University of New Orleans ScholarWorks@UNO University of New Orleans Theses and Dissertations and Theses Dissertations Fall 12-2016 Measuring Access to Employment to Guide and Evaluate Public Transit Service Planning in New Orleans Kevin Harrison University of New Orleans, kevinharrison@gmail.com Follow this and additional works at: https://scholarworks.edu/td Part of the Transportation Engineering Commons, and the Urban, Community and Regional Planning Commons Recommended Citation Harrison, Kevin, "Measuring Access to Employment to Guide and Evaluate Public Transit Service Planning in New Orleans" (2016). University of New Orleans Theses and Dissertations.edu/td/2256 This Thesis is protected by copyright and/or related rights. It has been brought to you by ScholarWorks@UNO with permission from the rights-holder(s). You are free to use this Thesis in any way that is permitted by the copyright and related rights legislation that applies to your use.
For other uses you need to obtain permission from the rights- holder(s) directly, unless additional rights are indicated by a Creative Commons license in the record and/or on the work itself. This Thesis has been accepted for inclusion in University of New Orleans Theses and Dissertations by an authorized administrator of ScholarWorks@UNO. For more information, please contact scholarworks@uno. Measuring Access to Employment to Guide and Evaluate Public Transit Service Planning in New Orleans A Thesis Submitted to the Graduate Faculty of the University of New Orleans In partial fulfillment of the Requirements for the degree of Master of Urban and Regional Planning Transportation Planning By Kevin G.
Saint Bonaventure University, 2005 December 2016 Acknowledgements My thesis committee was composed of Jane Brooks, Sandip Chakrabarti, and Marla Nelson and they provided thoughtful feedback on my research that played an essential role in developing my thesis. I would like to thank Marla Nelson, the committee chair, in particular for continually pushing me to finish my thesis over the last four years. Zach De Luna and Ed O’Brien helped me to understand the basics of programming and computer science that were necessary to work with OpenTripPlanner, Python, and R. Steven Farber provided helpful tips and infectious enthusiasm at the GIS in Transit Conference in Fall 2015.
Laurent Grégoire helped me troubleshoot OpenTripPlanner. Rafael Henrique Moraes Pereira provided 99.9% of the python script that I used to run my analysis. I would also like to thank friends and family that have patiently endured my endless ramblings about measuring access to destinations on public transit over the last few years. Keywords: Transportation; Public Transportation; OpenTripPlanner ii Table of Contents Table of Figures.
v List of Tables. 4 2 Accessibility in Public Transportation .1 Components of Accessibility.2 Methods for quantifying access .1 Cumulative Opportunity Metrics .2 Gravity-based Metrics .3 Utility-based Metrics .3 Resources for Accessibility Data .1 EPA Smart Location Database .2 University of Minnesota Accessibility Observatory .3 Center for Neighborhood Technology AllTransit .4 Accessibility in Planning.1 Accessibility in Land-Use Planning .2 Accessibility in Transit Service Planning. 23 3 Research Design and Methodology .2 Study Area Geography .4 Trip Planning Technology. 37 4 Results and Analysis.
Can a simple accessibility metric be used to evaluate transit service changes?. How can accessibility analysis be used to assist in developing schedules during routine transit service changes?. Can accessibility analysis be used to measure progress towards the goals of public transit in a community?. 56 Appendix B – Python Script.
59 iv Table of Figures Figure 1: Example of isochrones for cumulative opportunities metric. 12 Figure 2: Gravity metric example. 13 Figure 3: Smart Location Database Transit Tool. 16 Figure 4: University of Minnesota Accessibility Observatory's Access Across America.
18 Figure 5: Center for Neighborhood Technology's AllTransit. 19 Figure 6: Screenshot from birminghamhousingstudy.com shows the number of construction jobs in accessible in 30 minutes. 22 Figure 7: Ceder offers a number of ways to measure connectivity. This example closely resembles some elements of general accessibility.
25 Figure 8: Example from World Bank report on new transit alignment: Employment catchment areas for 60-minute commute trips from a selected location in Ate District. 26 Figure 9: " Illustration of the travel time cube and its atomic vectors. The axes represent origins (𝒊), destinations (𝒋), and minutes of the day (𝒎). Each location in this three dimensional matrix contains a shortest path travel time from 𝒊 to 𝒋 at time 𝒎.
28 Figure 10: Example of weighted centroids within study area. 32 Figure 11: The orange line represents the percentage of all commuters that are leaving home to go to work during 10-minute-long periods. The blue line indicates the average number of jobs that are accessible on public transportation and walking by time of day. 36 Figure 12: Average access to jobs under 2015 and 2016 service levels for Orleans Parish residents.
40 Figure 13: Average percent of study area jobs accessible on transit and walking between 7 AM and 9 AM. 42 Figure 14: Average percent of study area jobs accessible on transit and walking over 24 hours. 43 v Figure 15: Illustrates the percent of jobs accessible at “Peak” minus the percent of jobs accessible “All Day. 44 Figure 16: Average access to jobs under 2015 and 2016 service levels for residents of CBG 220710006031.
