Final Report Evaluation of Land Use and Transportation Strategies to Increase Suburban Transit Ridership in the Short Term by Gregory L. Thompson, Professor Jeffrey R. Brown, Associate Professor with Torsha Bhattacharya as Co‐Author for Chapter 4 Department of Urban and Regional Planning Florida State University A Report Made to: The Public Transit Office Florida Department of Transportation 30 April 2010 The Florida State University Department of Urban and Regional Planning Room 351 BEL 113 Collegiate Loop PO Box 3062280 Tallahassee, Florida 32306-2280 +1.850.644.4510 http://www.fsu.edu/~durp +1.850.644.8514 direct +1.850.645.4841 fax [email protected] http://garnet.acns.fsu.edu/~gthompsn/my_web/default.htm 30 April 2010 Ms Diane Quigley Public Transit Office Florida Department of Transportation Tallahassee, Florida Dear Ms. Quigley: On behalf of Professor Jeffrey Brown and myself, I am pleased to submit to you the final report, “Evaluation of Land Use and Transportation Strategies to Increase Suburban Transit Ridership in the Short Term.” I think that you will find that we addressed all of your comments satisfactorily. We also took the opportunity to refine our statistical analysis, and we reference its results to an onboard survey conducted of Broward County Transit passengers. This additional work shows a more robust statistical analysis supporting the overall conclusion that reducing transit travel times between all pairs of major origins and destinations is the most fruitful path to increasing transit ridership. There are many ways in which public policy can encourage shorter transit times, including the promotion of TODs on both the origins and destinations of trips. Such TOD policies would have the result of shortening walking time, which is an important component of the overall time spent in traveling from an origin to a destination. With the passage of time, if public policy directs most population and employment growth to TODs, urban regions will be more compact than they otherwise would be, and such compactness will increase transit patronage even more. Sincerely yours, Gregory L. Thompson Professor ii Evaluation of Land Use and Transportation Strategies to Increase Suburban Transit Ridership in the Short Term Executive Summary This study seeks to understand the relative efficacy of two classes of policies intended to increase the ridership and productivity of public transit service in Florida. One class of policies seeks to improve transit effectiveness by freezing transit service in the older parts of metropolitan areas (where it is thought that higher densities of population and employment and the presence of pedestrian amenities induce higher levels of transit demand) and directing new population and employment growth to redeveloped areas around transit stops in the older areas. The other class of policies seeks to connect employment and population, wherever it locates, as directly as possible by transit routes. The thrust of transit development of this second category of policies is in the newer rather than older parts of metropolitan areas, because it is in the newer areas where most population and employment growth is located. The study uses two methods, both focused on transit service in Broward County, Florida. The first method, presented in Chapter 4, is statistical and seeks to examine transit ridership between every pair of traffic analysis zones in Broward County in order to understand the importance of variables that might give rise to that ridership. The variables that we used give insight into both hypotheses; the purpose of the statistical analysis is to understand which of the variables are more important. We conducted our analysis with data for 2005, when there were 921 traffic analysis zones in Broward County and over 800,000 pairs of zones. Because of the fact that transit service did not exist between every pair of zones and the further fact that the Census Bureau suppressed data from some zones for confidentiality reasons, we actually analyzed transit ridership between about 550,000 pairs of zones. The statistical analysis developed a relatively weak model for predicting work transit trips between an origin zone and a destination zone, but that model none‐the‐less speaks clearly about variables that increase transit ridership and those that have little impact. In general, the model supports the efficacy of the second set of policies. The most important consideration in attracting transit ridership is to directly connect population and employment. The analysis shows that it does not matter where the population or the employment are located. Reducing travel time from places where people live to places that they want to go, measured by employment, is by far the most important thing policy can do to increase transit ridership. Policy can shorten transit travel time by restructuring routes, by improving headways, by extending coverage, and by increasing speed. It is not important where the employment is located; that located in the CBD does not have a particularly greater draw than that located elsewhere. It is important to serve it all. The conclusions about the ability of TOD developments to increase transit ridership are clouded by the fact that there are no TOD developments in Broward County, and our efforts to identify TAZs with development that is similar to TOD development were not successful. However, our results from the model clearly indicate that shorter walking times to and from transit are highly important for increasing transit ridership. TODs, if designed properly, will reduce walking time to and from transit and thus will increase transit ridership significantly. An implication of this finding is that planning methods that focus on the relationship of developments to stops will be effective if they take into account how well the stops are connected to all destinations in the region. Creating short walking times along attractive paths will boost transit ridership iii if the transit stops to which the paths connect are well‐connected to population and employment throughout the region. Another implication is that because both population and employment are dispersed, planners cannot achieve time reductions by implementing direct routes between every pair of origins and destinations. Planners need to think in terms of networks of routes that depend upon transfers. Ideally routes would be frequent, and if the areas traversed are large, routes would be speedy, as well. Transfer points should be designed for easy movement betwee n routes, and fare structures should facilitate transferring. Running express buses from many neighborhoods to CBDs would be ineffective, because CBDs account for so little of regional employment. However, in larger regions an overlay of a regional grid of limited‐stop routes offering much higher scheduled speeds than local buses, interconnecting all important employment concentrations in a region, is an important component of a transit network that achieves higher ridership. The second method used in this study, presented in Chapter 5, is a case study analysis that comes to similar conclusions to those drawn from the statistical analysis of Chapter 4. The case study compares transit development in Broward County with that in Tarrant County, Texas, where Ft. Worth is located. Both counties are the second counties in their respective metropolitan areas in terms of population and employment. Both counties have similarly sized populations, and both counties have grown at about the same rate over the past several decades. Transit service in both counties connects with relatively recently‐created rail commuter service originating in the dominant county of the respective areas. There are major differences in transit policy between the two counties, however. Broward County has no historic central business district, and the transit system has a county‐wide focus. The route structure is a grid that serves all population and employment concentrations in the county. County residents can get from most parts of the county to most other parts where employment is located. Tarrant County, however, contains the Ft. Worth central business district, and transit service historically developed in Ft. Worth as streetcars focused on that CBD. Transit technology in Ft. Worth now is bus, but the route structure still is largely radial in nature focused on the CBD. There also is a CBD‐focused express bus system super‐imposed on the local routes. Many areas of major employment growth in Tarrant County outside of the CBD remain un‐served by transit, however. The city of Arlington, which contains tens of thousands of jobs, remains the largest urban area in the United States without transit service. So, here we have two transit systems laid out according to two different transit policies. Transit in Broward County attempts to connect most origins to most destinations scattered throughout the county with a grid of routes, requiring many passengers to transfer. Transit in Tarrant County attempts to connect many neighborhoods to the CBD, where large numbers of jobs are located. Both local buses and peak period express buses focus on the Ft. Worth CBD. The idea is to serve one destination well, and the destination that is chosen has well‐developed pedestrian connections to jobs. Which policy is the more effective for attracting transit riders? The case study comparison points to the strategy of connecting all population to all jobs throughout the urban region as being the more effective in stimulating transit ridership. Broward County is an environment where transit is not supposed to work. There is no downtown and employment is scattered. Yet, transit in Broward County carries almost 400 percent more ridership per capita than does transit in Tarrant County, while each bus mile operated in Broward County carries about 35 percent more passengers. In summary, we provide two analyses, one statistical and one a case study comparison. Both analyses point in the same direction. The most effective policies for increasing transit ridership and productivity are those oriented to connecting together population and employment that is decentralized throughout metropolitan regions in Florida.