Capturing the Relationship between Motility, Mobility and Well-Being Using Smart Phones

Project Managers: 

Fang Zhao (fang.zhao@smart.mit.edu)
Maya Abou-Zeid (ma202@aub.edu.lb)

Sponsor: 

U.S Department of Transportation University Transportation Center

Team: 

Moshe Ben-Akiva, Maya Abou-Zeid, Sebastian Raveau, Muhammad Adnan, Milan Lovric, Ajinkya Ranjeet Ghorpade, Kalan Vishwanath Nawarathne, Jorge Gomes de Oliveira Santos, Aidan Michael O’Sullivan, Weiliang William Ko,  Zhengquan Qin.

Start Date: 

August 2013

Research Highlights: 

  1. To develop novel metrics of transportation related well-being, accessibility, and mobility from the recorded activity and travel space of the travelers and their self-reported measures of well-being (retrospective and real-time).
  2. To collect travel and well-being data using GPS enabled smartphones in an efficient and non-intrusive manner with minimum contribution from the participants.
  3. To influence travelers to make conscious travel decisions and thereby to encourage them to shift towards more sustainable transport behavior.

Abstract: 

Understanding and incorporating measures of travel well-being in transportation research is critical for the design and evaluation of policies aiming at enhancing well-being.  Individual’s well-being is derived not only from what a person actually does or is, but also from their capabilities (i.e. feasible functioning forms that they could have achieved or could have been).  In this study we conduct surveys and measure mobility patterns and well-being using smartphone technology (enabled with GPS, GSM, Wi-Fi and accelerometer), which overcome the limitations of conventional surveys methods to measure well-being, in order to develop novel measures of well-being based on a traveler’s mobility potentials (i.e. from motility) as well as to compare real-time and retrospective well-being measures.

Description: 

Understanding and incorporating measures of travel well-being in transportation research is critical for the design and evaluation of policies aimed at enhancing well-being. In recent years, several efforts have been made to quantify travelers’ subjective well-being using travelers’ self-reported state of happiness while participating in various activities or travel patterns. But, in line with Amartya Sen’s capabilities approach, it can be argued that the achieved mobility of an individual is not a sufficient measure to capture the well-being of human beings but also the potential of their mobility contributes significantly to their travel well-being. This potential of mobility can be called “motility”.

So far, a very limited number of studies have been conducted specifically in the field of transportation to measure the well-being of travelers derived from their motility - primarily because of the limitations of conventional survey methods to collect uninterrupted and comprehensive information about the activities and travel spaces of people. This research aims at conducting surveys and measuring mobility patterns using smartphone technology - enabled with GPS, GSM, Wi-Fi and accelerometer - which will overcome the limitations of conventional surveys. The information collected in this procedure can be augmented with web-based prompted recall survey where the participants will be able to validate their activity and travel information collected automatically via smart phones.

In addition to quantifying well-being through the concept of motility, this research will analyze other conceptual approaches to the measurement of well-being, including retrospective measures of well-being by activity type (through the prompted recall survey) and real-time measures through brief surveys administered through the smartphone while participants conduct their daily activities.

In addition to the measurement of travel, activities, and well-being, the research aims to influence travelers’ mobility patterns and well-being by providing them information about their aggregate travel patterns and how they compare to those of others. The information may include statistics about time and money spent on travel, emissions, well-being, etc. This process will allow the travelers to monitor and compare their travel choices and travel well-being with those of the other members in their peer group and may influence them to modify their current choices to enhance their well-being and to move towards sustainable transport behavior.

Though data collection using GPS technology and smartphones is increasingly getting popular, it is still quite challenging for the researchers to keep the participants motivated since it requires a relatively long term commitment of the travelers to carry the GPS enabled smartphone habitually and validate the collected information from time to time to have confidence in the quality of the data. The important aspect of the research would be to make the data collection procedure as non-intrusive as possible so as to minimize the user burden. One important research challenge lies in the correct identification of the travel modes and purposes without requiring frequent validation by the travelers.

Another challenging aspect of the research will be to monitor any anticipated change in the participant’s travel behavior like change of mode, reduction in the number of daily trips, etc., which would require following up with the survey participants beyond the primary period of data collection without affecting their habitual travel behavior.

References: 

  1. Carrion, C., Enam, A., Pattabhiraman, V., Abou-Zeid, M. and Ben-Akiva, M. (2015). Activity Pattern Models with Well-Being Indicators. 94th Annual Meeting of the Transportation Research Board, Washington, D.C., U.S.A. January  [forthcoming in Transportation Research Record Journal]
  2. Abou-Zeid, M. and Ben-Akiva, M. (2012). Well-being and Activity-Based Models, Transportation, Vol. 39, No. 6, pp. 1189-1207.
  3. Abou-Zeid, M., Witter, R., Bierlaire, M., Kaufmann, V., and Ben-Akiva, M. (2012). Happiness and travel mode switching: findings from a Swiss public transportation experiment. Transport Policy, 19, pp. 93-104.
  4. Pereira, F. C., Cottrill, C., Zegras, C., Abou-Zeid, M., Xiang, Y., Dias, I., Santos, J., Ben-Akiva, M. and Silva., J. A. (2011) Integrated Transportation Activity-Travel Smartphone Survey. 9th International Conference on Transport Survey Methods, Termas de Puyehue, Chile. November 2011.
  5. Abou-Zeid, M., Ben-Akiva, M., and Bierlaire, M. (2008). Happiness and travel behavior modification. 2008 European Transport Conference, Noordwijkerhout, Netherlands. October 2008.
  6. Future Mobility Survey, Future Urban Mobility Group, Singapore-MIT Alliance for Research and Technology (SMART).