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SARASOTA TRANSPORTATION ENHANCEMENT PLAN

Chapter Four Demand Estimationvi

CHAPTER FOURDEMAND ESTIMATION

INTRODUCTION......................................................................................................... 220CURRENT AND FUTURE DEMAND FOR TRANSIT SERVICE....................................... 220

Fixed-Route Demand Estimates ............................................................................ 220Ridership Trends...................................................................................................... 220Peer Group Comparison............................................................................................ 223Fare and Service Elasticities ...................................................................................... 226Block Group Analysis ................................................................................................ 229Interview and Survey Results.................................................................................... 231

AMERICANS WITH DISABILITIES ACT (ADA) RIDERSHIP DEMAND ESTIMATES .. 235ADA Eligible Population Estimates ........................................................................ 236Demand for ADA Complementary Paratransit Services........................................ 237Conclusions ............................................................................................................ 239

TRANSPORTATION DISADVANTAGED (TD) DEMAND AND SUPPLY ........................ 240Demand for TD Program Trips ............................................................................... 240Demand for General TD Trips ................................................................................ 241Supply of TD Trips .................................................................................................. 242

Supply of Program Trips ........................................................................................... 243Supply of TD General Trips ....................................................................................... 243

Unmet Demand for TD Trips .................................................................................. 244Barriers to Coordination of TD Services ................................................................ 244

DEMAND ESTIMATION: SUMMARY........................................................................... 246


Chapter Four Demand Estimation220

Chapter FourDemand Estimation

INTRODUCTION

The development of public transportation ridership demand estimates play a critical role in theassessment of mobility needs in a community and are crucial for the process of developingtransportation enhancements. For these tasks, demand for SCAT fixed-route bus service, aswell as ADA complementary paratransit service and TD paratransit, was estimated over aseven-year period.

Various methods of forecasting demand for public transportation service are presented anddiscussed in this Chapter. The demand estimation techniques utilize data and findings from allprevious tasks as well as operating data collected from other sources. The calculated demandestimates are compared to current public transportation service to determine the extent towhich transit demand exceeds existing service.

CURRENT AND FUTURE DEMAND FOR TRANSIT SERVICE

There are several different methods available to estimate the level of demand for transit servicein Sarasota County. For the STEP, the demand for fixed-route service has been estimatedthrough the use of trend analysis, peer review comparisons among similar Florida and non-Florida transit systems, fare and service elasticities, census tract analysis, results of communityleader interviews, and survey results. The following sections provide estimates for both fixed-route transit and paratransit demand in Sarasota County.

Fixed-Route Demand Estimates

Ridership Trends

Over the past 14 years, SCAT's ridership has, for the most part, increased steadily. SCAT�sridership has indicated an overall increase of 135 percent during this period, from 814,800passenger trips in FY 1984 to 1,918,177 passenger trips in FY 1997. Only two declines areevident in SCAT�s ridership trend during the 14-year period, first in 1987 and again in 1994.Both declines were relatively small (6.4 percent in 1987; 1.2 percent in 1994), and both werefollowed by periods of healthy ridership growth: a 67.1 percent increase in passenger tripsbetween 1987 and 1993 and a 47.3 percent increase in passenger trips between 1994 and1997. Most recently, preliminary (i.e., not yet validated by the Federal Transit Administration)FY 1998 National Transit Database (NTD) passenger trip information indicates that SCAT has



experienced another decline in ridership: a decrease of 13.6 percent between the 1997 and1998 fiscal years. It is expected that much of this decrease can be attributed to SCATincreasing its base fare from $0.25 to $0.50 between the two fiscal years.

To provide estimates of future annual ridership levels, a linear regression model was calibratedusing SCAT's historical NTD ridership data from fiscal years 1984 to 1997, as well as itsunvalidated ridership estimate for FY 1998. Such a model fits a straight line to the data points,thereby allowing ridership in future years to be predicted. Regression equations are very usefultools for forecasting. Clearly, however, the further into the future a forecast is made, the lessprecise it becomes. In this exercise, ridership levels, as measured by total number of annualpassenger trips, were estimated through FY 2005. The classical linear regression model takesthe following general form:

yt = αα + ββxt + εε t

where yt = dependent variable, or the variable to be forecast, at time t;α = constant term;xt = independent variable that influences yt, at time t;β = parameter on the independent variable;εt = error term, which represents influence not captured by the independent variable.

For this model, a regression line was fitted for annual ridership (in terms of passenger trips)with respect to time, service levels, and fare using the NTD data for these variables for the past15 fiscal years. The level of service was measured by revenue miles, while ridership impacts offare changes were captured by the average fare per passenger trip. It was especially importantto account for the significant changes in SCAT�s base fare in recent years; as such, fare datawere included in the model. The regression equation that resulted is as follows:

yt = -72,134.3 + 36.8xt + 0.51xrevmi - 1,162.8xfare

where yt = annual ridership (thousands of passenger trips) at time t;xt = year (year = 1984, 1985, 1986,...);xrevmi = level of service provided (thousands of revenue miles) at time t;xfare = average fare per passenger trip at time t.

The adjusted coefficient of determination for this model, denoted by R2, is .981, which meansthat approximately 98 percent of the variation in the estimated annual ridership is explained bythis regression equation. This statistic indicates quite a good fit for this model. In addition, theF-statistic, which is a measure of the overall usefulness of the model for predictive purposes, is188.401, which is statistically significant at the 95-percent confidence level (α = 0.05).



Statistical tests (t-tests) prove that the coefficients for time and fare are statistically differentfrom zero (significant) at the 95-percent confidence level. Although the variable representingrevenue miles is not statistically significant at the 95-percent confidence level, it is stillimportant and, therefore, remains in the model for forecasting purposes.

It should be noted that this model was first calibrated using data only through fiscal year 1997.When SCAT�s preliminary FY 1998 data for revenue miles and average fare were plugged intothe model, the resulting estimated ridership was less than one percent different (greater) thanSCAT�s reported number of passenger trips for FY 1998 (1,656,894 trips modeled versus1,656,654 trips reported). Thus, the model was recalibrated using the 1998 data. Table 4-1shows the existing level of ridership (FY 1998) for SCAT and the estimated future ridershipderived from the model for fiscal years 1999 through 2005. Two scenarios are presented: oneholding service (revenue miles) constant over the forecast period, and the other showing anenhanced 10 percent service increase in each year of the forecast. In both cases, SCAT�saverage fare was held constant. Given that the actual level of growth in SCAT�s fixed-routeservice is likely to be somewhere between zero and 10 percent each year, it is expected that,based on this model, the system�s ridership will increase to approximately 2.26 million trips by2005 (the average of the two values shown for FY 2005 in Table 4-1). This represents a 36percent increase from FY 1998.

Table 4-1Fixed-Route Ridership Projections for SCAT

(based on regression analysis)

FY 1998(Prelim) FY 1999 FY 2000 FY 2001 FY 2002 FY 2003 FY 2004 FY 2005

Base1 1,656,654 1,693,858 1,730,662 1,767,466 1,804,270 1,841,074 1,877,878 1,914,682

Enhanced2 1,656,654 1,766,067 1,882,301 2,006,478 2,139,393 2,281,918 2,435,015 2,599,742

1Level of service (and average fare) held constant.2Ten percent annual increase in service (average fare held constant).

