New travel time reliability methodology for urban arterial corridors

Ernest O.A. Tufuor, Laurence R. Rilett

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Scopus citations

Abstract

The need for reliable performance measures of urban arterial corridors is increasing because of the rise in traffic congestion and the high value of users’ travel time. Consequently, travel time reliability (TTR), which attempts to capture the day-to-day variability in travel times, has recently received considerable research interest. The basis of all TTR metrics is the underlying travel time distribution (TTD) along the given link or corridor. Estimating and forecasting arterial corridor TTDs for TTR analysis is the focus of this paper. This paper proposes a TTR methodology that addresses some of the limitations of the current U.S. state-of-the-art methodology which was published in the 6th edition of the Highway Capacity Manual (HCM6). Specifically, HCM6 can only estimate average TTD and not the population TTD. However, the population TTD is needed for accurate trip decision-making by individual drivers and logistics companies. In addition, HCM6 cannot be used to analyze the effect of new technologies, such as connected and automated vehicles, nor can it be used easily for long corridors or networks. The proposed TTR methodology, which is traffic-microsimulation based, was applied on a 1.16 mi arterial testbed in Lincoln, Nebraska, U.S. It was shown that the proposed TTR methodology, when calibrated, could replicate the empirical population TTD at a 5% significance level. The population TTD could also be transformed into an average TTD that also replicated the corresponding empirical average TTD at a 5% significance level.

Original languageEnglish (US)
Title of host publicationTransportation Research Record
PublisherSAGE Publications Ltd
Pages1106-1117
Number of pages12
Volume2675
Edition9
DOIs
StatePublished - 2021

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Mechanical Engineering

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