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Center Identification Number:  576-06

 

Project Title:  Reassessing passenger Mile Data for Transit Planning and Fund Allocation

 

Principal Investigator:        

 

Xuehao Chu

Phone: 813-974-9831

E-mail: xchu@cutr.usf.edu

 

Institution:                             

 

Center for Urban Transportation Research

University of South Florida

Fax: (813) 974-5168

 

External Project Contact:     

 

Ike Ubaka

Transit Program Manager

Public Transit Office - FDOT

Voice: 850-414-4532

Fax: 850-414-4508

 

I.  Project Objective

 

To document approaches to using passenger miles for transit planning to better serve transit users. This shall be done through the identification of potential approaches and case studies.  The result shall be specific approaches illustrated with examples.  These approaches provide agencies that are not already using them with new ways to plan and improve transit services for their customers.

 

II.  Project Abstract

 

The National Transit Database (NTD) is the system through which the Federal Transit Administration (FTA) collects uniform data needed by the Secretary of Transportation to administer department programs.  The database consists of selected financial and operating data that describe mass transportation characteristics.  Recipients and beneficiaries of Urbanized Area Formula Program grants must submit a NTD report through the life of the grant and/or capital equipment obtained through the grant.  As part of the required NTD reporting, agencies submit data on both unlinked passenger trips and passenger miles as services consumed.  Many transit agencies complain that they have to spend limited resources on coming up with passenger miles data for NTD reporting that have absolutely no use to them.  Some other agencies, however, have found innovative approaches to using passenger miles data for planning their transit services to better serve their customers.  The Jacksonville Transportation Authorityís strategy of establishing Interliners, for example, was developed from using passenger miles to track usage of its fixed route system.  As more and more agencies adopting automated passenger counters, the cost of obtaining reliable passenger miles data declines while the richness of the data increases dramatically.

 

The use of passenger miles has several advantages.  First, data on passenger miles can better reflect transit usage.  As a real example, transit boardings in St Louis increased by 15.0 percent from 1990 to 1995 during which the light rail system started operation, while passenger miles increased by only 3.4 percent during the same period.  As a hypothetical example, consider the relative values of passenger miles per vehicle mile versus boarding per vehicle mile under two scenarios: 1) 20 persons rode a bus for 10 miles; and 2) 20 persons rode the bus for only a block.  The usage by these 20 persons is reflected as 20 passenger miles per vehicle mile under scenario 1 and about 0.5 under scenario 2.  In contrast, their usage is reflected as 2 boardings per vehicle mile under both scenarios.  Second, passenger miles data may be used to measure transit vehicle occupancy or load factor.  Diesel-powered buses would not be environmentally sound relative to automobiles when occupancy or load factor is low.  Third, transitís value is relatively small for short trips by able-bodied persons because these trips can be made on foot without the fixed costs of waiting and access/egress times.  Passenger miles data captures the difference between long and short trips.

 

III.  Task Descriptions

 

Task 1:  Review of Literature and Current Practices

 

This task shall review the literature and current practices on the use of passenger miles data for transit planning.  It shall help identify potential agencies for case studies.  Finally, this task shall identify approaches to using passenger miles data that are not being used in practices.  Passenger miles data are being used by various levels of government agencies.  At the federal level,  

  • The US DOTís Conditions and Performance Report to Congress uses projected passenger miles to estimate transit investment needs nationwide.

  • The US FTA requires new starts projects to show changes in system-wide operating cost per passenger mile in the forecast year as the only measure for operational efficiency.

  • The Federal Section 5307 Urbanized Area Formula Program uses passenger miles data for fixed-route transit services. 

  • The Section 5308 Clean Fuels Formula Grant Program uses passenger miles data for buses.

  • The US DOT now uses growth rates in passenger miles as the performance measure on transit ridership at the national level.

  • The US DOT uses passenger miles as exposure to injury risk for transit users.