To estimate the ridership for a given year, the year itself is substituted for the variable xt in theregression equation, while a given number of revenue miles and a value for the average fareare substituted for xrevmi and xfare, respectively. For the calculations shown in Table 4-1 above,the number of revenue miles provided (for the base scenario only) and the average fare wereheld constant at the FY 1998 levels. For example, to predict ridership for fiscal year 2002, thevariable xt is set equal to 2002 in the model (the number of revenue miles is set at 1,424,014and the average fare is $0.40), and the resulting number of passenger trips (denoted by yt) is1,804,270, as noted in Table 4-1.



This model can be used to estimate ridership in any fiscal year and for any combination ofservice (revenue miles) and fare (average fare per passenger trip) levels. Also, the model canbe recalibrated every few years to include additional years of data. As the number of datapoints increases, so does the reliability of the model.

Peer Group Comparison

One alternate approach in determining the extent of transit demand is to compare per capitaridership, service, and spending levels at SCAT with those at similar systems in Florida and thesoutheastern United States. The fixed-route peer review analysis contained in Chapter Twopresented a wide array of data for 15 transit systems that operate between 9 and 49 buses inmaximum service. Of these systems, nine are in Florida and six are in other southeasternstates. By taking the averages of ridership per capita and other measures and then applyingthem to SCAT's service area population, it is possible to estimate the level of demand for transitservice in systems of this size, all other things being equal.

Table 4-2 presents the results of this exercise. In FY 1997, the peer group systems averaged12.47 passenger trips per capita, while SCAT averaged only 7.64 trips per capita. If SarasotaCounty were to match the average number of trips per capita for the peer group, SCATridership would increase more than 63 percent to more than 3.1 million from its existing 1.9million passenger trips. Similarly, SCAT provides less service, as measured by vehicle miles percapita, than the peer group average. Service levels would have to increase by approximately23 percent to match the peer group mean. Total operating expense per capita for SCAT isabout 68 percent of the peer group average. The projected operating expense would be nearly$5.8 million based on the per capita peer group average, a 46 percent higher figure thanSCAT's total expenditures in FY 1997.



Table 4-2Peer Group Comparisons with SCAT

Measure SCAT Peer Group

Population 251,0191 228,855

Passenger Trips per Capita 7.64 12.47

Vehicle Miles per Capita 6.12 7.51

Maximum Vehicles Operated 25 29

Operating Expenses per Capita $15.75 $23.06

Ridership: SCAT Actual/Projected & Peer Group Mean

Actual 1,918,177Projected 3,130,200

1,971,168

Vehicle Miles: SCAT Actual/Projected & Peer Group Mean

Actual 1,535,539Projected 1,885,150 1,329,857

Operating Expense: SCAT Actual/Projected & Peer Group Mean

Actual $3,953,581Projected $5,788,500

$3,728,323

As discussed previously in the fixed-route peer review analysis presented in Chapter Two, SCAThas one of its peer group�s largest service area populations, which has significantly impacted allof its per-capita measures. As a result, the system has not performed as well as many of itspeers in terms of service supply and service consumption; however, it has done comparativelybetter in terms of cost efficiency. Table 4-2 echoes this fact since it is shown that, in FY 1997,SCAT provided fewer trips and miles of service per person than the averages exhibited for itspeer group, but it did so with lower per-capita costs.

Since it was surmised that SCAT�s peer group averages were mitigated by the presence of the

smallest and largest systems in the group, combinations of the constituent peer systems werereviewed to determine if any subsets would be more representative of SCAT's current situationand/or its expected circumstances in the next several years. This subset analysis narrows thespan in which SCAT is compared, especially since it operated 25 vehicles in maximum service inFY 1997 and the peer group span actually ranges from 9 to 42 peak vehicles.

1The service area population and size figures utilized for SCAT in this analysis are from the system�s FY 1998 NTD report,

although all of the other SCAT and peer system data are for the 1997 fiscal year. These updated figures were utilized because itwas determined that SCAT�s previous method of calculating service area size and population was overestimating these indicators.In the case of FY 1997, SCAT�s original methodology calculated a service area population of 272,474 and a service area size of114.6 square miles. However, using FTA�s recommended ADA-based guidelines of 3/4-mile buffer zones around all fixed routes todetermine service area size and population (as well as 1997 Sarasota County census tract population estimates from Caliper Corp.),revised service area size and population figures were calculated for SCAT. These revised figures of 159.2 square miles and 251,019persons are expected to be a more accurate accounting of service area size and population in Sarasota County than that reportedby SCAT in its FY 1997 NTD submittal, therefore the reason for their use in this analysis.



Table 4-3 presents the ridership and service data for SCAT and three different subsets: peergroup systems that operate between 20 to 30 buses in maximum service, peer group systemsin Florida, and peer group systems in Florida that operate between 20 to 30 buses in maximumservice. As can be seen from the table, SCAT�s performance results are most similar to theaverages of Peer Subset 3, except for the passenger trips per capita and vehicle miles percapita measures. This suggests that the greater discrepancy between SCAT and the averagesof the full peer group are the result of both the inclusion of the larger systems (those operatingbetween 31 and 49 vehicles in maximum service) and the inclusion of the non-Florida peersystems. Nevertheless, SCAT has somewhat lower ridership, less service, and lower expenseson a per capita basis than would be expected for a system of its size.

Table 4-3Peer Subset Comparisons with SCAT

Measure SCATPeer Subset 120-30 Buses

Peer Subset 2Florida

Peer Subset 3Florida,

20-30 Buses

Population 251,019 223,619 273,411 251,992

Service Area Population Density(population/square mile)

1,577 2,157 1,884 1,698

Passenger Trips per Capita 7.64 7.72 8.94 7.55

Vehicle Miles per Capita 6.12 7.00 6.14 6.96

Maximum Vehicles Operated 25 25 28 25

Operating Expense per Capita $15.75 $18.46 $17.43 $15.86

Table 4-4 presents SCAT projections based upon the per-capita averages in the peer group andthe peer subsets. For example, annual ridership estimates range from 1,895,200, if SCAT per-capita ridership were to match the 20-to-30-bus Florida peer subset average, to 3,130,200, ifSCAT per-capita ridership were to match the full peer group average. Projected annual vehiclemiles of service range from 1,541,250 to 1,885,150, and operating expense projections rangefrom $3,981,200 to $5,788,500.

