The National Academies

TCRP B-31 [Completed]

Guidebook for Measuring, Assessing, and Improving Performance of Demand-Response Transportation

  Project Data
Funds: $250,000
Research Agency: KFH Group
Principal Investigator: Elizabeth Ellis
Effective Date: 9/8/2005
Completion Date: 3/8/2007

Background. Demand-response transportation (DRT) systems are under increasing pressure to improve performance because of increased demand for service and financial constraints. Improving DRT performance requires understanding the characteristics of DRT services and the factors that affect performance. To identify opportunities for improvement, DRT systems need better data and methods to measure and assess performance consistently and systematically.

Assessing and improving performance of DRT systems is complicated because there are many types of DRT systems, and the performance of DRT systems is influenced by many factors--both controllable and uncontrollable. Controllable factors are those within the DRT operator's domain, such as service policies (e.g., pickup time windows, maximum allowed onboard time, and curb-to-curb versus door-to-door service); fleet mix (e.g., vehicle capacity, vehicle design, and fleet size); trip-scheduling method (i.e., the extent to which it produces viable and efficient vehicle routes and schedules); dispatch control method (e.g., re-scheduling late trips and making use of capacity in the event of late cancellations and passenger no-shows); and driver and dispatcher training. Uncontrollable factors include physical and geographical factors (e.g., size of service area and geographic barriers, such as bridges); service type (e.g., ADA complementary paratransit service versus other demand-response services); and passenger demand.

The existence of diverse types of DRT systems affected by different controllable and uncontrollable factors makes it difficult to compare the performance of different DRT systems and identify opportunities for improvement. For example, a DRT system with low ridership could be operating in an area where few passengers are eligible to use a service. Conversely, low ridership could be caused by poor service scheduling that does not maximize vehicle utilization and ride-sharing.

DRT systems need reliable data and useful measures that allow for meaningful assessments of performance over time and across DRT systems. Historically, data collection and reporting have not been rigorous among DRT systems. Data on performance have not been consistently defined and methods for collecting data have not been consistently or rigorously applied. Similarly, performance measures have not been widely or consistently used as an element of performance assessments. For example, service effectiveness for DRT, a measure of utilization or productivity, can be defined as the number of passenger-trips per vehicle-hour of operation. However, the exact definitions of the terms "passenger-trips" and "vehicle-hours" vary across systems.

Consequently, research is needed to provide guidance on the types of data and measures that are needed to allow for meaningful assessments of and improvements to DRT performance.

Objective. The objective of this research is to develop a guidebook for measuring, assessing, and improving the performance of demand-response transportation (DRT) systems. The methods presented in the guidebook should address the diversity of DRT services, service areas, and passengers. The guidebook should identify the important controllable factors that affect DRT performance and should include methods based on reliable data and meaningful measures that allow relevant assessments of performance over time and across DRT systems.

Status. The project is completed and the report has been published as
TCRP Report 124.   A second phase to this project (TCRP B-31A, Guidebook for Measuring, Assessing, and Improving Demand Response Transportation in Rural Areas) focusing on rural transit was funded by the TOPS Committee in October 2006 and completed in 2009.  This project produced TCRP Report 136.

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