Measuring risk of missing transfers in public transit systems using high-resolution schedule and real-time bus location data

New paper: Liu, L. and Miller, H.J. (2020) “Measuring risk of missing transfers in public transit systems using high-resolution schedule and real-time bus location data,” Urban Studies  (Special issue on Big Data in the City)

Abstract: The emergence of urban Big Data creates new opportunities for a deeper understanding of transportation within cities, revealing patterns and dynamics that were previously hidden. Public transit agencies are collecting and publishing high-resolution schedule and real-time vehicle location data to help users schedule trips and navigate the system. We can use these data to generate new insights into public transit delays, a major source of user dissatisfaction. Leveraging open General Transit Feed Specification (GTFS) and administrative Automatic Passenger Counter (APC) data, we develop two measures to assess the risk of missing bus route transfers and the consequent time penalties due to delays. Risk of Missing Transfers (RoMT) measures the empirical probability of missed transfers, and Average Total Time Penalty (ATTP) shows overall time loss compared to the schedule. We apply these measures to data from the Central Ohio Transit Authority (COTA), a public transit agency serving the Columbus, Ohio, USA metropolitan area. We aggregate, visualise and analyse these measures at different spatial and temporal resolutions, revealing patterns that demonstrate the heterogeneous impacts of bus delays. We also simulate the impacts of dedicated bus lanes reducing missing risk and time penalties. Results demonstrate the effectiveness of measures based on high-resolution schedule and real-time vehicle location data to assess the impacts of delays and to guide planning and decision making that can improve on-time performance.

Keywords:  automatic passenger counter data, General Transit Feed Specification data, public transit, risk of missing transfer

NSF Sustainable Urban Systems “New Mobility, Cities and Data” Workshop Report

On July 15-16 2019, a diverse group of university researchers and community stakeholders from Columbus, Ohio and Portland, Oregon participated in a workshop to explore issues surrounding new mobility technologies, sustainable urban systems and data.  This event was organized in response to the National Science Foundation Dear Colleague Letter (NSF 19-032; “Concepts for Advancing Sustainable Urban Systems (SUS) Research Networks”) released in December 2018.

Deeper scientific understanding of cities and more nuanced, effective sustainability policy and planning interventions are crucial as we move towards an almost completely urbanized planet by the end of the 21st century.  A pressing concern are questions and needs relating to new technology-enabled services that are disrupting the mobility landscape of cities.  Urban mobility is experiencing a revolution, much of it driven by the private sector, with new technologies and services involving light individual transport (e.g., scooters), shared vehicles, microtransit, mobility as a service and eventually connected and autonomous vehicles.  The impacts of the new mobility revolution on urban sustainability is uncertain: similar to the introduction of cars and highways in the early 20th century, it is possible that mobility technologies and services that individually appear to be sustainable and beneficial may collectively reshape cities to have larger environmental footprints, greater inequality and/or less economic flexibility and resilience.

Urban sustainability data observatories (USDOs) are a means for persistent, ongoing data collection, archiving and analysis to enable new knowledge about complex human and coupled human-natural systems, such as cities. They integrate many of the diverse elements that are needed to significantly advance sustainable urban systems (SUS) science. Importantly, they support new data and methods for understanding current SUS drivers and interactions, advancing comparative studies, developing the science to model the future of SUS, and fostering the science of knowledge co-production. USDOs can also facilitate more sensitive and nuanced understanding of how context and history shape the outcomes of policy and planning interventions in complex urban systems.  Finally, they can go beyond observation to enable platforms and processes for data-enabled engagement and discussions among heterogeneous stakeholders concerned with the environmental, social and economic future of their community.

A report on the workshop is now available here (in PDF) SUS Workshop Report – FINAL 25 Sept 2019.

Measuring the impacts of new public transit services on space-time accessibility

Lee, J. and Miller, H. J. (2018) “Measuring the impacts of new public transit services on space-time accessibility: An analysis of transit system redesign and new bus rapid transit in Columbus, Ohio, USA,” Applied Geography, 93, 47-63.


  • Lack of access to opportunities contributes to poor social and health outcomes.
  • Columbus, OH introduced a transit route and schedule redesign and bus rapid transit.
  • We analyze impacts on accessibility to opportunities in a deprived neighborhood.
  • Detailed route and schedule data allow high resolution accessibility analysis.
  • The new bus rapid transit has a much greater impact on accessibility


The absence of effective access to opportunities and services is a key contributor to poor socio-economic and health outcomes in underserved neighborhoods in many cities. The city of Columbus, Ohio, USA is attempting to enhance residents’ accessibility by providing new public transit services. These new services include a major Transit System Redesign (TSR) of the conventional bus network and the introduction of a new bus rapid transit, named CMAX. Using a high-resolution space-time accessibility measure, we analyze whether these new public transit services will change residents’ accessibility to job and healthcare in an underserved neighborhood of Columbus. Also, we assess whether enhancing the CMAX service to reduce delays (e.g., reserved lane, off-board payment system) will improve accessibility. The high-resolution space-time accessibility measure in this study uses published public transit schedules via the General Transit Feed Specification (GTFS). We use multiple departure times during a day to account for the temporal fluctuations of accessibility based on the transit schedule changes. We also consider the operating hours of job opportunities and healthcare services. Results suggest that the TSR yields ambiguous benefits for accessibility to jobs and healthcare. However, the new CMAX service and its potential upgrades lead to a substantial increase in both job and healthcare accessibility. The results can be used for city officials and urban planners to evaluate the effectiveness of public transit innovations in improving accessibility.

Keywords: Transportation; Space-time accessibility; Public transit; Bus rapid transit; Jobs; Healthcare