Case studies

New York’s MTA uses CitySwift’s data and AI to analyse bus performance, predict trends, and balance supply and demand across 4 city boroughs


  • A holistic view of network performance to analyse mobility patterns and predict future trends and opportunities.
  • The ability to accurately match supply and demand resulting in increased ridership, enhanced passenger experience and less congestion on roads.
  • Ensuring efficiency of resource allocation and network planning decisions during a very unpredictable time.

The Metropolitan Transportation Authority (MTA) is North America’s largest public transport authority with a network serving on average 11 million passengers per day. The MTA manages the New York bus network, which operates the largest bus fleet in the country with almost 6000 vehicles transporting approximately 802.5 million people annually.

In January 2022, the MTA selected CitySwift from over 600 startups to partner in a year-long project for their Covid-19 Response Challenge. As part of the public-private initiative created by The Transit Tech Lab and supported by the New York State Energy Research and Development Authority (NYSERDA), CitySwift worked alongside several teams within the MTA to help solve their most pressing operational and commercial challenges.

Making public transport more attractive, accessible and responsive amid the COVID-19 pandemic

With a fleet of over 5,800 buses, the MTA bus network is a critical part of how the residents of New York transport around the city, providing over two million rides each workday on over 300 routes.

However, COVID-19 cut bus ridership by half while private transportation increased since the start of the pandemic. According to the MTA, daily ridership decreased significantly while bridge and tunnel traffic increased significantly. This posed many challenges for the MTA, particularly around:

  • Passenger safety concerns
  • Transit network planning and resource allocation
  • Reducing congestion and car usage

With this in mind, the initial objective of CitySwift was to provide New York City bus riders with accurate vehicle capacity information and predictions. This scope was created to help passengers to understand when the ‘best’ time to travel was in order to support physical distancing guidelines issued by the U.S. authorities. Not only that, but passengers would be provided with a credible data source to plan their journeys, allowing them to travel with confidence on public transport in the midst of the Covid-19 outbreak.

CitySwift was the first ever company to ingest MTA ridership data successfully, combining passenger counting, to onboard and offboard transactions. CitySwift’s data enabled the MTA's operational and planning teams to predict when and where specific buses would reach near-capacity, allowing operators to adjust accordingly. As a result, supply and demand were accurately matched, resulting in more effective network planning and resource allocation.

The objective was to improve the passenger experience, ensure that people return to using public transportation instead of private vehicles, reduce congestion and greenhouse gas emissions, and ensure that resource allocation and network planning decisions were made as efficiently as possible during a very unpredictable time. 

Optimising internal processes to improve operational excellence

Due to the importance of post-Covid recovery and a data gap inside the existing MTA processes, two core modules from CitySwift's product suite, Evolve and Explore, were also introduced outside the initial project scope.

CitySwift’s Evolve generates AI-optimised runtimes and scenario planning and was used in 4 out of 5 of the New York Boroughs including Brooklyn, Bronx, Manhattan and Queens. The goal of Evolve was to use the program for network performance improvements, timetable optimisation, and process enhancement.

CitySwift’s Explore cleans, enriches and analyses transport data, providing operators with automated insights and visualisations to track network performance against key metrics such as punctuality, demand and efficiency. The MTA was able to integrate Explore seamlessly into their pre-existing systems and data sources to reveal a complete and never-before-seen picture of their bus network. Through this, users were able to effectively scale data processing, fully understand and improve network performance and analyse mobility patterns to predict future trends and opportunities.

CitySwift was able to successfully implement the modules into the existing MTA systems and demonstrated what was possible to deploy throughout New York. Across 4 city boroughs, CitySwift achieved:

  • Bespoke data integrations
  • Platform customisation
  • A Hastus Integration  
  • On-site training & on-boarding of over 40 users 

“…CitySwift to be smooth, enjoyable, and truly impactful…
…Having each of the required metrics in one dashboard, it will save us a significant amount of time as well as provide a medium for a more uniform approach…”
- Matthew Lazo, Transportation Planner, New York City Transit

Once the project was complete, CitySwift received extremely positive feedback from the internal MTA team on the product suite and capabilities. Working across multiple teams such as Customer Experience, Operations Planning, and Ridership Analysis & Modeling (RAM) Teams, each saw clear value in what each product could provide and how the data could be used for upcoming redesign projects, such as the Queens Network Redesign.

This feedback was centred around the ease of use of the products and the myriad of operational benefits they provided to the internal MTA team through the ability of better matching supply and demand, which results in a better passenger experience, increased desire to use public transport and thus less congestion in the city.

CitySwift was honoured to partner with the MTA on this exciting project and become a vital part of their Covid19 recovery strategy, receiving excellent feedback both during and after the process.

….Without a doubt, this will help us to do our jobs faster than ever before.”
…This will improve our current data analytics processes, make more efficient use of our time, and make more data-driven decisions across the NYCT network.
- Evan Bialostozky, Bus Network Redesign Manager, New York City Transit

Read how CitySwift will drive a better bus experience across Wales in our partnership with Transport for Wales.