportation landscape wherein preferences are adopting to new markets such as ride-share and bike-share services, demands for physical infrastructure and transit policies are shifting.  The NHTS, currently conducted every 5-7 years at a cost of several million dollars, provides results that are within a short time outdated by disruptions to the travel services sector (new modes and business models), infrastructure changes (construction projects), and policy developments (changes to gas taxes, transit expenses).  A mobile-based transportation data collection system can provide efficient long-term travel data at lower cost and user burden than existing survey methodologies.

The FHWA should require the use of mobile-based transportation surveys in future NHTS contracts, either by licensing the software provided by NuStats, or working in collaboration with partners such as MIT’s Intelligent Transportation Systems Lab to establish a long-term mobile-based application.  In the initial development of a mobile-based instrument, both the traditional methodologies (web, phone and paper based surveys) and a mobile-based system should be employed and their results compared to evaluate the relative effectiveness.  Potential resistance to a mobile-based platform can be overcome through a series of comparative studies during the application’s development and initial implementation.


Works Cited

Board, T. R. (2011). Use and Deployment of Mobile Device Technology for Real-Time Transit Information. Washington, D.C.: Transportation Research Board.

Boyle, R. (2011, August 3). Microwave Sensors Auto-Detect Bikes At Intersections, To Trigger Traffic Signals and Protect Cyclists. Retrieved from Popular Science:

Chicago Transit Authority. (2014). Open Data from CTA. Retrieved from Chicago Transit Authority:

Cottrill, C. D. (2013). The Future Mobility Survey: Experiences in developing a smartphone-based travel survey in Singapore. Singapore: Future Urban Mobility Lab.

Cynthia Chen, H. G. (2010). Evaluating the feasibility of a passive travel survey collection in a complex urban environment: Lessons learned from the New York City case study. Transportation Research, 830-840.

European Commission. (2014). Smart Mobility Challenge. Retrieved from Mobility and Transport:

Kaufman, S. M. (2012). Getting Started with Open Data: A Guide for Transportation Agencies. Robert F. Wagner Graduate School of Public Service, New York University.

MassDOT. (2012). Massachusetts Travel Survey. Austin: NuStats.

NHTS. (2014). Our Nation’s Travel. Retrieved from National Household Travel Survey:

NuStats LLC. (2014). NuTripX. Retrieved from Web & Mobile Applications:

Sivaramnakrishnan Srinivasan, S. B. (2009). Methodology for Converting GPS Navigational Streams to the Travel-Diary Data Format. University of Florida, USA: .

Transportation, U. D. (2013, December). Data Inventory. Retrieved from US DOT:

Travel Forecasting Resource. (2014). GPS-enabled surveys. Retrieved from Travel Forecasting Resource:

Tyburski, R. (1989). A Review of Roadway Sensor Technology for Monitoring Vehicle Traffic. ITE Journal, 27-29.



One Response to Transportation Data Collection through Mobile Phones – Transforming Transit Data Surveys

  1. Hosting says:

    While people in more developed cities might be comfortable with data on how they travel being used to improve transport systems, passengers in emerging cities are also starting to benefit from the collection and application of digital information.

Leave a Reply

Your email address will not be published. Required fields are marked *