01711258

Component

https://doi.org/10.1177/0361198119850471

State transportation agencies working to alleviate congestion need to design appropriate and effective congestion mitigation strategies for each sub-region and corridor, but solutions to solve recurring and nonrecurring congestions problems differ. Past research shows large variations in the proportion of delay attributable to recurring and nonrecurring sources and cannot be readily used by other states to develop practical solutions. An affordable, automated, and sound delay estimation methodology that breaks down congestion cause components could bring some insights to this problem. This paper seeks to use traffic and event data elements that are commonly available to Departments of Transportation to develop a methodology that can be broadly adopted by states to estimate the magnitude of recurring and nonrecurring congestion. The methodology uses data commonly available to public agencies, and does not require additional data-collection efforts or periodic re-calibration processes. A case study with the Virginia Interstate network, covering over 2,200 directional miles, is summarized in this paper. The results show that nonrecurring congestion contributed to around 24% of total delays. The result also clearly shows that recurring congestion contributed to most of the delays in urban districts, whereas nonrecurring congestion contributed to most of the delays in more rural districts. It can, therefore, be concluded that the use of a static statewide congestion profile is not suitable for individual district needs.

The Standing Committee on Statewide Transportation Data and Information Systems (ABJ20) peer-reviewed this paper (19-05711). © National Academy of Sciences: Transportation Research Board 2019.

19-05711

English

2019

Transportation Research Record: Journal of the Transportation Research Board

Digital/other

References

Case studies; Congestion management systems; Methodology; Traffic congestion; Traffic forecasting

Virginia

Highways; Operations and Traffic Management; Planning and Forecasting

TRIS, TRB, ATRI

Apr 26 2019 2:44PM

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