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CHAPTER 5
Results and Performance Evaluation
This chapter synthesizes the findings of the preliminary · Ridership is not a simple function of density. Local policy
and detailed case studies to identify applicable traits that decisions often appear to accept lower productivity (as
transit agencies can consider in establishing suburban measured in passengers per hour) as a trade-off for increased
transit services. To show how the applicable traits may coverage (see Figure 5-9).
relate to one another, the chapter presents several analyses. · The best performing routes (with performance measured
However, because the findings of this study were insuffi- in passengers per hour) are among those serving the most
cient to establish concrete guidelines for all transit agencies, balanced mix of land uses (see Figure 5-10).
each of the analyses in the chapter uses only a few case · Services that target specific groups, such as seniors and stu-
studies. Therefore, the findings of the analyses in this dents, seem to be among the most productive (with pro-
chapter cannot be extended to all transit agencies. ductivity measured in passengers per hour and weekday
Nonetheless, the traits identified in this chapter can help revenue-hours) (see Figure 5-11).
transit agencies think about the issues involved in sub-
urban transit services.
Analysis of Land Use
Service Area
versus Transit Service Characteristics
and Operating Performance
An analysis was performed on routes in Albany, Detroit,
Minneapolis, and Portland to determine the relationship Density
of land use (i.e., service area characteristics) to transit serv- Diversity
ice characteristics and operating performance measures. Design
Deterrents
Figure 5-1 shows this research objective, and Figure 5-2 to driving
shows the types of suburban transit services available. Fig-
ure 5-3 shows the routes that were analyzed for this portion
of the report. Figures 5-4, 5-5, and 5-6 show the "spatial
adaptation" (i.e., flexibility of location), "temporal adapta- Service Format Operating
Productivity Performance
tion" (i.e., flexibility of time), and demand level, respec- Transit Service Service Design
Cost Measures
tively, of all the routes. Characteristics Parameters
Although no clearly defined characteristics were isolated, a
series of findings were made:
Figure 5-1. Research objective: To determine the
· Most services are in areas with fewer than 20,000 trip ends relationship of land use (i.e., service area
per square mile (see Figure 5-7). characteristics) to transit service charac-
· The best performing services (with performance measured teristics and operating performance
in passengers per hour) are among the least flexible (see measures.
Figure 5-8).
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Spatial Adaptation
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Temporal Adaptation
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employer shuttles door-to-door demand response
high
Figure 5-2. Spatial and temporal flexibility, or
"adaptation," of different types of
suburban transit services.
Figure 5-3. Case study routes that were analyzed for this portion
of the report.
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Note: Numbers on the y-axis represent the number of routes analyzed for this portion of the report. Bars withou t x-axis labels represent services that
incorporate characteristics of both the service to the right and the service to the left of the bar.
Figure 5-4. Spatial adaptation of the routes analyzed for this portion of the report.
Note: Numbers on the y-axis represent the number of routes analyzed for this portion of the report.
Figure 5-5. Temporal adaptation of the routes analyzed for this portion of the report.
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Note: Numbers on the y-axis represent the number of routes
analyzed for this portion of the report.
Figure 5-6. Demand level of the
routes analyzed for this
portion of the report.
Finding : Most services are in areas with fewer than 20,000 trip ends per square mile.
Note: See Figure 5-3 for a "key" to the colors and abbreviations listed here.
Figure 5-7. Density versus transit service.
Finding: The best performing services are among the least flexible
(with performance measured in passengers per hour).
Note: See Figure 5-3 for a "key" to the colors and abbreviations listed here.
Figure 5-8. Route flexibility or time flexibility versus productivity.
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Finding: Ridership is not a simple function of density. Local policy decisions often
appear to accept lower productivity as a trade-off for increased coverage (with
productivity measured in passengers per hour).
Note: See Figure 5-3 for a "key" to the colors and abbreviations listed here.
Figure 5-9. Trip density versus productivity.
Finding: The best performing routes (with performance measured in passengers per
hour) are among those serving the most balanced mix of land uses.
Note: See Figure 5-3 for a "key" to the colors and abbreviations listed here.
Figure 5-10. Land-use mix versus productivity.
Finding: Services that target specific groups seem to be among the most productive
(with productivity measured in passengers per hour and weekday revenue-hours).
Note: See Figure 5-3 for a "key" to the colors and abbreviations listed here.
Figure 5-11. Service level versus productivity.
