Abstract:

Analyzing and visualizing traffic stream data in order to better understand traffic behavior, safety concerns, and capacity needs is a need of the hour. Due to the insufficient interaction between old-fashioned traffic congestion and incident data analysis tools, it is essential to find contemporary visualization techniques to identify traffic problems using historical or real-time data [1]. Large streams of data available today make it possible to manage and operate vehicles based on their observable characteristics such as length, occupancy, or speed. Understanding this freight behavior can reduce traffic congestion, air pollution, and observe trends that will be useful for future policy. Due to the fact that heavy vehicle characteristics are different from regular-sized vehicles, obtaining traffic stream data from inductive loop detectors which offer length and speed-based variables can help us to distinguish these vehicles from their smaller sized counterparts. Truck-specific visualization tools can give some alternative ideas to public entities or private companies based on their loading-unloading times, and better understand the needs for their seemless mobility. The current study collects 20-second interval data, which include vehicle length and average speed, analyzes trends, visualizes movement and interprets the traffic phenomenon in terms of heavy vehicle volume/percentage and average vehicle speeds observed in the traffic stream. The Portland-Oregon Regional Transportation Archive (PORTAL), a mobility data portal that collects traffic data using more than 600 loop detectors, is used to collect the data used for this study. Even though PORTAL also offers limited visualization tools based on the collected data, high level insights focusing on urban freight movement at a granular level are not available to better inform freight stakeholders, and future policy. The main goal of this study is to offer a new visualization technique that shows the volumes and speeds of freight-purpose vehicles within a 5-minute interval. Interstate-5 (I-5) was chosen as the study corridor due to its important role in the Canada-Mexico corridor. Moreover, the current location (under the Portland-Vancouver region) is of importance considering the major freight generators around the chosen route. Results show the merit in combining heavy vehicle volumes, their shares, and average speeds within 5-minute intervals to capture instantaneous differences in these parameters. The results of this study and the techniques employed here can be used across cities, and regions to better understand and visualize freight movement dynamics across major corridors.