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From page 22... ... 20 CHAPTER 2: FINDINGS The purpose of this chapter is to organize that information and data into the findings of the research. To assist in the organization, three perspectives of the analysis of the information and data will be used: • Land-Use Assessment • Performance Measurement • Pearson Correlation Matrix These analyses will indicate whether the information and data can be aggregated into findings that appropriately generalize the results, or whether disaggregated use of the data and information may be of more value regarding other areas potential to use this research. Read the entire page →
From page 23... ... 21 service area. This uniform measure enabled us to compare service areas within the regions and across the country. Read the entire page →
From page 24... ... 22 The street network was evaluated for its level of connectivity to determine whether transit riders would have options for direct routes to transit stops. This rating was also done on a scale of 1 to 5, with greatest connectivity being a 5. Read the entire page →
From page 25... ... 23 Table 2-2: Rating System for Street Connectivity Rating System for Street Connectivity Rating Description Aerial View 1 Very low level of street coverage; mostly a few collectors or arterials with a few cul-de-sacs 2 Cul-de-sacs and curvilinear roads predominate; there are few areas with grid coverage 3 Significant grid coverage but also a number of areas with cul-de-sacs/ dead ends 4 Extensive grid network with a few cul-de-sacs and dead ends 5 Complete grid network with no culde-sacs or dead ends Read the entire page →
From page 26... ... 24 RELATIONSHIPS OF LAND-USE SERVICE AREA CHARACTERISTICS TO TRANSIT SERVICE AND PERFORMANCE In the section below, a series of graphics, first used at a presentation for the APTA Bus and Paratransit Conference in May 2005 at Columbus, Ohio, indicate the relationships and findings from a land-use assessment perspective. Figure 2-1: Research Objective Read the entire page →
From page 27... ... 25 Figure 2-2: Typology of Services The routes that were analyzed for this portion of the report are indicated below: Figure 2-3: Case Study List of Services Read the entire page →
From page 28... ... 26 The routes displayed the following characteristics: Figure 2-4: Spatial Adaptation Figure 2-5: Temporal Adaptation Read the entire page →
From page 29... ... 27 Figure 2-6: Demand Level Some of the findings included: Figure 2-7: Moderate Density Read the entire page →
From page 30... ... 28 Trip ends per square mile appears to be a different metric to use in this type of analysis. Figure 2-8: Fixedness and Productivity However, as will be discussed later, the local policy decisions appear often to accept this lower productivity as a trade-off for increased coverage. Read the entire page →
From page 31... ... 29 In this instance the best performing route was again the fixed route in Wilsonville. Also note that density in this analysis is "trip density" in contrast to the more usual population density analysis. Read the entire page →
From page 32... ... 30 Overview of Results As indicated previously, in depth land-use data were able to be collected for four of the case study areas. In those instances the level of detail was significant, but the varied types of service delivery made aggregated comparisons extremely general, as indicated by the results described above. Read the entire page →
From page 33... ... 31 communities, including passage of funding resources legislation. Conversely, in other areas locales have opted out of the transit district to make their own policy decisions and even provide funding for those services. Read the entire page →
From page 34... ... 32 Service Area Definition Each route's service area was defined as follows: • Fixed Route -- all areas within ¼ mile air distance of any branch of the route. • Dial-a-Ride -- the dial-a-ride service area. Read the entire page →
From page 35... ... 33 Pedestrian Network Factors The following factors relating to street network connectivity were evaluated: • Network Connectivity Factor -- the number of links (i.e., street segments between intersections) within the service area, divided by the number of nodes (i.e., intersections) Read the entire page →
From page 36... ... 34 Figure 2-12: Population Density versus Productivity R2 = 0.9514 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 Productivity (passengers/revenue hour) Read the entire page →
From page 37... ... 35 There was some correlation between productivity and the amount of service provided, as measured by the Florida TLOS Indicator, which includes both the span and frequency of service: Figure 2-14: TLOS Indictor versus Productivity R2 = 0.3318 R2 = 0.3855 0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 Productivity (passengers/revenue hour) Read the entire page →
From page 38... ... 36 Factors that showed no apparent correlation included fare, percent of population under 18, and all three of the walkability factors. It should be noted that all of these comparisons are based on single-variable regressions; multiple linear regression and other more advanced statistical techniques might reveal other trends in the data. Read the entire page →
From page 39... ... 37 • The size of TAZs in suburban areas may impact results from this type of performance analysis based on the potential impacts on the available data for the variables used in the analysis. CORRELATION MATRIX The final performance indicator used to assess the findings was the correlation matrix from the Broward County including Margate and surrounding areas as discussed below: The Correlation between Passengers per Revenue Hour and Transit Utilization Factors The hypothesized relationships between passengers per revenue hour and such measures as population density, income, the elderly segment of the population, the student-age segment of the population, the number of owner-occupied units, the number of renter-occupied units and car ownership were tested at the route level with data derived from the census blocks which permitted Pearson correlations to be conducted to measure the magnitude and sign of these relationships. Read the entire page →
From page 40... ... 38 trip purposes. The segment of renter occupied units with one car is slightly negatively correlated with passengers per revenue hour, so as renters get personal vehicles, ridership on the shuttle system would decline. Read the entire page →
From page 41... ... 39 minutes versus 45) than most of the Lauderhill routes. Read the entire page →

From page 22...

... 20 CHAPTER 2: FINDINGS The purpose of this chapter is to organize that information and data into the findings of the research. To assist in the organization, three perspectives of the analysis of the information and data will be used: • Land-Use Assessment • Performance Measurement • Pearson Correlation Matrix These analyses will indicate whether the information and data can be aggregated into findings that appropriately generalize the results, or whether disaggregated use of the data and information may be of more value regarding other areas potential to use this research.