Transit agencies across North America have been collecting ridership data for decades. But the question that most of this data fails to answer is not how many people are riding — it is who is not riding, and why.
Over the past 18 months, our team analyzed service data from 42 transit agencies, combining it with census demographic data and fare payment records. What we found confirms longstanding suspicions and points toward actionable remedies.
The Headline Finding
2.3×
Average wait time in low-income census tracts vs. high-income areas, same city
Source: Urban Insight Group Analysis, 2025
This is not simply a matter of lower demand in lower-income areas. In fact, households in the lowest income quartile depend on transit at higher rates than wealthier households — they are less likely to own cars and more likely to make essential trips (work, healthcare, food) by transit. The service gap is a supply problem, not a demand problem.
Service Quality Across Income Levels
The chart below shows average frequency (buses or trains per hour) broken down by neighborhood income quartile across our sample of 42 agencies.
Source: Urban Insight Group analysis of GTFS data from 42 North American agencies, 2025.
The pattern is consistent across agency sizes and geographies. Even in cities with strong transit overall, low-income neighborhoods receive systematically less frequent service.
The Reliability Problem
Frequency is only part of the story. Service reliability — the gap between scheduled and actual arrival times — is equally important for riders who cannot afford to miss a bus. Our analysis found that routes serving predominantly low-income areas experience on-time performance rates 14 percentage points lower than routes in high-income areas.
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Methodology note: On-time performance was measured using GTFS-Realtime feeds over a 12-month period (October 2024–September 2025). A trip was considered on-time if it arrived within 5 minutes of scheduled time.
The reliability gap compounds the frequency gap. If a low-income rider faces both fewer buses and less reliable buses, their effective wait time is significantly longer than the schedule implies.
A Geographic View
The map below shows an illustrative example from one major transit agency in our sample. Each marker represents a transit stop; color indicates the average household income of the surrounding census block group. The pattern is visible: the densest stop coverage clusters in wealthier central districts.
What Drives the Gap?
There are several interrelated causes:
- Legacy route structures designed around pre-1970 land use patterns persist even as demographics have shifted
- Revenue allocation formulas that tie service levels to fare revenue — which is lower in lower-income areas partly because of the fare structure itself
- Political economy of service planning that responds more quickly to vocal organized constituencies than to underrepresented low-income communities
- Infrastructure gaps including fewer dedicated bus lanes and transit signal priority in lower-income corridors
"The service gap is a supply problem, not a demand problem. Low-income households depend on transit more — and receive less of it."
What Can Agencies Do?
The agencies in our sample that have made the most progress on equity share several practices:
Equity-weighted service allocation. Some agencies have adopted equity rubrics that explicitly weight service improvements toward high-need neighborhoods. Seattle's King County Metro and Los Angeles Metro have both formalized this approach.
Frequency guarantees. Setting a minimum frequency standard (e.g., buses at least every 15 minutes on all routes) creates a floor that benefits lower-income areas without requiring zero-sum tradeoffs.
Reliability investments in low-income corridors. Targeted bus lane projects and transit signal priority in equity corridors can close reliability gaps without requiring new vehicles.
Participatory service planning. Structured processes that bring community members into service design decisions — not just comment periods — have been shown to shift investment toward underserved areas.
Looking Ahead
Projections based on agencies that have adopted equity-weighted planning frameworks. Source: Urban Insight Group, 2025.
The projections above are based on trajectory data from agencies that have adopted equity-weighted planning. The takeaway is optimistic: the gap is closeable within a decade, but only with deliberate investment and sustained political will.
Marcus Williams is a Principal at Urban Insight Group. He leads the firm's transportation practice. This analysis is drawn from ongoing research supported by a grant from the Robert Wood Johnson Foundation.