Multicriteria Freeway Performance Measures for Trucking in Congested Corridors

Abstract

Research was undertaken to develop multicriteria tools for measuring and analyzing the impact of recurring and nonrecurring congestion on freight. Unlike previous studies, this work used several distinct data sources to analyze the effects of congestion on I-5 in the Portland, Oregon, metropolitan area: Global Positioning System data from commercial trucks, Oregon Department of Transportation corridor travel time loop data, and incident data. A new methodology and algorithms combine these data sources and estimate the impact of recurrent and nonrecurrent congestion on reliability and delays, costs, and emissions of freight movements. The results suggest that traditional traffic sensor data tend to underestimate the impact of congestion on travel times and variability of commercial vehicles. Congestion is detrimental not only for carriers’ and shippers’ costs but also for the planet because of increases in greenhouse gas emissions and for the local community because of increases in oxides of nitrogen, particulate matter, and other harmful pollutants. The developed methodology can provide useful freight operation and performance data for the freight community, transportation decision makers, and other transportation stakeholders.