Movement analytics for sustainable mobility

New paper: Miller, H.J. (2020) “Movement analytics for sustainable mobility.Journal of Spatial Information Science, 20, 115-123.

Invited essay for 10th anniversary issue

Abstract: Mobility is central to urbanity, and urbanity is central to our common future as the world’s population crowds into urban areas. This is creating a global urban mobility crisis due to the unsustainability of our 20th century transportation systems for an urban world. Fortunately, the science and planning of urban mobility is transforming away from infrastructure as the solution towards a sustainable mobility paradigm that manages rather than encourages travel, diminishes mobility and accessibility inequities, and reduces the harms of mobility to people and environments. In this essay, I discuss the contributions over the past decade of movement analytics to sustainable mobility science and planning. I also highlight two major challenges to sustainable mobility that should be addressed over the next decade.

Keywords: movement analytics, mobility science, animal movement ecology, sustainable mobility, urbanity

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

How to Run a City Like Amazon, and Other Fables

What would it be like to live in a city administered using the business model of Amazon (or Apple, IKEA, Uber,…)?  A new book playfully combines speculative fiction and analysis of 38 different business models when applied to running cities of the future.  How to Run a City Like Amazon, and Other Fables, edited by Mark Graham, Rob Kitchin, Shannon Mattern and Joe Shaw, is available in paperback and PDF from Meatspace Press.

My contribution to the book, Cities Need Mass Transit, shows how a highly personalized transportation system envisioned by Tesla and Elon Musk cannot possibly scale to be an effective urban mobility solution.