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10.000
9.000
8.000
7.000
Service Area (square miles)
6.000
5.000
4.000
3.000
2
R = 0.4945
2.000
R2 = 0.4086
1.000
0.000
0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0
Productivity (passengers/revenue hour)
Figure 5-15. Service area size versus productivity.
The demand-responsive services, when looked at as a performance over time. Table 5-2 provides an example matrix
group, tended to show better correlation for several factors comparing performance measures with service types for the
than the correlation shown for these factors by other serv- services discussed thus far in this chapter. The left group of
ices. Two possible explanations for this are that (1) the performance measures represents traditional measures that
demand-responsive services tended to serve larger areas than most transit agencies already use. The right group of per-
the fixed-route and commuter services and (2) none of the formance measures represents nontraditional measures sug-
demand-responsive services overlapped with each other. gested in this report based on land use (i.e., service area
To sum up, many of the fixed-route services that were stud- characteristics) and transit service characteristics. The center
ied had service areas that significantly overlapped with other group of performance measures represents the application of
fixed-route services. Because the overlapping services covered both groups of measures to the routes discussed thus far in
areas with relatively similar population densities, any differ- this chapter.
ences in productivity would be the result of other factors. In The services have been structured to isolate performance
contrast, all of the demand-responsive services that were measurement ranges that transit planners can use in estab-
studied served unique areas that were not part of the service lishing their own services and measures for evaluation.
areas of other studied routes. Thus, the variety of services that
were included in this analysis from various parts of the coun-
try did not provide many significant findings, with the fol- Activity Surface Example
lowing exception: Population density, not trip density, proved
As indicated in a previous section, where sufficient demo-
to have a good correlation to productivity, especially for
graphic and land-use data are available in GIS format, an
demand-responsive services.
activity surface can be created to depict the land-use and
travel patterns. Figures 5-16 through 5-18 and Table 5-3 show
Relating the Land-Use Analysis
an example of how this activity surface can be tied to sub-
to the Transit Performance
urban transit service planning. The agency featured in this
Measurement Analysis
example is MetCouncil in Minnesota.
Matrixes can be developed to help transit agencies deter- Route 224 serves an area with more density and destina-
mine the most appropriate form of transit and to measure tions than Route 421. This is depicted in Figure 5-16 by the
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Table 5-2. Service types versus performance measures.
Performance Measures
Application of traditional and nontraditional measures to case study Nontraditional measures
Traditional measures*
routes suggested in this report*
Weekday TLOS
Weekday TLOS
Revenue-Hours
Revenue-Hours
Passengers per
Passengers per
Service Area
Service Area
Connectivity
Connectivity
Productivity
Productivity
Service
Ridership
Ridership
Indicator
Indicator
Network
Network
Annual
Annual
Annual
Annual
Types
Index
Index
Hour
Hour
0.056 1.408 1.410 6.600
Fixed Route 11,599 1,770 6.6 11,599 1,770 6.6 0.056 4.387 1.57 6.6
0.125 5.164 1.680 32.300
Demand
13,970 1,778 7.9 13,970 1,778 7.9 0.292 2.660 1.37 7.9 0.292 2.66 1.37 7.9
Responsive
4,064 953 0.028 3.924
Flexible 1.0-8.8 4,352 953 4.6 0.028 7.506 1.59 4.6 1.471.59 4.615.5
29,464 16,929 0.111 8.947
Commuter 83,800 5,080 16.5 83,800 5,080 16.5 0.080 2.091 1.84 21.3 0.056 2.091 1.771.84 21.325.9
0.080 2.919
Weekday TLOS Indicator = % of day service provided to bus stops along route, with each fixed-route-only bus providing 10 minutes worth of transit access.
Service Area = route service area (square miles).
Network Connectivity Index = (# of intersections/# of links) in area served by route (1.55 = grid pattern).
Productivity = boardings per revenue-hour.
*Values in these columns represent typical ranges or averages that transit agencies may find for their services.
Table 5-3. Operational performance of
MetCouncil Routes 224 and 421.
Performance Measure Route 224 Route 421
Annual passengers 11,599 4,352
Revenue-hours 1,770 953
Passengers per hour 6.6 4.6
Cost per passenger $6.48 $18.73
Cost per hour $42.45 $85.54
Source: MetCouncil Route Profiles
Figure 5-16. MetCouncil (Minnesota) activity
surface.
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Shoreview
Community Ctr
Twin Midwest To Roseville:
Cities Special
Services
ria
Arsenal 224 226 227
62
Victo
To St. Paul:
Hwy
1 P 62
96
Ramsey
Shoreview County
Arden View Mall Library
Townhomes
Hamline
SNAIL
LAKE
Lexington
Shoreview
Co Rd
F
Arden Hills
Business Park Atrium
Dunlap
Apartments
Hwy
Bethel 51
College Red Fox Rd 694
CLC O
l
d
2 SuperTarget
Hw
Grey Fox Rd
y 10
Co Rd
E 227
Arden
Hills
LAKE
JOHANNA e
LAKE Co Rd
Av
JOSEPHINE D
ng
Josep
Snelli
hin
e
Lydia
Fairview
Co Rd
C2
Co Rd
C
35W
Roseville
3 Co Rd
B2
P Hwy
36
Rosedale Co Rd
B
Lexington
Transit Center
Hamline
Snelling
To Minneapolis:
32 52R 260 801
To Roseville:
223 224 225
226 227
To St. Paul:
65 83 84 87
Figure 5-17. Route 224 map.
darker shading and numerous ridges. Thus, the planning although more service area coverage was provided under
solution for Route 224 was to add a few route deviations, the flexible-route service (Route 421).
but maintain a general fixed-route orientation (see Figure Note: Although MetCouncil and some other areas that
5-17). Conversely, Route 421 was designed to serve a were examined in this study had the necessary demographic
broader area with flexible-route service, which has more and land-use information available to display in GIS format,
demand-responsive characteristics than fixed-route char- most areas either did not have data readily available in this
acteristics (see Figure 5-18). The differences from serving format or had the data housed in multiple agencies, which
diverse markets and densities are reflected in the opera- resulted in numerous difficulties in collection, display, and
tional information, which shows higher ridership, more comparison with transit data. There are indications that more
service hours, and lower costs for Route 224 than for Route areas are looking to connect the land-use and transit data in
421 (see Table 5-3). Thus, the efficiency and effectiveness, GIS format, which in the long term will assist in developing
measured in passengers per hour and cost per passenger, more land-use and transit relationships for consideration in
was better for the route-deviation service (Route 224), suburban service planning.
