Why is traffic congestion getting worse? A decomposition of the contributors to growing congestion in San Francisco-Determining the Role of TNCs

Sneha Roy, Drew Cooper, Alex Mucci, Bhargava Sana, Mei Chen, Joe Castiglione, Gregory D. Erhardt

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


Traffic congestion has worsened noticeably in San Francisco and other major cities over the past few years. This change could reasonably be explained by strong economic growth or other standard factors such as road and transit network changes. However, the worsening congestion also corresponds to the emergence of Transportation Network Companies (TNCs), such as Uber and Lyft, raising the question of whether the two trends may be related. Our research decomposes the contributors to increased congestion in San Francisco between 2010 and 2016, considering contributions from five incremental effects: road and transit network changes, population growth, employment growth, TNC volumes, and the effect of TNC pick-ups and drop-offs. We do so through a series of controlled travel demand model runs, supplemented with observed TNC data collected from the Application Programming Interfaces (APIs) of Uber and Lyft. Our results show that road and transit network changes over this period have only a small effect on congestion, population and employment growth each contribute about a quarter of the congestion increase, and that TNCs are the biggest contributor to growing congestion over this period, contributing about half of the increase in vehicle hours of delay, and adding to worsening travel time reliability. This research contradicts several studies that suggest TNCs may reduce congestion, and adds evidence in support of other recent empirical analyses showing that their net effect is to increase congestion. It is more data rich and spatially detailed than past studies, providing a better understanding of where and when TNCs add to congestion. This research gives transportation planners a better understanding of the causes of growing congestion, allowing them to more effectively craft strategies to mitigate or adapt to it.

Original languageEnglish
Pages (from-to)1371-1382
Number of pages12
JournalCase Studies on Transport Policy
Issue number4
StatePublished - Dec 2020

Bibliographical note

Funding Information:
This work was funded by the San Francisco County Transportation Authority. Alan Mislove, Christo Wilson and Le Chen of Northeastern University contributed to the data collection.

Publisher Copyright:
© 2020


  • Causes of congestion
  • Lyft
  • Ride-hail
  • Traffic congestion
  • Transportation Network Companies (TNCs)
  • Travel demand model
  • Travel time reliability
  • Uber

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Transportation
  • Urban Studies


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