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26 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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28 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.