At the state level, for example, the ratio of passenger miles to seat miles available is used as a performance measure for transit utilization in FDOTís Mobility Performance Measures Program. At the county level, for example, Fulton County, Georgia uses passenger miles as a performance measure for transit services in its current Comprehensive Transportation Plan.  At the metropolitan level, Metroplan Orlando uses passenger miles per dwelling as a performance measure.  Cleveland is proposing to use passenger miles as a long-term measure of transit performance but to use customer satisfaction as a short-term measure.  At the agency level, BART uses operating expenses per passenger mile and passenger miles per seat mile available as performance measures.  Jacksonville Transportation Authority uses passenger miles as a performance measure for its transit system and the ratio of passenger miles to seat miles available as a productivity measure for individual routes.

 

Task 2:  Data Needs of Transit Planning

 

This task shall review the data needs of transit planning to better serve transit users.  This review shall cover different levels of transit planning, such as strategic planning, short-range planning, service planning, etc.  Not only the type of data but also the level of detail may vary with these planning types.  Data needs also depend on the audience.  There are four players related to public transit in general: users, transit agencies, communities, and funding agencies.  CUTR shall provide the FDOT Project Manager Technical Memo One to document tasks 1 and 2 in an electronic format via e-mail.

 

Task 3:  Roles of Passenger Miles Data

 

This task shall examine the roles that data on passenger miles can play in transit planning in order to improve services for transit users.  This task shall also examine the role of passenger miles data in the planning of passenger transportation other than local transit, such as airlines, intercity bus, and Amtrak.  Potential roles would include system monitoring, peer comparison, and service evaluation.  Data on passenger miles may be used directly as an aggregate value.  Data on passenger miles may be used as ratios with some other variables.  Potential ratios would include passenger miles per seat mile available (i.e., load factor), passenger miles per revenue vehicle mile (occupancy), public subsidy per passenger mile, injuries per passenger mile, etc.  Data on passenger miles may also be used in other ways with the rich data made available with new technologies.  Examples would include the percent of passenger miles under crowded conditions, the percent of passenger miles at certain level of service reliability, etc.  This task shall also examine some of the shortcomings of using passenger miles for transit planning. 

 

Two case studies will be used to document how agencies actually use passenger miles data and the benefits and shortcomings as perceived by these agencies.  It is likely that Jacksonville Transportation Authority would be one of the two case studies.  When feasible, a case study may be conducted on the use of passenger miles data by a passenger airline company.

 

Task 4:  Sources of Passenger Miles Data

 

This task shall review the different potential sources from which data on passenger miles may be derived.  Potential sources include traditional manual methods as well as new automated methods that are made possible with technologies such as automated passenger counters, automatic vehicle location, magnetic fare cards, and smart cards, etc.  Data sources may vary across different approaches to using passenger miles data.  CUTR shall provide the FDOT Project Manager Technical Memo Two to document tasks 3 and 4 in an electronic format via e-mail.

 

Task 5:  Draft Final Report

 

This task shall prepare a draft final report to document the research efforts.  CUTR will e-mail the draft final report with two bonded hard copies to the FDOT Project Manager.

 

Task 6:  Final Report

 

It is expected the FDOT Project Manager will provide his comments on the draft final report within two weeks of receiving the e-mailed document.  After receiving comments from the FDOT Project Manager, CUTR will revise the draft final report accordingly.  In addition to the 30 copies for the Research Office, CUTR will deliver 45 copies of the final report to the FDOT Project Manager.

 

IV.  Project Schedule

 

A project-duration of 15 months is proposed.  The establishment of a working account at CUTR shall start the 15-month project schedule.  CUTR shall not request an extension within sixty (60) days of the scheduled completion date of the project.  November 1, 2003 is the expected start.

