Assessment and Refinement of Real-Time Travel Time Algorithms for Use in Practice

Kristin Tufte, Portland State University

Summary:

The Federal Highway Administration (FHWA) has set a high priority on the use of existing dynamic message signs (DMS) to provide travel time estimates to the public. The Oregon Department of Transportation (ODOT) currently has three DMS in the Portland metropolitan area configured to display travel time information. In the near future, ODOT would like to make travel time estimates available on additional DMS, over the Internet on tripcheck.com and via 511. Travel time estimates are valuable to the traveling public; however, the estimates must be accurate to be useful. The FHWA indicates that 90% accuracy is ideal and suggests a minimum accuracy of 80%. Thus, in order to display travel time estimates, it is essential to understand the accuracy of the estimates.
The purpose of this study is to extend prior travel time research conducted at Portland State University with additional data collection and analysis to provide statistical confidence in travel time estimates and to determine the best travel time estimation approach for ODOT. Ground truth data in the form of probe vehicle runs will be collected and travel time estimates will be evaluated using that data. Several travel time estimation algorithms will be evaluated and modifications to existing algorithms will be proposed. In addition, this project will provide analysis to help understand the reliability and performance of the algorithms under various conditions (free-flow, congestion, incidents). A methodology will be developed for determining if travel time estimates fall within an acceptable accuracy limits. At the conclusion of the project, it is desired that a methodology can be recommended that will provide accurate measures of travel time for use with DMS, the Internet and 511 applications.

Project Details

Project Type:
Research
Project Status:
Completed
End Date:
June 30,2008
UTC Grant Cycle:
OTREC 2007
UTC Funding:
$23,062