Estimating a Route Travel Time Distribution Function With Segment Correlations Using Segment-Level Travel Time Data Only: A Moment-Based Method

Abstract

Travel time reliability is a major factor affecting travelers’ route and mode choice behaviors, which is an important aspect of intelligent transportation systems. The calculation of travel time reliability measures is founded on the travel time distribution function. In practice, directly fitting the route-level travel time distribution function using complete route-level travel time data is challenging. As an alternative to route-level travel time data, segment-level travel time data are more abundant and easier to obtain. However, existing estimation methods of route travel time distribution function either neglect travel time correlation among segments, or rely on historical route-level data, or assume a single distribution type for all segments or routes. To address these issues, this paper proposes a moment-based method of estimating the route travel time distribution function that uses only segment-level travel time data. The proposed method estimates the correlation coefficients of segment travel times using the Rearrangement Inequality. Then, the four moments of route travel time are analytically derived. By further employing the corrected Cornish-Fisher expansion, the proposed method ultimately provides an analytical expression for the route travel time distribution function without assuming the distribution functions of segments or routes. The accuracy of the method is examined using data from a license plate recognition system on an expressway in Shenzhen and taxis GPS in Beijing. The proposed method enables a precise calculation of route travel time reliability in road networks that is quite important to travelers’ behavioral decisions and managers’ operational decisions.

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