This research focuses on the development of multi-criteria tools for measuring and analyzing the impacts of recurring and non-recurring congestion on freight. Unlike previous studies, this work employs several distinct data sources to analyze the impacts of congestion on interstate 5 (I-5) in the Portland Metropolitan Area: global positioning system (GPS) data from commercial trucks, Oregon DOT corridor travel time loop data and incident data. A new methodology and algorithms are developed to combine these data sources and to estimate the impacts of recurrent and non-recurrent congestion on freight movements’ reliability and delays, costs, and emissions. The results suggest that traditional traffic sensor data tend to underestimate the impacts of congestion on commercial vehicles travel times and variability. This research shows that congestion is not only detrimental for carriers and shippers costs but also for the planet due to increases in greenhouse gas emissions, and for the local community due to increases in oxides of nitrogen, particulate matter, and other harmful pollutants. The methodology developed throughout this work has the potential to provide useful freight operation and performance data for the freight community, transportation decision makers, and other transportation stakeholders.
The different versions of the original document can be found in: