Making data matter : the role of information design and process in applying automated data to improve transit service

As public transit agencies install new technology systems they are gaining increasing amounts of data. This data has the potential to change how they operate by generating better information for decision-making. Deriving value from this data and applying it to improve service requires changing the institutional processes that developed when agencies had little reliable information about their systems and customers. With automated systems producing large quantities of high quality data, it becomes the impetus for, rather than simply the input to, measurement. Capturing more value from automated data thus involves rethinking what agencies can know about service. This research uses the Massachusetts Bay Transportation Authority (MBTA) as a case study. It first assesses how the MBTA currently uses real-time and historical data. Based on this assessment, it redesigns and advances the agency's daily performance reports for rapid transit through a collaborative and iterative process with the Operations Control Center. These reports are then used to identify poor performance, implement pilot projects to address its causes, and evaluate the effects of these pilots. Through this case study, this research finds that service controllers' trust and interpretation of performance information determines its impact on operations. It concludes that new data will be most effective in producing service improvements if measurements accurately reflect human experience and are developed in conjunction with their eventual users. It also finds that developing pilot projects during this collaborative process enables new performance information to result in service improvements. Based on these findigs, this work produces a set of recommendations for generating useful performance information from transit data, as well as a specific set of recommendations for expanding the use of data at the MBTA. Thesis Supervisor: Frederick P. Salvucci Title: Senior Lecturer in Civil and Environmental Engineering Thesis Reader: David Block-Schachter Title: Research Associate in Civil and Environmental Engineering

[1]  Mickaël Schil Measuring journey time reliability in London using automated data collection systems , 2012 .

[2]  Jennifer E. Rowley,et al.  The wisdom hierarchy: representations of the DIKW hierarchy , 2007, J. Inf. Sci..

[3]  Jennifer S. Evans-Cowley There's an App for That: Mobile Applications for Urban Planning , 2011 .

[4]  Michael S Frumin,et al.  Automatic data for applied railway management : passenger demand, service quality measurement, and tactical planning on the London Overground Network , 2010 .

[5]  Stephen Greaves,et al.  Household travel surveys: Where are we going? , 2007 .

[6]  Rabi G. Mishalani,et al.  Service Reliability Measurement Using Automated Fare Card Data , 2010 .

[7]  Catherine T. Lawson,et al.  Evaluating the feasibility of a passive travel survey collection in a complex urban environment: Lessons learned from the New York City case study , 2010 .

[8]  Matthew Thomas Shireman Using automatically collected data for bus service and operations planning , 2011 .

[9]  One Gateway Plaza,et al.  Metropolitan Transportation Authority , 1998 .

[10]  Ahmed M El-Geneidy,et al.  Estimating Bus Run Times for New Limited-Stop Service Using Archived AVL and APC Data , 2009 .

[11]  Peter M. Blau,et al.  The Dynamics of Bureaucracy: A Study of Interpersonal Relations in Two Government Agencies. , 1956 .

[12]  Alexandra A Malikova MBTA Green Line 3-car train operating plans to enhance capacity and reliability , 2012 .

[13]  David G Gerstle,et al.  Understanding bus travel time variation using AVL data , 2012 .

[14]  Albert Boonstra,et al.  Managing Information Systems: An Organisational Perspective , 2002 .

[15]  S. Spear,et al.  Decoding the DNA of the Toyota Production System , 1999 .

[16]  Jason B. Gordon Intermodal passenger flows on London's public transport network : automated inference of full passenger journeys using fare-transaction and vehicle-location data , 2012 .

[17]  Adam Rahbee,et al.  Origin and Destination Estimation in New York City with Automated Fare System Data , 2002 .