Table 4-4SCAT Projections Based on Per Capita Averages in Peer Groups

MeasureSCAT

(Actual FY97) Peer GroupPeer Subset 120-30 Buses

Peer Subset 2Florida

Peer Subset 3Florida,

20-30 Buses

Projected Ridership 1,918,177 3,130,200 1,937,900 2,244,100 1,895,200

Projected Vehicle Miles 1,535,539 1,885,150 1,757,100 1,541,250 1,747,100

Projected OperatingExpense

$3,953,581 $5,788,500 $4,633,800 $4,375,300 $3,981,200



While peer group analysis is useful for comparing the relative performance levels of similarsystems, caution must be used in applying these results to demand estimation. The underlyingassumption that the propensity to use transit is constant across urbanized areas of similar sizeand with similar transit system characteristics ignores differences among cities in urbandevelopment, demographics, and quality of service. In SCAT's case, the high end of the range(i.e., peer systems operating 31-49 vehicles in maximum service) appears to be currently out ofreach. However, the most realistic projections, based on the averages of the Florida peersystems operating between 20 to 30 buses in maximum service, would result in a 14 percentincrease in fixed-route service and only a less than 1 percent increase in fixed-route operatingexpenditures over FY 1997 levels. Interestingly, SCAT�s FY 1997 ridership already exceeds the

fixed-route ridership projection for this subset by approximately one percent, indicating thesystem�s better comparative performance in attracting riders with less service and loweroperating expenses than the peer systems in this particular subset.

Fare and Service Elasticities

Another means of estimating future demand for transit is through the use of fare and serviceelasticities. An elasticity is a measure of the sensitivity of a dependent variable, such aspassenger trips, to changes in an independent variable, such as fare or level of service. It isalso represented by the percent change in a dependent variable divided by the percent changein an independent variable. While considerable variations can occur, especially for changes atthe level of individual routes, fare and service elasticities have been shown to remain relativelyconsistent across transit systems of all sizes at the aggregate system level.

The American Public Transit Association (APTA) has published a value of -0.43 for the elasticityof ridership with respect to fare (for systems serving areas with populations of less than onemillion).2 According to an Ecosometrics, Inc. report, the elasticity of ridership with respect tolevel of service as measured by vehicle miles is +0.61.3 The elasticity measures are interpretedas follows: a 10 percent increase in the transit fare would result in a 4.3 percent decrease inridership, while a 10 percent increase in the level of service would generate a 6.1 percentincrease in ridership. These elasticities show that, generally, transit riders are more sensitive toservice levels than to the fare.

1American Public Transit Association, Effects of Fare Changes On Bus Ridership (Washington: American PublicTransit Association, May 1991), 7.

2Ecosometrics, Inc., Patronage Impacts of Changes in Transit Fares and Services, report prepared for the U.S.Department of Transportation (Washington: Government Printing Office, September 1980), 65.



It is interesting to note at this point that SCAT recently completed its own analysis of theelasticity of ridership with respect to fare. On October 1, 1997 (the beginning of the 1998 fiscalyear), SCAT doubled its base fare from $0.25 to $0.50. Between FY 1997 and FY 1998, SCAT�sridership dropped 13.6 percent, presumably because of the fare change. The 100 percentincrease in fare and the 13.6 percent decline in ridership indicate that SCAT�s elasticity ofridership with respect to fare was -0.136 for this event (assuming all other things being equal)--a figure significantly lower than APTA�s published value of -0.43. Nevertheless, for purposes ofthis particular analysis, the accepted industry value will be used in the following examplescenarios since it is not known whether other factors had an impact on SCAT�s ridershipdecline, as well.

Table 4-5 presents the results of two fare pricing scenarios as well as a scenario involving anincrease in the level of service. The first scenario predicts how ridership will be affected if thecurrent regular adult fare of $0.50 were to increase an additional 10 percent to $0.55.According to the elasticity measure, with a fare of $0.55, the system can expect a decrease inridership (as measured by the number of passenger trips) of 71,236 trips, all other things beingequal. However, since the demand for transit is considered inelastic with respect to fare(indicating a lesser degree of sensitivity to fare changes), the increase in revenue frompassengers paying the higher fare will more than offset the loss from fewer trips, resulting in anannual net financial impact of $34,922 (based on SCAT's average passenger fare revenue perpassenger trip, i.e., average fare).

In the second pricing scenario, the effects of a fare decrease from $0.50 to $0.45 are reported.As evidenced in Table 4-5, the 10 percent decline in the fare would cause an increase inridership equal to the decrease from the first scenario: 71,236 passenger trips, holding all otherfactors constant. Due to the inelasticity of transit demand with respect to fares, the increase inriders will not generate enough revenue to counter the loss from the lower fare, and an annualnet financial impact of -$40,621 will be realized.



Table 4-5Impacts of Fare and Service Scenarios

MeasureExisting

(FY 1998,Preliminary)

Scenario 110% increase

in fare

Scenario 210% decrease

in fare

Scenario 31

10% increasein service

Fare $0.50 $0.55 $0.45 $0.50

Average Fare $0.40 $0.44 $0.36 $0.40

Vehicle Miles 1,522,987 1,522,987 1,522,987 1,675,286

Passenger Trips 1,656,654 1,585,418 1,727,890 1,757,710

Operating Expense $4,159,199 $4,159,199 $4,159,199 $4,575,119

Change in Ridership -- -71,236 +71,236 +101,056

Change in Revenue -- +$34,922 -$40,621 +$40,422

Change in Operating Expense -- -- -- +$415,920

Net Financial Impact -- +$34,922 -$40,621 -$375,498

1 Scenario 3 utilizes fully-allocated costs per vehicle mile to generate the estimated annual operating expense.

The last scenario in Table 4-5 shows the results of an increase in SCAT's level of service, asmeasured by vehicle miles. As with the elasticity of transit demand with respect to fare,demand with respect to level of service is also considered to be inelastic. Therefore, a 10percent increase in vehicle miles would produce 101,056 additional passenger trips, whichwould generate additional revenues of $40,422, all else being equal. However, a 10 percentincrease in the level of service provided is presumed to require a 10 percent increase inoperating expense. Despite the additional revenues that are generated, this increase inoperating expense to provide the additional service would result in an annual net financialimpact of -$375,498.

As shown by the changes in ridership in Table 4-5, it is clear that, while both elasticities exhibitinelastic demand, changes in fare have less of an impact on passenger trips than changes inservice levels. Nevertheless, the results of the elasticity calculations indicate that increasingservice levels does not necessarily produce the overall financial results one might expect, sincethe cost involved in service expansion is significant. A 10 percent increase in vehicle mileswould represent a major challenge for many transit agencies. These results imply thatproposed service improvements must be closely scrutinized for impacts on cost as well asridership. Also important, however, is the fact that all service extensions are not equal; animprovement targeted at a specific corridor or location where there is significant demand canperform much better than aggregate averages.



Table 4-6 is similar to Table 4-1 in that it presents two ridership projection scenarios for SCAT,one for base conditions (no fare or service changes) throughout the forecast period and one forenhanced conditions with 10 percent service increases in each year of the forecast. The basecondition scenario in Table 4-6 includes the original base fixed-route ridership projections fromthe regression analysis and is identical to the base condition shown in Table 4-1. The enhancedcondition is different, however, since its estimates are based on the previously-discussedservice elasticity of +0.61. That is, it is assumed that an annual 10 percent increase in servicewould result in a 6.1 percent increase in ridership. This increase would be in addition to theannual ridership increases estimated by the linear regression equation. The resulting enhancedestimate is 2.7 million trips by FY 2005, compared to the regression-based enhanced estimatein Table 4-1 of 2.6 million. Again, given that the actual level of change in SCAT�s fixed-routeservice is likely to be somewhere between zero and 10 percent annually, based on the serviceelasticity analysis it is estimated that SCAT will generate approximately 2.31 million trips peryear by fiscal year 2005 (as compared to the 2.26 million trips per year estimate derived fromthe enhanced regression analysis).

