1. Need vs. Supply Analysis of the New Haven Public Bus System
W. Stan Mathis MD Department of Psychiatry, Yale School of Medicine
Introduction 0%
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Results
Public mass transportation is utilized for a variety of reasons, including environmental impact, convenience, and cost. But, one can argue that its most pressing mission is to provide transportation to those who lack their own mode of transport. The aim of the study was to assess how well the public transportation system of New Haven County was matched to the public transit need using publicly available geospatial datasets from state and federal sources.
Waterbury
The choropleths in the left column depict the specific percentage (Fig. 1) or the relative proportion (Figs. 2-4) of households with progressive levels of vehicle access. Figure 1 visually represents public transportation need as defined for this study: percentage of households having access to zero vehicles. One finds pockets of need in New Haven Town, Ansonia, Southbury, Waterbury, Naugatuck, and Meriden.
Figure 5 depicts intensity of supply as defined for this study: number of bus stops per square mile of census tract. Here one finds a radial distribution of bus routes around the New Haven town center, with increasing bus stop density as the routes converge.
In order to quantify disparities between supply and need, the data were graphed on a scatterplot and divided into quadrants defined by the median supply and median need lines (Fig. 6). Census tracts with high supply and low need were labeled “Over Served”, while tracts with both supply and need above the median were deemed “Good Fit”. Most interesting were the tracts with lower than median supply but higher than median need, called here “Under Served”.
When the results of this sorting are mapped in Figure 7, one can starkly see the Under Served pockets. Corrected for bus stop supply, the areas around Ansonia, Southbury, Waterbury, Naugatuck, and Meriden are more pronounced. Conversely, the high bus supply of New Haven Town is a good fit for its high need, with the isolated exception in the neighborhood of Westville.
Meriden
Southbury
Naugatuck
Ansonia
New Haven
Materials and Methods
Figure 1. Percentage of households with zero vehicles.
Figure 5. Bus stops per square mile of census tract.
A series of custom python scripts were used to extract data from various sources, concatenate and manipulate the data, and draw the figures.
Longitudes and latitudes for each of the 4,325 bus stops serving New Haven County were extracted from a State of Connecticut Open Data geographic dataset (
US Census TIGER files were used to extract the Federal Information Processing Standard (FIPS) code and all the (longitude, latitude) points describing the boundaries of each census tract (
The FIPS code for each tract was then used to query the American Community Survey (ACS) year estimate dataset using a data access interface. The ACS is a sample-based survey that collects key population, social, housing, and economic variables from respondents (response rate in the mid 90%) ( Survey question B08014, which asked how many vehicles were available to the household, was collected. The ACS returns data aggregated to the census tract, setting the geographic modulus for this project.
Public transit Need and Supply were defined:
Under Served
Over served
Good Fit
(n=36)
(n=59)
Median Need (1.87%)
Supply: Bus stops per square mile
Figure 2. Relative proportion with ≤ 1 vehicles.
Median Supply ( stops/mi2)
Need: Percent households with no vehicles
Figure 6. Census tract busing Need versus Supply.
Under Served
Over Served
Good Fit
Waterbury
Meriden
Figure 3. Relative proportion with ≥ 1 vehicles.
Southbury
Conclusion
The availability and investigatory potential of public data is overwhelming. Accessing and interoperating disparate data sources and formats are still the main barriers. Also, there are trade-offs between exigency and accuracy when dealing with large public data sets of limited precision. But, working within these limitations, this study has demonstrated that in New Haven County there are areas of high public transportation need that are not well-served by the current public busing route.
Naugatuck
Westville
Ansonia
Figure 4. Relative proportion with ≥ 2 vehicles.
Figure 7. Goodness of fit of busing Need versus Supply.

2. Figure 1. Percentage of households with no vehicles.
Figure 2. Relative proportion with ≤ 1 vehicles.
Figure 3. Relative proportion with ≥ 1 vehicles.
Figure 4. Relative proportion with ≥ 2 vehicles.
Figure 7. Goodness of fit of busing Need versus Supply.
Figure 5. Bus stops per square mile of census tract.
Figure 6. Census tract busing Need versus Supply. 0%
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Under Served
Over Served
Good Fit
Median Supply ( stops/mi2)
Median Need (1.87%)
Supply: Bus stops per square mile
Need: Percent households with no vehicles
Over served
(n=36)
(n=59)

3. Figure 1. Percentage of households with no vehicles.0%
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Figure 1. Percentage of households with no vehicles.
Figure 2. Percent households with ≤ 1 vehicles.
Figure 3. Percent households with ≥ 1 vehicles.
Figure 4. Percent households with ≥ 2 vehicles.
Figure 7. Goodness of fit of bus need versus supply.
Figure 5. Bus stops per square mile of census tract.
Figure 6. Scatterplot of tract bus Need (percent households with no vehicles) vs Supply (bus stops per square mile).
Deficit
Surplus
Good Fit
Neutral

4. Figure 1. Percentage of households with no vehicles.
Figure 5. Bus stops per square mile of census tract
Figure 2. Percent households with ≤ 1 vehicles
Figure 3. Percent households with ≥ 1 vehicles
Figure 4. Percent households with ≥ 2 vehicles
Figure 7. Goodness of fit of bus need versus supply