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National Transit Demand Response Level of Service

(Center Identification Number: 79060-02-A)

Problem Statement

Demand response transit service is a major source of mobility for elderly and disabled Americans in urban and rural areas. Federal Transit Administration’s (FTA) grant programs under sections 5307, 5310, and 5311 all have components designed to increase the availability of paratransit or demand response service. The National Transit Database (NTD) is a standard reporting system for urban and rural transit providers and can be used to assess transit system performance. However, there is little information in the NTD or elsewhere about the extent of demand response coverage across the country. Also, availability of service data is not uniform for all the agencies and the accuracy of the available service area, service times, etc. are questionable. Therefore, it is challenging to know the gaps in the service coverage and to understand unmet needs. Transit agencies, MPOs, and State DOTs planning for demand response service often lack data on where the greatest needs for additional service coverage are. Therefore, there is a great need to fill the data gaps to the available NTD database to effectively determine the demand response level of service by communicating with transit agencies operating demand response service in the US to assess national demand response coverage.

Also, for the fixed route transit in big cities, national level of service data is being analyzed by the Center for Urban Transportation Research (CUTR) using the national transit network with the effective utilization of general transit feed specification (GTFS) data that was setup by Google making it easy for service evaluation and help improve service planning. GTFS is not being used by demand response transit systems, however. Therefore, there is also a need to have a unique system for national demand response system such that the transit agencies, MPOs, and State DOTs can better understand the national demand response level of coverage and improve the service in locations with limited or no demand response service.

Objectives

Primary Objective

                Develop a method for assessing national demand response level of service.

Secondary Objectives

1)      Summarize the research on transit level of service and demand response level of service.

2)      Determine the data needs for tabulating the demand response level of service for the study framework. Identify the data that is available from the National Transit Database, Rural National Transit Database, and Census data that can be used in the study procedure to determine the demand response level of service. Also identify data that is lacking from the various databases considered to making necessary calculations in obtaining the demand response level of service.

3)      Design the framework of the study for calculating the demand response level of service and understanding the level of service coverage.

4)      Design and develop a GIS map tool for collecting the missing data from NTD and other required data for level of service calculations from the transit agencies operating demand response transit in selected US states.

5)      Calculate the demand response level of service for all the transit agencies in the selected test states and map the level of service to identify the needs for service improvements.

6)      Provide recommendations to construct a demand response level of service GIS map for any US state and ultimately for all US states to understand the needs for improvement in the demand response system.

Research Plan

Task 1: Literature Review

Previous literature and studies on determining demand response coverage, and level of service will be studied in detail with intent to be incorporated into this study.  Further, the role of GTFS data in gauging transit performance will be briefly presented. The GTFS data role in building National Transit Network and in developing national transit level of service will also be briefly summarized from an ongoing project that is being conducted by the Center for Urban Transportation Research. The way GTFS data can be useful in understanding and improving the transit service performance will be differentiated from how the current study identifies the demand response transit service performance.

Roles: NDSU will have lead role in this task with input from USF.

Task 2: Data Needs and Data Availability

Data needs will be studied to effectively determine the level of service for all the transit agencies serving demand response service throughout the nation. Demand response service data are needed for three areas: service area, service frequency, and service eligibility. Existing data on service area, frequency, and eligibility from databases such as NTD and any other appropriate database will be identified.

Existing data in the NTD database is not adequate for effectively determining the demand response level of service. Therefore, additional measures of service area, frequency, and eligibility will be proposed. Service area will be measured for geographic areas smaller than the county level, such as census block groups, census tracts, zip codes, or some other geographic area; service frequency could be measured in terms of number of days per week or month the service is available, hours of service, and scheduling requirements; and service eligibility would identify to whom the service is available. The resulting data need to be in a format so that they can be combined with other data collected by the U.S. Census Bureau to allow transit agencies, MPOs, and State DOTs to plan demand response service. Once data needs and potential variables are identified, methods for collecting these data will be developed.

Roles: NDSU will lead on this task with USF also having a significant role.

Task 3: Design the Framework of the Study

Determine the appropriate study procedure that can be used to find the national demand response level of service based on the data availability in NTD, census data, and additional service data collected by contacting demand response service operating agencies. TCRP Report 100: Transit Capacity and Quality of Service study has described different ways to measure demand response transit performance by passenger’s perspective, economic performance measures, and vehicle-focused performance measures. Level of service for the demand response transit is the most common way for assessing the service performance and availability of a transit agency. Therefore, determining the Level of service for each demand response transit operating agency for its service location would be the most appropriate way to assess the service performance of national demand response transit and therefore determine the national demand response level of coverage. Level of service of a demand response transit agency can be measured on a scale of 1 to 8 where, level of service 1 represents the response time for a ride to arrive is up to half an hour and level of service 8 represents a response time for a ride to arrive is more than 2 weeks, or not able to accommodate the trip.

