Valuing travel time variability: Characteristics of the travel time distribution on an urban road

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The Path Inference Filter: Model-Based Low-Latency Map Matching of Probe Vehicle Data (2011, background): “, 2006), while other studies have found more skewed distributions to provide better fit (e.g., Uno et al., 2008; Fosgerau and Fukuda, 2012).”
Compound Gamma representation for modeling travel time variability in a traffic network (2015, methodology): “Data points are connected in the order of their succession in time to examine successive changes in the mean and SD, where hysteresis loops are observed as in the literature (Fosgerau, 2010; Fosgerau and Fukuda, 2012; Gayah et al., 2013; Yildirimoglu et al., 2013).”
Travel through time: the story of research on travel time reliability (2013, background): “Fosgerau and Fukuda (2012) suggested the ‘stable’ distribution as a viable statistical distribution able to represent the observed skew in the travel time variability data.”
Analytic Relationships between Travel Time Reliability Measures (2011, background): “A recent finding about the characteristics of travel time distributions was contributed by Fosgerau and Fukuda: a stable distribution can fit standardized travel times (travel times minus the mean, normalized by the standard deviation) well (24).”