Latest revision as of 13:11, 21 January 2021

Abstract

Basic reliability issues are addressed in this study, which is not concerned with average travel times, but rather ways of describing travel times that reflect the uncertainty in the amount of time required to travel between two points. Some of the uncertainty is systematic, such as the normal ebb and flow of traffic within the course of a work day or season of the year. Congestion associated with this systematic uncertainty is called recurrent. Congestion due to unpredictable or unexpected events is called nonrecurrent. If every travel time observed over a highway section for a year is plotted, a distribution of travel time is obtained. This plotted distribution is the picture of travel time variability. Such distributions are the focus of this research, especially the degree to which recurring and nonrecurring congestion influence the nature of the distribution. This research shows how to derive performance measures from such distributions and recommends a set for use by managers, planners, and systems operators. The research reexamines the composition of the congestion puzzle in terms of the fractions attributable to recurrent and various sources of nonrecurrent congestion. The project team used before-and-after studies to determine the effectiveness of different types of actions, both operational and capacity improvements, in improving reliability. This study also examined the effect of the downturn of the economy on travel time reliability. Finally, this research resulted in two types of models that can be used to estimate or predict travel time reliability. These models have broad applicability to planning, programming, and systems management and operations.

Original document

The different versions of the original document can be found in:

• http://dx.doi.org/10.17226/22806

• https://ntlrepository.blob.core.windows.net/lib/61000/61900/61950/Project_L03_Final_Report.pdf

• https://rosap.ntl.bts.gov/view/dot/3605,

https://trid.trb.org/view.aspx?id=1226380,

https://academic.microsoft.com/#/detail/611104584