US census data would be used to identify the geographic locations (categorized by demand response service provider locations) with elderly and disabled population. The identified elderly and disabled population data will be combined with demand response service provider’s level of service values by using a procedure/model to determine the locations with significant elderly and disabled population with limited demand response service.

An Upper Great Plains Transportation Institute study “Personal Mobility in North Dakota: Trends, Gaps and Recommended Enhancements” has developed a three step model to determine the mobility needs index and rank the regions in North Dakota based on available data such as the population of elderly, elementary and high school students, low-income individuals, the disabled, minorities, and individuals in households without vehicles. This methodology is in consideration to help identify the locations with significant population of elderly and disabled and rank them accordingly. This ranking combined with the level of service for a particular region will help identify service requirements if necessary. One more methodology under consideration is to combine the level of service values with the percentage of elderly and disabled population for a particular region and generate the ranking to identify locations that needs service improvements. Although, at this point the way of ranking the locations is not finalized, a decision will be made as the study progress. These proposed methodologies can be effectively used by transit agencies, MPOs, and State DOTs to plan demand response service where needed.

Roles: NDSU will lead this task. USF will provide their contribution with their expertise in census, geographic data, and transit performance evaluation.

Task 4: Develop a GIS Map Tool

A map questionnaire tool is proposed to be developed by the research team to gather some important information for the demand response operating transit agencies such as coverage of demand response service, service frequency, etc.

The questionnaire will be distributed online and consist of a clickable map for agencies to select the areas they serve. Space will also be provided for agencies to clarify how those areas are serviced. For example, they may only provide service to a specific area on Wednesday. This type of information can be submitted as part of the questionnaire.

Providing a user-friendly online map where transit agencies can identify their service area reduces the data reporting burden to these agencies. The map will be divided into geographic areas smaller than the county. Areas such as census tracts, census block groups, zip codes, and others will be considered. The end result from the map questionnaire will be a record from each demand response agency that identifies the geographic areas it serves as well as the service characteristics for each of those geographic areas, such as service times and days. The resulting data can be mapped in GIS and combined with population and demographic data from the U.S. Census.

Roles: NDSU will take a lead in developing the data acquisition tool and test the tool in North Dakota/Minnesota. USF will test and evaluate the data acquisition tool and provide GIS data resources to support the data collection effort of Florida.

Task 5: Test the Proposed Framework

This proposed framework will be demonstrated at a statewide level for one or two states. At least one of these states will include a combination of urban areas (with big cities) and rural areas to study the demand response transit in these locations.

The map questionnaire tool developed in task 4 will be distributed to demand response providers in the demonstration area. A few different data variables and methods for collecting information will be tested. Different versions of the map tool, as well as a non-map tool, will be developed and tested as a means for collecting information. Each tool will be evaluated based on the quality and usefulness of data collected, response rate, and reporting burden for transit providers.

The results for the two states that are proposed to demonstrate the frame work will be generated in an US map with gradation of colors at census block levels to distinguish the demand response level of coverage and to also know the locations of top priority for improving the demand response service.

Roles: NDSU will be responsible for coordinating with the demand response providers in North Dakota/Minnesota to acquire the required data for the study. USF will coordinate with all the Florida demand response providers to input and collect Florida data.

Task 6: Calculate Demand Response Level of Service and Map Results on US Map using GIS

Based on the information gathered from the map questionnaire tool from all the transit agencies for the selected states, transit agency data available from NTD database, and census data, the level of service and level of coverage of demand response transit will be tabulated following the study framework. A US GIS map file with census information will be used to plot the demand response transit level of service values. A procedure/model will be developed to integrate the census data and level of service value to determine the potential locations that needs service improvements for the demand response service.

Roles: NDSU will lead this task with input from USF.

Task 7: Provide Recommendations for Using the Framework Generated

Based on the results from the demonstration project, the study will provide recommendation regarding data needs and an appropriate method for collecting those data. The recommended framework will provide useful information to transit agencies, MPOs, and state DOTs for identifying deficiencies in service while minimizing reporting burden for transit providers.

The end result from this study will be a GIS map to visualize the census data (elderly and disabled population information) combined with the level of service of the demand response transit operating agency to better understand if there is a need for improving the service to meet the needs of paratransit users.

Roles: NDSU will take a lead role in this task and USF will provide recommendations for the Florida part of the study.

Task 8: Prepare Final Report

A full report detailing the research effort will be produced, as well as an executive summary and slide presentation. The research team will also prepare a video demonstration for the transit agencies, MPOs, and State DOTs officials to better understand the procedure that is developed in this study to identify the potential locations in need of demand response service improvements.

Roles: NDSU will take the lead in preparing the final report. USF will provide input for providing editorial comments for this task.

Project Schedule

February 2014 to July 2015

Project Budget

Total Project Cost     $112,513.00

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Sponsors

  • Florida Department of Transportation
  • US Department of Transportation

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National Center for Transit Research c/o Center for Urban Transportation Research 4202 E. Fowler Ave., CUT100 Tampa, FL 33620-5375