Table 4-6Fixed-Route Ridership Projections for SCAT

(based on service elasticity analysis)

FY 1998(Prelim)

FY 1999 FY 2000 FY 2001 FY 2002 FY 2003 FY 2004 FY 2005

Base1 1,656,654 1,693,858 1,730,662 1,767,466 1,804,270 1,841,074 1,877,878 1,914,682

Enhanced2 1,656,654 1,693,858 1,833,987 1,984,862 2,147,269 2,322,053 2,510,118 2,712,430

1Level of service (and average fare) held constant.2Ten percent annual increase in service (no fare changes).

Block Group Analysis

Census block group data can be used to compare demographic information, particularly thosecharacteristics that are highly correlated with a person's or household's need for transit, withthe county's existing transit network configuration. This type of analysis is useful fordetermining whether block groups with transit-dependent characteristics are adequately servedby the existing transit network. For this analysis, the demographic characteristics that wereused to indicate transit dependence included the distribution of youths (less than 18 years old),elderly (65 years or older) persons, low-income (less than $10,000 annual household income)households, and zero-vehicle-ownership households. The database that was used is CaliperCorporation�s 1997 Demographic Estimate & Projection, a commercial database based on 1990Census data and other government information sources. Unfortunately, this database did not



include updated information for zero-vehicle households, so 1990 Census data had to be utilizedfor this particular household characteristic.

The first step in identifying the block groups that have persons or households with the greatestpropensity for transit use involved the calculation of the percent distributions of the fourdemographic characteristics for each block group. This process resulted in a table of valuesindicating the percent of youths, elderly persons, low-income households, and zero-vehiclehouseholds for each of Sarasota County's 155 block groups. The block groups were then sortedfor each characteristic in descending order of percent distribution so that the block groups withhigher percentages for each characteristic would appear at the top of their respective ranges.

From the percentage ranges, an average percent value and a standard deviation value werecalculated for each characteristic.4 Statistically, the standard deviation may be thought of as ameasure of distance from the average value. According to an empirical rule of thumb, for mostmoderately-sized data sets with a bell-shaped normal distribution, approximately 68 percent ofthe data values will lie within one standard deviation of their average and approximately 95percent of the data values will lie within two standard deviations of their average. Each of thefour characteristic ranges was then stratified into four segments based on the following breakpoints: average percent, average percent plus one standard deviation, and average percentplus two standard deviations. Thus, the block groups fell into one of the following fourcategories for each characteristic: below average, above average but below one standarddeviation (average), between one and two standard deviations above average (above average),and more than two standard deviations above average (far above average).

The next step involved the assignment of discrete numerical scores to each of the fourcategories established for each demographic characteristic. These scores serve two basicpurposes: to provide uniform ranking to all of the block groups within a particular category andto numerically differentiate among the four categories for each characteristic. A comparativeprobability estimation method was utilized to develop the scores. First, the probability that ablock group would be part of a specific category for a given characteristic was calculated foreach category. For example, 5 of Sarasota County's 155 block groups were part of the "farabove average" category for the elderly characteristic. This meant that there was a 3.22percent probability (# tracts in category ) # total tracts H 100%) that one of Sarasota County's

block groups would fall within the range established for that particular category for the elderlycharacteristic.

3It should be noted that two of the percentage ranges (for the low-income and zero-vehicle householdsdemographic characteristics) did not approximate a normal distribution. Since this is a key requirement for thestatistical scoring methodology that was utilized, a log transformation was completed for each of these percentageranges. These transformations, then, resulted in normally-distributed data ranges that could be used in the analysis.



After the probabilities were calculated for each characteristic's categories, they were then usedto estimate the categories' scores via comparative probability ratios. That is, the probabilitypercentage for each category was divided into the probability percentage for the "belowaverage" category. This numerator was selected so that, for each characteristic, the censustracts in the "below average" category would receive a score of one (1). Again using the "farabove average" category of the elderly characteristic as an example, it was determined that thescore for this category would be 16.0, since the probability for the "below average" categorywas 51.61 percent and this probability divided by the "far above average" category probabilityof 3.22 percent equals 16.028. The probabilities and final scores for each demographiccharacteristic's categories are presented in tabular form in Appendix N.

Finally, composite scores were calculated for the block groups by summing the individualcategory scores that they had received for each demographic characteristic. The block groupswere then ranked by composite score and stratified into four levels using the same method thatwas utilized to develop characteristic categories. The block groups that fell into the "far aboveaverage" category were defined as primary transit-dependent block groups, i.e., block groupswith the greatest propensity for transit based on the block groups' percentages of youths,elderly persons, low-income households, and zero-vehicle households. Secondary transit-dependent block groups included those that fell into the "above average" category; tertiarytransit-dependent block groups included those in the "average" category.

Table 4-7 presents the results of the block group analysis. The majority of the block groupslisted in the table are served by the existing transit system, with the block groups in DowntownSarasota receiving the most service coverage. For the purposes of this analysis, areas areconsidered to be “adequately served” if a route travels through or borders the block group.Figure 4-1 illustrates the primary, secondary, and tertiary transit-dependent block groups withan overlay of SCAT's fixed-route network. Based upon this analysis, it was determined that allbut one of the primary transit-dependent block groups are currently being served. Overall, onlyeight of the block groups identified as transit-dependent are not currently being served: sevenof these block groups are in North Port and the eighth is in the eastern portion of SarasotaCounty just to the north of North Port. These are the areas, particularly North Port, that maywarrant further detailed analysis with regard to the possible need for additional servicecoverage.

Interview and Survey Results

Findings from the interviews with community leaders in Sarasota County and the results of theSarasota County Transportation Resources and Needs Survey are presented in Chapter Five.The overall opinions of the public transportation system were generally positive. However, itwas generally believed that several service enhancements will be necessary before the systemis able to meet the mobility needs that currently exist in the county. In particular, the



infrequent nature of existing bus routes and the inconvenience of traveling on the currentsystem present formidable barriers that will need to be overcome if the system is to become amore effective transportation option. In addition, findings from these sources suggest thatmore community-oriented transportation within local areas may play a key role in SCAT’s futureas the mobility manager within Sarasota County. This scenario is also suggested by growthdata that shows that the areas with the most anticipated growth will be outside of DowntownSarasota, the area with the most bus service currently. In addition, most of the intervieweesindicated that, although the residential and commercial growth that the county is forecast toexperience will spur additional demand and need for public transportation, actually obtainingthe funding for expansion of SCAT services will be “extremely difficult.” It was widely perceivedthat anti-tax sentiment in the county currently was too strong to expect any new public financialsupport for public transit.

Despite the indeterminate nature of future funding, the data reveals general concensus thattransportation needs exist in Sarasota County and something must be done to ensure adequatemobility for residents and visitors now and in the future. Public transit was seen by many as animportant social responsibility and SCAT and SFC were lauded for the job they are doing inproviding public transportation in an environment characterized by limited resources.Management and staff were commended for efficiently providing a beneficial service to thecommunities within the county. Overall, there was a relatively high level of satisfaction withSCAT and its services among the interviewees and survey respondents.

