Abstract
Performance measures allow planners and engineers to monitor and evaluate transportation facilities or projects and to justify the allocation of funds among alternative transportation improvement options. To capture the impact of corridor congestion on freight vehicles, new tools and methodologies are developed to analyze data from commercial vehicles and produce performance measures such as travel time, speed, and travel time reliability. Because long freight corridors comprise segments with varying reliability characteristics, the objective was to develop a programming logic that would use available truck Global Positioning System data to (a) identify natural segments or regions in a corridor between urban centers, Interstate junctions, or rural areas and (b) estimate corridorwide impact of travel time unreliability. The case study presented investigates the I-5 corridor in Oregon. The research applies statistical techniques to compute vehicle travel time and reliability for freight movements within each segment. The proposed methodology has been used successfully to identify distinct segments and characteristics of travel time reliability in freight corridors. Travel time information was used to compute cost effects of delays within rural and urban areas along the I-5 corridor. The research presents an advance in the processing and aggregation of Global Positioning System truck data to produce succinct yet informative performance measures and segments.
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