Urban Mobility Behaviors & Preferences Test Bed

Project Managers: 

Moshe E. Ben-Akiva, Jing Ding-Mastera


Ford-MIT Alliance


Massachusetts Institute of Technology: Moshe Ben-Akiva, Jing Ding-Mastera, Bilge Atasoy, Mazen Salah Danaf, Xiang Song

Singapore-MIT Alliance for Research and Technology (Singapore): Fang Zhao, Christina Lui


Start Date: 

October 3, 2013

Research Highlights: 

  • Design of an SP survey – Define the objective of the context-specific stated preference survey, the interaction process with users, the events to trigger the survey questions, and the survey questions.
  • Software development – Develop a stand-alone plug-and-play event-based preference experiment environment that prompts users with customized preference questions based on their mobility behavior.
  • Pilot survey – Proof of concept for the proposed methodology through a small-scale pilot survey in Boston.
  • Data analysis – Develop joint estimation methods using the combined revealed preference and stated preference data. Analyze the collected data to demonstrate the effectiveness of the proposed methodology.


The objective of this project is to develop a methodology to study consumer preferences related to mobility solutions based on mobility behavior observed through GPS-enabled devices such as smart phones, GPS loggers, etc., followed by a survey. The scope of the project includes implementation of the methodology, software development, proof of concept and analysis.

GPS-enabled devices are gaining popularity as tools to collect individual travel behavior data in travel surveys. We propose to develop a customized adaptive stated preference survey system that extends the capability of these GPS-enabled travel surveys.  An event-based preference experiment environment will be setup that allows hypothetical questions to be asked based on observed user travel/activity behavior.

Each mobility market/urban center is unique in terms of its infrastructure, demographics and mobility behavior. To customize solutions, it is necessary to understand the aforementioned elements. This methodology can be a powerful and cost-effective tool to study the future mobility market and effectiveness of solutions.


Stated preference (SP) surveys are widely used in behavior research and practice to identify behavioral responses to choice situations, which are not revealed in the market. GPS-enabled devices, such as smart phones and GPS loggers, are gaining popularity as data collection tools in individual travel surveys. They improve the quantity and quality of data collected and overcome many limitations of conventional surveys. The unprecedented amount of detailed data provides us with an opportunity to perform individualized, context specific stated preference surveys.

Using high-resolution data collected through GPS-enabled devices, we will develop a methodology to study consumer preferences related to mobility solutions through individualized preference experiments. Event-based triggers on the users’ travel and activity behavior will be used to present customized hypothetical questions to them to assess their preference and choices on various attributes. We plan to develop a plug-and-play software that can interface with GPS-based travel survey systems to conduct this stated preference survey. The software can be used for various purposes, e.g., evaluating user reaction to new technologies, products, services etc.

We envisage performing a proof-of-concept for this new technology to collect both stated preference as well as revealed preference information on the same set of users. We plan to develop joint estimation methods using the combined data. The rich and detailed data collected by the combined system can increase the quality of the estimates. 

We will test this new methodology with a smart phone and web-based travel survey system called the Future Mobility Survey (FMS), which has been developed in the Singapore-MIT Alliance for Research and Technology (SMART). The FMS app, available in Android and iOS app stores, is a non-intrusive tool to collect user’s location and accelerometer data. The raw data collected is analyzed in the back end to infer user’s stops, modes, and activities. The processed data is presented in the web-based activity diary for users to validate or modify. In the pilot, FMS will be used to define the context used in our SP survey.


Zhao, Fang, Francisco Camara Pereira, Youngsung Kim, Yafei Han, Christopher Zegras, Moshe Ben-Akiva. "Exploratory Analysis of a Smartphone-Based Travel Survey in Singapore." Transportation Research Record 94th Annual Meeting (January 2015).

This project is related to FMS.  To see more information about FMS, click here FMS.