One way that was discussed to help SCAT alleviate some of its funding burden and becomemore self-sufficient was to attract additional riders, specifically discretionary riders. Some ofthe most common suggestions for increasing SCAT’s ridership base included increasedfrequency, extended service hours, improved amenities at bus stops, the advent of "traveltraining" classes, and the development and implementation of localized, community-basedservices potentially funded through partnerships with communities, municipalities, and localbusinesses. Improvements such as these were seen as being extremely important in makingSCAT more convenient and attractive to residents and visitors in the county.

Results from the SCAT On-Board Bus Passenger Survey were discussed in Chapter Two. Aninteresting finding from the on-board survey was that, while the performance aspects “hours ofservice” and “frequency of service” received the highest combined unfavorable ratings (20 and13 percent, respectively), nearly 84 percent of the riders surveyed rated the service a combined“very good” and “good”. These positive perceptions, along with positive comments from theinterviews and the resources and needs survey, seem to suggest a foundation for increasedsupport and utilization of SCAT’s services, as well as the opportunity for service enhancementsand innovations.



Table 4-7Transit-Dependent Block Groups

Census Tract and Block Group Routes Serving Block Group Comments

PRIMARY TRACTS/BLOCK GROUPS (far above average)

03.00 BG 2 North Sarasota 7, 8, 12 Adequately served

02.00 BG 2 North Sarasota 2, 15 Adequately served


01.00 BG 3 Downtown Sarasota 1 - 8, 11, 12, 15, 17, 18, Trolley Adequately served

07.00 BG 2 St. Armand�s Key 4, 18 Adequately served

24.00 BG 2 Venice 13 Route serves northern & southern portions

27.02 BG 1 North Port -- Not served

27.01 BG 1 North Port 9 Route serves southern portion

01.00 BG 2 Downtown Sarasota 1, 3, 4, 5, 6, 7, 8, 12, 17, Trolley Adequately served

SECONDARY TRACTS/BLOCK GROUPS (above average)

05.00 BG 7 NW Sarasota County 3, 6 Adequately served

15.01 BG 2 NW Sarasota County 3, 14 Routes serve southern portion & NE corner

01.00 BG 6 Downtown Sarasota 1, 3, 4, 5, 11, 17, Trolley Adequately served

11.00 BG 6 NW Sarasota County 7, 12 Adequately served

27.03 BG 3 North Port 9 Route serves northern portion

24.00 BG 3 Venice 13 Adequately served

01.00 BG 1 Downtown Sarasota 3, 6, 11, 12, Trolley Adequately served



02.00 BG 4 North Sarasota 7, 8, 12 Adequately served





TERTIARY TRACTS/BLOCK GROUPS (average)

17.01 BG 6 NW Sarasota County 5, 6, 15 Adequately served



09.00 BG 2 North Sarasota 15 Adequately served

01.00 BG 5 Downtown Sarasota 1, 3, 4, 5, 11, 17, 18, Trolley Adequately served



11.00 BG 3 NW Sarasota County 7, 8, 15 Adequately served


27.06 BG 1 E Sarasota County -- Not served

11.00 BG 2 NW Sarasota County 8, 15 Routes serve northern & eastern portions

11.00 BG 4 NW Sarasota County 7, 12 Routes serve eastern & southern portions

16.00 BG 5 NW Sarasota County 6, 14 Routes serve eastern & southern portions

23.00 BG 2 Venice 9, 13, 16, 17 Adequately served

23.00 BG 3 Venice 13 Route serves southern portion




Transit Dependency Map – se end of document



AMERICANS WITH DISABILITIES ACT (ADA) RIDERSHIP DEMAND ESTIMATES

In addition to requiring transit agencies to provide accessible fixed-route bus service, theAmericans with Disabilities Act of 1990 (ADA) requires that complementary paratransit servicesbe provided by agencies that operate fixed-route bus service. The paratransit service must"shadow" the fixed-route service area and a comparable level of service must be provided forpersons who cannot use the fixed-route service. The regulations define the service criteria thatmust be met when implementing complementary paratransit service. The seven servicecriteria, described in Section 37.31 of the federal regulations (49 CFR Part 37), are:

� Service area � Trip purpose� Response time � Hours and days of service� Fares � Capacity constraints� Eligibility

Only individuals who are ADA-eligible may use the complementary paratransit service. ADA-eligible persons fall into three categories:

Category 1: Persons who are unable to board, ride, or disembark from a vehicle even if theyare able to get to the stop and even if the vehicle is accessible.

Category 2: Persons who cannot use vehicles without lifts or other accommodations. Thesepersons are eligible for paratransit service if accessible fixed-route vehicles arenot available on the route on which they need to travel when they need to travel.

Category 3: Persons with specific impairment-related conditions who cannot travel to aboarding location or from a disembarking location to their final destination.

SCAT operates a total of 20 fixed routes. All of SCAT’s fixed routes currently are served bybuses that are wheelchair lift-equipped. While all of SCAT’s fixed-route vehicles are equippedwith wheelchair lifts, the service is not yet 100 percent accessible to persons with disabilities.SCAT is responsible for providing complementary paratransit services to persons that are ADA-eligible and, to date, SCAT is fully compliant with the requirements for ADA complementaryparatransit service. These services are provided by the CTC in Sarasota County (SFC) undercontract to SCAT. The ADA paratransit program in Sarasota County has been experiencingmuch growth in terms of demand for ADA complementary paratransit services in recent yearsand this demand is now beginning to have a significant impact on the public transit system inSarasota County.

Current growth in both the ADA-certified population and demand for complementary paratransittrips in Sarasota County has been impacted by at least two internal SCAT policies. First, untilvery recently, a very limited and somewhat lenient eligibility process was being used by SCATstaff to certify individuals as ADA paratransit eligible. That eligibility process consisted of a one-



page application that was to be completed by a licensed physician or designated representativeof a local, State, or Federal medical institution or agency chosen by each applicant.Applications were reviewed by SCAT personnel to determine the nature and extent of eachapplicant’s ADA paratransit eligibility. Because SCAT is obligated by Federal law to provideunconstrained paratransit service to persons who are certified ADA paratransit eligible, it is inthe best interest of the agency to ensure that only individuals who are truly unable to use thefixed-route system are certified as a ADA eligible. That lenient eligibility process was likelycontributing to the rate of growth occurring in the ADA paratransit program. Finally, SCAT isalso providing ADA paratransit service to origins and destinations throughout the entire county,rather than restricting trips to origins and destinations within the three-quarter mile corridorthat surrounds each fixed route, as suggested in the ADA legislation. This policy may also becontributing to rising demand for ADA paratransit trips.

Representatives from SCAT and SFC report that a new ADA paratransit eligibility process hasbeen developed and will be implemented by FY 2000. This process has been designed to moreeffectively apply the eligibility criteria outlined in the Federal ADA regulations and should resultin a reduction in the current number of individuals in Sarasota County who are certified as ADAparatransit eligible.

