Temporal Disaggregation of Performance Measures to Manage Uncertainty in Transportation Logistics and Scheduling

Abstract

Transportation planning for highways is informed by performance metrics with aggregated data that can obfuscate the uncertainty of performance conditions across hours, days, and weeks. Recent advances in data collection methods provide disaggregated speed data at a regional level, which can be processed to inform planners and stakeholders of system performance hotspots. Based on the methods of corridor trace analysis (CTA), this paper extended the framework through temporal disaggregation of highway performance metrics, classified as a temporal corridor trace analysis, t-CTA. This approach introduces a temporal weight and temporal value associated with observed performance during discrete periods. The temporal value allows stakeholders to address uncertainty in logistics and scheduling, adjusting the significance of measured performance based on when the adverse conditions are observed. The t-CTA framework provides for analysis of multiple performance criteria across geographic regions and multiple temporal domains. This approach was demonstrated for a limited-access highway and principal arterial road network evaluated across five disparate periods. The availability of probe speed data and accessibility of the t-CTA framework has implications for national planning initiatives that must consider multiple objectives.