45 Figure 17: Percent change in the number of jobs accessible in the number of jobs accessible from 2015 to 2016. Pink asterisk indicates the weighted centroid for CBG 220710006031 in the Behrman neighborhood. 46 vi List of Tables Table 1: Time leaving home to go to work: Orleans Parish workers over 16 who did not work at home. 31 Table 2: Brief description of accessibility metrics.
38 Table 3: Impact of service level Changes on job accessibility for Orleans Parish residents. 39 Table 4: The distribution of jobs accessible from CBGs based on the All Day metric by decile. 41 Table 5: Impact of service level changes on job accessibility for residents of CBG 220710006031. 45 vii Abstract New software and technology is making it easier than ever before for public transportation planners to evaluate how quickly residents can reach jobs and other destinations.
Because in the past it was difficult to measure access to opportunities, these concepts remained primarily in the theoretical and academic realms of research. This thesis reviews methods that could be used to evaluate routine bus service improvements and performs a comparative analysis of different methods in the context of New Orleans. There are many different variables in how the analysis could be performed, but this thesis focuses on the role that time of day plays in analyzing service changes. The results show that accessibility can be a very useful metric to evaluate the effectiveness of transit service changes.
It goes on to explore techniques that could assist transit planners and schedulers to identify service gaps and prioritize service changes.1 Background It’s easy to answer the question of whether an individual has access to broadband internet, natural gas lines, the electrical grid, etc. and sometimes there is an inclination to regard access to public transportation in the same terms, perhaps by asking if there is a bus stop within a quarter of a mile. Utilities and public transportation are often both illustrated by drawing lines on a map, but we know that a particular transit stop may connect to transit line that comes frequently or infrequently, travels quickly or slowly, and goes to destinations that are close or far away. These variables and many others represent the mobility that is provided by public transportation service.
Mobility refers to one's ability to move about freely and is often measured by speed, travel time, or distance (Hanson, 2004). Unlike utilities that provide a standard level of quality to everyone that’s connected, the mobility that is offered by access to transit can vary tremendously. When planners wish to evaluate the effectiveness and usefulness of public transportation, it is therefore reasonable that planners should not only measure the distance to a transit stop or even the mobility of the connecting transit line. Importantly, planners should also measure how transit provides access to destinations and opportunities.
Definitions of access have been viewed differently over the years and many academics have created their own definitions. “These include such well-known definitions as ‘other potential of opportunities for interaction’ (Hansen, 1959), or ‘the ease with which any land-use activity can be reached from a location using a particular transport system’ (Dalvi and Martin, 1976), ‘Other freedom of individuals to decide whether or not to participate in different activities’ (Burns, 1979) and ‘Other benefits provided by a transportation/land-use system’ (Ben-Akiva and Lerman, 1979)” (Geurs et al.” Defining accessibility is growing in importance today because technological advances and improvements in data availability have made it much easier to perform accessibility analysis. As this capability moves into the hands of more planners and city officials, it will become increasingly important to understand the best ways to interpret the data appropriately. A great deal of the work being done in this field is in the theoretical or academic realm (Tomer et., 2016(b)), and it is often geared toward informing communities how their transit is working at a fixed point in time.
This may be adequate for planning efforts related to land use and long-term infrastructure projects, but more research is needed to determine how accessibility metrics can be used to assist in planning and scheduling for transit agencies. Politicians and community stakeholders have a strong desire to improve access, in particular access to employment. The mayor of New Orleans, Mitchell Landrieu, recently expressed that sentiment in his State of the City address. After discussing a variety of initiatives to create more employment opportunities in the city, Mayor Landrieu stated, “And getting people to and from these jobs is really important.
That’s why we’ve announced a major expansion of public transit, with more overnight RTA service, more buses on the busiest routes, and a new airport line. Plus, this fall a new streetcar along Rampart Street and St. Claude Avenue will be done” (Landrieu, 2016, p. Clearly, city officials in New Orleans see access to jobs as a key reason for investing in public transit and if the city is going to improve access, it will be important to define it appropriately.2 Research Questions This thesis examines different methodologies for measuring job access via public transportation and investigates how accessibility measures can be used to evaluate transit service changes in New Orleans.
In particular transit service varies greatly over the course of the day and this thesis will explore how those variations can be included in analysis. The general goal of the thesis is to see how accessibility analysis can be used on a routine basis to inform decision makers at the higher levels of government and also by transit planning and scheduling staff to perform a more detailed analysis. Specifically, this thesis investigates three questions: 1. Can a simple accessibility metric be used to evaluate transit service changes? One potential function of an accessibility metric would be to provide a simple way to demonstrate the impact of transit service changes to policymakers.
For example if the RTA board is evaluating a service change that has been brought forward by the planning department, it would be beneficial for them to have a single figure that could be used to evaluate the effectiveness of the service change. For this question, it will be essential to evaluate different summary metrics for job access in the city. Different organizations have recently advanced such metrics and they will be discussed in more detail in section 2. This question asks if there is a consolidated metric that goes beyond what has been provided in the past to offer a comprehensive evaluation of service improvements over 24 hours in a single number.
How can accessibility analysis be used to assist in developing schedules during routine transit service changes? This question asks how planners and transit agency staff members can use accessibility metrics as part of the iterative process of developing transit schedules.