Because the demand for ADA paratransit service in Sarasota County is experiencing rapidgrowth, the agency is now beginning to grapple with the financial implications of providingunconstrained service to eligible individuals. As a result, it is very possible that some time inthe near future capacity constraints could become a reality for Sarasota County’s publictransportation system. If this does happen, SCAT will no longer be in compliance with the ADAregulations. Consequently, the fixed-route system may be jeopardized in that the extent ofADA paratransit services offered in the county are tied directly to the configuration andavailability of the fixed-route bus system in Sarasota County. Thus, any consideration ofexpansion of fixed-route services and/or modifications to existing model of service deliveryutilized by SCAT should include discussion of the potential impact on the demand for ADAcomplementary paratransit services. In order to facilitate these discussions and assist inplanning for future impacts of the ADA legislation, it is necessary to develop estimates of theADA-eligible population residing in Sarasota County, as well as the potential demand for ADAcomplementary paratransit trips by this population.

ADA Eligible Population Estimates

Estimates of the eligible population for all three categories of ADA-eligible persons weredeveloped for Sarasota County based on the methodology presented in the ADA ParatransitHandbook prepared by the U.S. Department of Transportation. The population estimates arepresented in Table 4-8. The population estimates were developed for SCAT’s fixed-route transit



service area. Census block group data for 1997 were used to determine total populationestimates for the three-quarter mile ADA corridor surrounding SCAT’s fixed routes. SarasotaCounty’s fixed-route service area and the three-quarter mile ADA corridor which surrounds theroute network were include in Chapter Two (Figure 2-1). As shown in this figure, a smallamount of population duplication exists where SCAT routes overlap. Estimates of thepopulation within the three-quarter mile buffer zones throughout the county were developedunder the assumption that the percentage that these populations are of total county populationcurrently, would remain the same as in 1997. Estimates of total county population are basedon county-level data from the Bureau of Economic and Business Research (BEBR) at theUniversity of Florida and 1997 Sarasota block group demographic data produced by the CaliperCorporation. BEBR provides estimates of population for the years 1995, 2000, and 2005. Totalcounty population estimates for intermediate years were developed under the assumption thatthe rate of population growth would remain constant within the five-year intervals.

The ADA-eligible populations were determined by multiplying each service area population by1.5 percent for ADA Category 1 and Category 3 combined, and by 0.7 percent for Category 2.Category 2 is broken out because these persons would use the fixed-route system if thevehicles and service were 100-percent accessible. Therefore, the number of ADA-eligiblepersons within this category will become smaller over time as the fixed-route system becomesmore accessible. These population estimates were then adjusted for Sarasota County byweighting the populations by the percent of persons in Sarasota County reporting a "publictransportation disability" in the 1980 Census (7.0 percent) divided by the national percentage(3.5 percent). (Information from the 1980 Census was used because this question was notasked in the 1990 Census.) Based on this methodology, the 1999 ADA-eligible population inSarasota County is estimated to be 7,916 persons and is forecast to grow to 8,628 persons in2005.

Demand for ADA Complementary Paratransit Services

Estimates of the demand for ADA complementary paratransit services have been developed forthe fixed-route service area in Sarasota County. The methodology called for in the ADAParatransit Handbook assumes 100 percent utilization by the entire ADA-eligible population inthe ADA service areas. However, the principal author of the ADA Paratransit Handbook hasreported that national experiences since the publication of the ADA Paratransit Handbook havedemonstrated that communities never achieve 100 percent certification of the ADA-eligiblepopulation. Rather, most rural communities can expect to certify approximately 50 percent ofthe ADA-eligible population and urban communities tend to range from 20 percent to 40percent, based on the level of urbanization. Additionally, mature systems have averagedbetween four and six ADA complementary paratransit trips per user per month. According totrip data provided by SFC, the current trip-making rate for ADA eligible riders has been



approximately 7 trips per user per month (84 trips per user per year). Based on thisinformation, CUTR modified the methodology to better represent the current situation inSarasota County.

Table 4-8Sarasota County ADA Paratransit Population Estimates

YearService AreaPopulation

Est.Category

1 & 3

Est.Category

2Weight

Adj. Est.Category

1 & 3

Adj. Est.Category

2

Adj. Est.Total

1999 246,619 3,699 259 2.0 7,399 518 7,916

2000 250,485 3,757 263 2.0 7,515 526 8,041

2001 254,041 3,811 267 2.0 7,621 533 8,155

2002 257,648 3,865 271 2.0 7,729 541 8,2712003 261,306 3,920 274 2.0 7,839 549 8,388

2004 265,016 3,975 278 2.0 7,950 557 8,507

2005 268,778 4,032 282 2.0 8,063 564 8,628

Table 4-9Sarasota County ADA Paratransit Ridership Demand Estimates

YearAdj. Est.Category

1 & 3

Adj. Est.Category

2

Adj. Est.Total

PercentRegistered

Est. TripsCategory

1 & 3

Est. TripsCategory

2

Est. TotalTrips

1999 7,399 518 7,916 29% 180,230 12,616 192,8462000 7,515 526 8,041 14% 88,371 6,186 94,557

2001 7,621 533 8,155 16% 100,646 7,045 107,691

2002 7,729 541 8,271 18% 114,625 8,024 122,649

2003 7,839 549 8,388 20% 130,546 9,138 139,6852004 7,950 557 8,507 22% 148,679 10,408 159,086

2005 8,063 564 8,628 25% 169,330 11,853 181,183

The demand estimates, included in Table 4-9, represent a forecast of how demand for ADAcomplementary paratransit may grow over the next seven years given the current situation inSarasota County. The estimates of demand presented in Table 4-9 are based on theassumption that ADA complementary paratransit utilization within the SCAT fixed-route servicearea begins in 1999 at the current rate of certification among the ADA-eligible population (29percent), as reported by SFC, and will experience a 15 percent decrease early in FY 2000 due toimplementation of a stricter ADA paratransit eligibility process. The 15 percent reduction in thenumber of persons certified as ADA paratransit eligible is based on national experiences whichhave shown that the implementation of a strict eligibility determination process, coupled with anaggressive recertification effort, may initially reduce the number of certified individuals by asmuch as 15 to 20 percent. For this set of demand estimates, the rate of certification is then



increased incrementally between FY 2000 and 2005 from 14 percent certification rate tocertification of 25 percent of the eligible population. The estimates are also based on a trip-making rate of 7 trips per month per ADA-certified paratransit user (84 trips per year). Thistrip-making rate was provided by SFC and represents the current rate of utilization ofparatransit services by active ADA-certified SFC passengers. Using this approach, the demandfor ADA complementary paratransit can be expected to grow from 94,557 trips in 2000 to181,183 trips in 2005.

Conclusions

Based on the information currently available, the set of demand estimates presented bestrepresents the current, unique situation in Sarasota County (demographically and statistically)and, therefore, is the set of demand estimates used throughout the remainder of this report forplanning and budgeting purposes. However, because any combination of variables could resultin Sarasota County’s ADA paratransit program becoming more important to the mobility ofpersons with disabilities, it is recommended that SCAT continue to monitor the average ADAparatransit certification rate, trip-making rate, and ridership demand estimates on a regularbasis. This will be particularly important over the next two years, as SCAT proceeds with theimplementation of a stricter eligibility determination process and recertification of all persons intheir ADA paratransit database. Given the data currently available and using the average tripcost of $15.00 for general paratransit trips provided by SFC in the Annual Operating Report(AOR) for FY 1998, the total cost of providing the estimate number of ADA complementaryparatransit trips in 2005 would be approximately $2,717,745.