 

Tasks/Deliverables

Calendar Months

11

12

1

2

3

4

5

6

7

8

9

10

11

12

1

1:Literature/Practices

T

T

T

T

T

 

 

 

 

 

 

 

 

 

 

2: Data Needs

T

T

T

T

T

 

 

 

 

 

 

 

 

 

 

Technical Memo 1

 

 

 

 

 

D

 

 

 

 

 

 

 

 

 

3: Roles

T

T

T

T

T

T

T

T

T

T

T

 

 

 

 

4: Data Sources

T

T

T

T

T

T

T

T

T

T

T

 

 

 

 

Technical Memo 2

 

 

 

 

 

 

 

 

 

 

 

D

 

 

 

5: Draft Final Report

 

 

 

 

 

 

 

 

 

 

 

T

T

T

 

6. Final Report

 

 

 

 

 

 

 

 

 

 

 

 

 

 

T

Progress Reports

 

 

 

D

 

 

 

D

 

 

 

D

 

 

 

Note:    T = Task efforts;           D = Deliverables

 

V.  Total Project Budget

 

Innovative Approaches to Using Passenger Miles Data for Transit Planning

Budget Categories

State Share

   Institute Director Salary (rate X hours)

$0

   Faculty Salaries (39.56 X 531 hours)

$21,000

   Administrative Staff Salaries (25.00 X 40 hours)

$1,000

   Other Staff Salaries (rate X hours)

$0

   Student Salaries (15.00 X 233 hours)

$3,500

   Staff Benefits

$7,100

Total Salaries and Benefits

$32,600

   Permanent Equipment

$0

   Expendable Equipment and Supplies

$113

   Domestic Travel

$620

   Foreign Travel

$0

   Other Costs

$0

Total Direct Costs

$33,333

   Indirect Costs

$1,667

TOTAL COSTS

$35,000

Note: This budget does not reflect any federal participation. The project team will include faculty, students, and secretarial and other support staff who will work directly on the project and whose costs are reflected in the direct costs of the project as listed above. 

 

VI.  Student Involvement

 

Students will provide assistance in a variety of capacities.

 

VII.  Relationship to Other Research Projects

 

As part of the NCTR program, CUTR is exploring alternative sampling techniques to estimate passenger miles data for reporting to the National Transit Database.

 

A TCRP report (2002), A Guidebook for Developing a Transit Performance-Measurement System, provides examples of performance measures for a transit performance measurement system.

 

A TCRP synthesis report (1995), Bus Route Evaluation Standards, documents performance measures used by individual agencies to set standards for route evaluations. 

 

A US DOT report (1985), Transit Data Collection Design Manual, discusses data needs for a performance monitoring process of transit services.

 

VIII. Technology Transfer Activities/Peer Review

 

The results of this analysis will be provided to the FDOT through a series of quarterly progress reports and a final report.  Copies of the final report will be widely distributed to various agencies, offices, and decision-makers in Florida.

 

IX.  Potential Benefits of the Project

 

When using passenger miles data along with other information appropriately, transit agencies can improve services, have happier customers, and reach higher usage of their services.  The experience at the Jacksonville Transportation Authority is a good example.  As already mentioned earlier, JTA developed its interliners with the use of passenger miles data as its performance measure for transit usage and the ratio of passenger miles to seat miles available for route evaluation.  Interlining gets rid of the need for transferring by customers who used to transfer between the interlined routes.  With little additional operating costs on the part of JTA, services are improved.  Customers are happy.  Participants of a recent user focus group listed the interliners as one of JTAís top three strengths.  Although boarding volumes dropped to some degree, the number of passenger miles increased significantly.  Either existing customers have become more frequent users or new customers have become users or both.    

National Center for Transit Research ∑ at the Center For Urban Transportation Research ∑ University of South Florida ∑ 4202 E. Fowler Ave., CUT100 ∑ Tampa, FL 33620-5375 ∑ (813) 974-3120 ∑ (813) 974-5168 ∑ www.nctr.usf.edu ∑ Comments: webmaster@cutr.eng.usf.edu