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Analyzing Regional Transit Demand + Equity

Replica's Transit Demand & Equity Scores Application supports new analysis about how transit systems service their surrounding communities. Learn how We Used Replica Data to Score Every Transit Stop in the Country.

Published on
October 11, 2023

Transit planners are accustomed to redefining their systems based on shifts in demographics and other underlying factors. However, nothing could have prepared the transit world for the disruptions caused by the Covid-19 pandemic. At the peak of the crisis, transit ridership fell by 70%, taking much needed revenues with it. Today, while the wreckage from the pandemic has mostly cleared, ridership is still running roughly 20% below historic averages across the nation. 

Fig. 1: At the peak of the pandemic in 2020 ridership tumbled by over 70%. Today transit is still running below 20% of historic norms. (Source: American Public Transportation Association (APTA), Quarterly and Annual Totals by Mode)

Transit agencies are now facing the tall order of reassessing what the ‘new normal’ means for them and how to target services to new patterns of demand and usage. Replica data can help with this, and we drew inspiration from the New York Metropolitan Transportation Authority (MTA) Extending Transit’s Reach plan in creating two new Replica metrics related to transit. (To learn more about the MTA’s plan, check out our blog post here.) Specifically, we are pleased to announce the release of the following two new metrics from Replica: The Transit Demand Score and the Transit Equity Score. 

The first metric, the Transit Demand Score, answers questions about where demand for service is highest and where it would be most utilized if made available. It does this by assigning a score from 1 to 100 to predefined zones, where zones with the highest scores have the greatest need for transit. 

Demand scores are based on several factors, including: total population, total workers, households without automobiles, median household income, and the total estimated transit commuters within each zone. The demand score evaluates the need for transit across an entire city, regardless of where transit exists today.   

Fig. 2: Replica Transit Demand Scores applied to Chicago. Each zone on the map is given a score between 1 to 100, where 100 equals the highest level of transit demand. 

The second new metric is the Transit Equity Score. It considers the locations of existing stops to answer the question, “How well does a city’s existing public transit system serve the portion of the community that is most dependent on transit day to day?” 

The equity score, like its demand counterpart, assigns each transit stop a score from 1 to 100, where the highest scored stops are those most critical to the equity of the transit system as a whole. Scores are generated by categorizing the riders using each stop based on their income, race, employment type, average commute times, and access to private autos. We also consider the proportion of work trips occurring from each stop within the calculation. 

Fig. 3: Replica Transit Equity Scores applied to Chicago. Results are applied to the existing stops in a service area. Red and orange colored stops are those that serve populations more dependent on transit services.

Agencies can use the Transit Equity and Demand Scores in their own local analyses to  answer questions such as:

  • How well does my existing network cover the areas of my city with the highest transit demand scores?
  • To what extent do existing transit stops provide connectivity (e.g., access to jobs and essential services) for the most burdened portions of our population?

The demand and equity scores leverage Replica’s proprietary data about mobility within the built environment to create meaningful insight into pressing questions facing transit planners. That said, we view this as just the beginning, and realize agencies will likely adapt these metrics to best suit their own needs. That’s why your feedback is very important to us. Moving forward, we plan to iterate on the models from what we learn to produce new versions that grow increasingly useful at predicting transit demand in tandem with equity considerations for any area of interest.

Learn more by downloading Replica's Transit Guide

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