TRANSPORTATION DISADVANTAGED (TD) DEMAND AND SUPPLY

Chapter One presented forecasts of the Potential TD Population and the TD Population inSarasota County. As discussed in Chapter One, the Potential TD Population is forecast toincrease from 146,801 persons in 1999 to 160,924 persons in 2005 and the TD Population isforecast to grow from 24,449 persons in 1999 to 26,773 persons in 2005. The followingsections use the population forecasts presented in Chapter One to develop demand estimatesfor TD transportation in Sarasota County. A description of the methodology used to developthe forecasts is also presented.

Demand for TD Program Trips

Florida’s TD program provides two types of trips for TD customers – program trips and generalpurpose trips. The demand for each type of trip is forecast in a distinctive manner. Asdiscussed in Chapter One, program trips are sponsored by social service agencies for thepurpose of transporting clients to and from the programs of those agencies. Members of thePotential TD Population are eligible for these trips. The demand for program trips is a deriveddemand, that is, the demand for program trips is dependent upon the existence of theprogram(s) to which the Potential TD Population is transported. For example, demand for tripsto sheltered workshops exists only because there are sheltered workshop programs. Thus, thedemand for program trips is equal to the number of trips required to take advantage of theservice offered by the programs. Therefore, the demand for program trips depends on the levelof funding for the various social service programs.

Many factors at various levels of government determine the level of funding for social serviceprograms. The lack of clear indicators of the future funding levels of these programs make itnecessary to make funding assumptions. For this report, it is assumed that funding for socialservice programs, and for transportation to and from the programs, will increase at a ratesufficient to continue to provide the current level of service to members of the Potential TDPopulation in Sarasota County. That is, funding for these programs will increase at a ratesufficient to allow the number of trips supplied in the county to grow at the same rate as thePotential TD Population. Under these assumptions, the demand for program trips in SarasotaCounty is forecasted to increase from 272,689 in 1999 to 294,663 in 2005. Table 4-10 showsthe forecasts of the Sarasota County Potential TD population, as well as demand and supplyestimates for program trips by the Potential TD population for the years 1999 through 2005.



Table 4-10Forecasts of Sarasota County Potential TD Population

And Program Trip Demand and Supply

Year Potential TD Population(Category I)

Demand forProgram Trips

Supply forProgram Trips

1999 146,801 272,689 272,6892000 148,648 276,235 276,2352001 151,025 279,825 279,8252002 153,440 283,464 283,4642003 155,895 287,148 287,1482004 158,391 290,881 290,8812005 160,924 294,663 294,663

Source: Estimates prepared by CUTR using the methodology described in the 1993 CUTR report MethodologyGuidelines for Forecasting TD Transportation Demand at the County Level

Demand for General TD Trips

General trips are trips made by transportation disadvantaged persons to destinations of theirchoice (not to agency programs). Examples of general trips are trips to work or grocery storesand non-Medicaid medical trips. In this report, the demand for general trips is forecasteddifferently from the demand for program trips. The methodology developed to forecastdemand for general trips involves the use of trip rates derived in a study of paratransit demandconducted in 1990 for the San Francisco Bay Area Metropolitan Transportation Commission byCrain & Associates, Inc. and others (San Francisco Bay Area Regional Paratransit Plan: FinalReport). The trip rates were developed from the actual experiences of paratransit systemsaround the country that were meeting most or all of the trip demand in their service areas. Theuse of these trip rates has been recommended by the Federal Transit Administration forestimating demand for ADA complementary paratransit.

In the San Francisco study, trip rates were developed from an evaluation of seven paratransitsystems that provided high levels of service. These trip rates, 1.0 and 1.2 trips per month percapita in urban and rural areas, respectively, represent the demand for general trips. Totaldemand for general trips is simply the TD Population multiplied by the trip rates. The TDPopulation (rather than the Potential TD Population) was used to forecast demand because theTD Population is the pool of persons eligible for general trips funded by the State. The rate of1.0 trip per month was used for TD persons with access to fixed-route transit and the rate of1.2 trips per month was used for TD persons without access to fixed-route transit. Table 4-11shows the forecasts of the Sarasota County TD Population, as well as demand and supplyestimates for general trips by the TD population for the years 1999 through 2005. Based onthis methodology, the demand for general trips was estimated to be 318,033 in 1999 andforecast to increase to 348,263 in 2005.



Table 4-11Forecasts of Sarasota County TD Population

And General Trip Demand and Supply

YearSarasota County

TD Population(Category II)

Demand forGeneral Trips

Supply ofGeneral Trips

Unmet Demandfor General Trips

1999 24,449 318,033 51,573 266,4602000 24,772 322,234 52,263 269,9712001 25,160 327,281 52,965 274,3162002 25,554 332,406 53,676 278,7302003 25,954 337,610 54,396 283,2142004 26,360 342,891 55,125 287,7662005 26,773 348,263 55,864 292,399

However, it should be noted that the figures related to the demand and supply of TD generalpurpose trips in Sarasota County include trips that will fall under the category of ADAcomplementary paratransit services. As discussed in previous sections, the ADA of 1990provides for the unconstrained delivery of paratransit trips for persons who cannot use thefixed-route bus system due to the nature and/or extent of their disability. In Sarasota County,persons may be certified as eligible for ADA paratransit trips, as well as TD general purposetrips. In addition, elderly individuals who are not able to access the fixed route because theyare too frail are currently being classified as TD eligible, rather than ADA eligible. Therefore, itis likely that the figures included in Table 4-11 related to unmet demand for general purpose TDtrips, as well as those contained in Table 4-9 related to the demand for ADA paratransit trips,are inflated and reflect some duplication in the calculation of trip demand.

Supply of TD Trips

It is expected that program trips and general trips will be supplied by operators within thecoordinated TD system and by operators currently outside of the coordinated system. Thenumber of trips supplied within the coordinated system in 1998 is available in the AnnualOperating Report (AOR) submitted by the Sarasota County Community TransportationCoordinator. However, data are lacking on the number of trips supplied outside of thecoordinated system. To estimate the number of trips supplied outside of the coordinatedsystem, data from 1995 Actual Expenditure Reports submitted by the agencies that fund TDtrips were compared to the CTC’s AOR for that year. This comparison suggested that 75percent of the funds expended for TD trips in 1995 were expended within the coordinatedsystem, and the remaining 25 percent were expended outside of the coordinated system. Itwas assumed that the average cost of a trip within the coordinated system was the same as theaverage cost of a trip outside of the coordinated system. Therefore, it was assumed that 75



percent of the TD trips supplied were supplied within the coordinated system, and theremaining 25 percent were supplied outside of the coordinated system.

