A hazard-based model to derive travel time under congested conditions

Ninad Gore, Shriniwas Arkatkar, Gaurang Joshi and Srinivas S. Pulugurtha

Transport Policy, 2023, vol. 138, issue C, 1-16

Abstract: Increasing congestion levels and their elusive impact warrants the development of congestion mitigation strategies. Quantifying congestion and analyzing the spatiotemporal variations is imperative to achieve this target. Travel time is being explored as a measure of congestion with the advent of Intelligent Transportation Systems (ITS) and the deployment of related technologies. Researchers identified congested conditions when the average travel time exceeds 1.33 or 1.66 times free-flow travel time (FFTT). It is well known that travel time under congested conditions (Tc) is more sensitive to land use, road geometry, and traffic control characteristics than the FFTT. Therefore, the extension of FFTT to derive Tc may not be appropriate. This study focuses on developing a hazard-based model to derive Tc. Travel time is modeled using a parametric accelerated failure time (AFT) model. The applicability of the proposed methodology is justified using empirical and simulated datasets. The Tc derived from the AFT model is close to the travel time for the level of service (LOS F). Based on the Tc, a new measure of congestion, termed congestion index (CI), is proposed. The proposed index can quantify the frequency and intensity of congestion on a link or network. The traffic states identified based on CI were mapped on the fundamental diagram (FD) and the macroscopic fundamental diagram (MFD). It was concluded that if travel times are uncertain and unstable under low-density conditions, then the ascending leg of the FD or MFD can be marked congested. Uncertain and unstable travel times indicate that traffic flow is unstable, and therefore, it can be concluded that traffic instabilities significantly affect congestion.

Keywords: Travel time; Travel time under congested conditions (Tc); Accelerated failure model (AFT); Congestion index (CI) (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1016/j.tranpol.2023.05.003

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