Travel time variability: A review of theoretical and empirical issues

By Robert B. Noland, John W. Polak. 2002

513 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Transportation

View Paper: https://www.semanticscholar.org/paper/109c26d5194366e9aabf8a9ad7ff3aca72f04c64

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Citations in the corpus

Modelling network travel time reliability under stochastic demand (2005, background): “…framework, the impact on the typical route choice pattern (Mirchandani & Soroush, 1987; Lo & Tung, 2000; Yin & Ieda 2001; Gordon et al, 2001; Liu et al, 2002; Watling, 2002a), or on other responses such as departure time choice (Uchida & Iida, 1993; Noland et al, 1998; Noland & Polak, 2002).”
Comparison of Morning and Evening Commutes in the Vickrey Bottleneck Model (2002, background): “tion (1, 2, 14) is mixed and does not provide a clear indication on”
Temporal and weather related variation patterns of urban travel time: Considerations and caveats for value of travel time, value of variability, and mode choice studies (2014, background): “For a comprehensive review of VOT and VOR studies and the theoretical background, the readers are referred to Noland and Polak (2002) for an early review, Carrion and Levinson (2012) and Li et al. (2010) for a more recent review of the research area.”
Travel through time: the story of research on travel time reliability (2013, background): “• Traveller information systems including reliability aspects – Al-Deek and Emam (2006b), Bell (2009), Guo, Rahka, and Park (2010), Kaparias, Bell, and Belzner (2008), Noland (1997), Noland and Polak (2002), Rakha et al. (2006), Sohn and Kim (2009), Uno et al. (2009).”
Compound Gamma representation for modeling travel time variability in a traffic network (2015, background): “Travel time variability can be defined at varying levels from different perspectives, namely, dayto-day variability, within-day or period-to-period variability and vehicle-to-vehicle variability (Noland and Polak, 2002; Yildirimoglu et al., 2013).”
Finding the most reliable path with and without link travel time correlation: A Lagrangian substitution based approach (2011, methodology): “27 as suggested in the travel time reliability study by Noland et al. (1998), and β =4 as a comparatively large value for testing purposes. The travel time reliability coefficient represents how much travel time reliability (in terms of standard deviation) the trip-maker is willing to trade for unit”
Passenger Perspectives in Railway Timetabling: A Literature Review (2016, background): “Noland and Polak (2002) measured the importance of reliability relative to travel time by defining a reliability ratio RR: RR = b a ln 1+ g b ( ) , (11) where α is a parameter associated with in-vehicle time, β relates to Schedule Delay Early (SDE) and γ to Schedule Delay Early (SDL).”
Ride On! Mobility Business Models for the Sharing Economy (2014, background): ““Shared Mobility” Business Models for Sustainability As cities continue to grow in population and land use, increasing pressure is being placed on the reliability of urban transportation systems (Noland & Polak, 2002).”