Supply of Program Trips

As discussed previously, the demand for program trips is a derived demand—the demanddepends on the existence of social service programs. Therefore, assuming that these programsprovide sufficient funding to transport their clients to their programs, the supply of programtrips will equal the demand for the trips. For this report, as discussed in the section ondemand, it is assumed that the demand and supply of program trips both within thecoordinated system and outside of it will increase at the same rate of growth as the potentialTD population (see Table 4-10). Under these assumptions, based on the estimated number ofprogram trips supplied in 1998, the supply of (as well as the demand for) program trips inSarasota County is forecasted to increase from 272,689 in 1999 to 294,663 in 2005. However,it should be noted that the supply of program trips will remain equal to the demand for thosetrips only as long as the various governmental and social service programs maintain sufficientfunds to accommodate the transportation needs of their clients. Currently, many of theseprograms are facing serious threats to their funding in general and, in some cases, theirtransportation funding specifically (i.e., Medicaid). If the budgets of these programs are cut oreliminated, the demand for non-sponsored trips can be expected to grow significantly. This isparticularly true in the case of Medicaid non- emergency transportation. The transportationbudget for this federal program has already been cut by 30 percent. However, demand forthese trips can be expected to remain at the current level, regardless of agency funding. Thistype of scenario potentially represents a serious challenge that may have to be met by the CTCin the future.

Supply of TD General Trips

Supply forecasts for general trips among the TD population in Sarasota County are presented inTable 4-11. General trips will be purchased through the TD Trust Fund, through local subsidies,and by social service agencies. Within the coordinated system, it is assumed that the supply ofgeneral trips purchased through the TD Trust Fund will increase at the same rate as the TDPopulation, and that the supply of general trips purchased through local subsidies and by socialservice agencies will increase at the same rate as the Potential TD Population. Outside of thecoordinated system, it is assumed that the supply of general trips purchased through localsubsidies and by social service agencies will grow at the same rate as the growth in thePotential TD Population. (Outside of the coordinated system, no trips will be purchased throughthe TD Trust fund.) Under these assumptions, based on the number of general trips supplied in1998, the supply of general trips is forecasted to increase from 51,573 in 1999 to 55,864 in2005.



Unmet Demand for TD Trips

A significant gap exists between forecasted trip demand for general trips among the TDPopulation in Sarasota County and the forecasted supply of these trips. The forecasted unmetdemand for TD trips is the difference between the demand and the supply of these trips. All ofthe unmet demand consists of demand for general trips. As discussed previously, there is nounmet demand for program trips because the demand for program trips is assumed to equalthe supply. Unmet demand refers to demand that currently exists in the TD transportationmarket, but is not being met due to factors such as funding, price, convenience, comfort,eligibility, and the availability of other transportation modes. The unmet demand is forecastedto increase from 266,460 in 1999 to 292,399 trips in 2005, as shown in Table 4-11. However,because some amount of duplication exists in the calculation of ADA paratransit demand andTD trip demand, a portion of the unmet demand for TD trips will likely be met through SarasotaCounty’s ADA paratransit program which is coordinated by the CTC.

Data related to trip purposes of general trips in Sarasota County suggest that approximately 46percent are medical, 27 percent are work or educational, 14 percent are life-sustaining, 10percent are nutritional, and 3 percent are "other" (e.g., recreational trips and personalbusiness). Assuming that these data also apply to the unmet demand for general trips, theunmet demand in 2005 would be for approximately 134,504 medical trips, 78,948 educationand work trips, 40,936 life-sustaining trips, 29,240 nutritional, and 8,772 other trips.

Barriers to Coordination of TD Services

No federal, state or local government policies are in place that prohibit, hinder or prevent thecoordination of TD transportation services. No characteristics of the natural or operationalenvironment constrain or hinder coordination. The major barriers to coordination of both inter-and intra-county coordination remain in existing and proposed funding constraints. Fundingreductions in both Medicaid and the Older American Act grants have forced the CTC to monitorexpenditures of funding closely and limit the availability of out-of-service-area trips.Coordinating inter-county trips require the negotiation of farebox collections that serve asmatch for grant funding sources. Passengers using more than one coordinated system for masstransit service may be responsible for a fare when boarding each entity's vehicle. This can bevery cost prohibitive for TD passengers.

Defining eligibility for sponsoring funds also often varies from system to system, makingeligibility determination problematic for the systems. In addition, variance in rate schedules forpassenger trips creates coordination difficulties. Senior Friendship Centers, Inc., uses a zonalrate while adjacent counties employ mileage rates. Adjacent counties include Manatee, DeSoto,Charlotte and nearby Pinellas and Hillsborough.



Perceived territorialism also has limited the success of inter-county coordination. The CTCcoordinates return trips for its clientele when they return from adjacent counties, eliminatingdown time for their vehicles. Little reciprocation exists from surrounding counties. However,extensive coordination between Sarasota and DeSoto counties exists, since Senior FriendshipCenters is the CTC for both counties.

Intra-county coordination has vastly improved over past years. Former barriers, such asinsurance requirements, rates and contract language have been eliminated. The CTC currentlyhas six (6) coordinated agreements with local agencies and eleven (11) contracted operators.The CTC continues to negotiate coordination opportunities with private entities in SarasotaCounty. Sarasota County CTC's ultimate goal is 100% coordination.

Local efforts to address the barriers to coordination have included:

1. Seeking coordination agreements with adjacent counties that may encouragestandardized trip and farebox rates with the CTCs.

2. Seeking a simplified eligibility process for purposes of inter-county coordination.

3. Establishing a toll-free phone number for return trips.

4. Provide passengers with business cards that identify the return operator.

5. Selecting pick-up/drop-off locations at county lines for trips moving south to north, withPinellas and Hillsborough as final destinations.

6. Continuing efforts to increase intra-county coordination by recruiting and includingproviders not currently under contract.

The Commission for the Transportation Disadvantaged can encourage and support coordinationthrough the adoption of standardized eligibility definitions and a uniform application process.The Commission also could employ a uniform inter-county contract/agreement for all CTCs.Educational workshops offered by the Commission for the Transportation Disadvantaged shouldinclude the barriers to inter-county coordination.

One of the main objectives of the STEP has been to identify opportunities and means tocoordinate existing transportation resources in the community in order to achieve enhancedindividual and community mobility. A number of the alternatives presented in Chapter Eightaddress issues related to achieving higher levels of community transportation coordinationthrough the development of mutually beneficial relationships.



DEMAND ESTIMATION: SUMMARY

The various analyses contained in this chapter suggest that, while there is some level of unmetdemand for fixed-route and paratransit service in Sarasota County, overall, SCAT and the CTCare doing a very good job providing service to those who most need it. However, as theanalyses of ADA complementary paratransit service and TD transportation demand indicated,the need for public transportation service in Sarasota County will continue to grow. In addition,there are several areas in South County with large proportions of trnsit dependent individualsthat are either not served or not adequately served by the fixed-route system. Specific transit-dependent areas deserving additional analysis have been noted in this chapter. The communitymust also consider future growth patterns in the county, particularly in the unincorporatedareas of South County and along the I-75 corridor, in addition to the residential and commercialdevelopment that is occurring throughout the county. All of these issues raise importantquestions regarding the future direction public transportation should take in Sarasota Countyand the region. The next chapter expands on the issues raised thus far in the STEP bydescribing input gathered from the community at-large through various STEP publicinvolvement activities.

chapter four demand estimation - cutrchapter four demand estimation 224 table 4-2 peer group...

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