01506631

Component

This paper proposes a compound probability distribution approach for capturing both vehicle-to-vehicle and day-to-day variability in modeling travel time reliability in a network. Starting from the observation that standard deviation and mean of distance-normalized travel time in a network are highly positively correlated and their relationship is well characterized by a linear function, this study assumes multiplicative error structures to describe data with such characteristics and derives a compound distribution to model travel delay per unit distance as a surrogate for travel time. The proposed Gamma-Gamma model arises when (within-day) vehicle-to-vehicle travel delay per unit distance is distributed according to a Gamma distribution, with mean that itself fluctuates from day to day following another Gamma distribution. The study calibrates the model parameters and validates the underlying assumptions using simulated vehicle trajectory data. The Gamma-Gamma distribution shows good fits to travel delay observations when compared to the (simple) Gamma and Log-normal distributions. The main advantage of the Gamma-Gamma model is its ability to recognize different variability dimensions reflected in travel time data, and a clear physical meaning of its parameters in connection with vehicle-to-vehicle and day-to-day variability. As such, the model provides a systematic way of quantifying, comparing and assessing different types of variability, which is important in understanding travel time characteristics and evaluating various transportation measures that affect reliability.

This paper was sponsored by TRB committee AHB45-1 Traffic Flow Theory and Characteristics Special Paper Review.

01503729

14-1616

English

23p

2014

Transportation Research Board 93rd Annual Meeting

Digital/other

Figures (4) ; Maps (1) ; References (42) ; Tables (2)

Gamma distributions; Mathematical models; Probability; Traffic delays; Traffic flow; Traffic simulation; Travel time

Data and Information Technology; Highways; Operations and Traffic Management; I72: Traffic and Transport Planning

Transportation Research Board Annual Meeting 2014 Paper #14-1616

TRIS, TRB, ATRI

Jan 27 2014 2:35PM