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The objectives of this research were to retrospectively study the feasibility for using truck transponder data to produce freight corridor performance measures (travel times) and real-time traveler information. To support this analysis, weigh-in-motion (WIM) data from each of the 22 stations in Oregon were assembled, processed, and uploaded in the WIM data archive which is housed under the Portland Transportation Archive Listing (PORTAL) umbrella at Portland State University’s Intelligent Transportation Systems Lab. Nearly 42,000,000 truck records were successfully uploaded to the archive dating back to July 2005. Two separate algorithms necessary for this research were scripted, tested, and validated. The closest stations are 38.3 miles apart; the most separated are 258 miles apart. The first algorithm matched transponders of all vehicles in a time window between the upstream and downstream stations. The second algorithm filtered these matches for through trucks. The filter was validated by comparing estimated travel times during a winter weather-induced delay. The analysis showed that corridor-level travel times for trucks for 2007 and 2008 could be generated from the archived data. To explore the feasibility of using these same data for real-time traveler information, ground truth probe vehicle data were collected. Travel time estimates from the WIM data and the probes were used to establish a simple linear relationship between passenger car and truck performance. It was concluded that the long distances between stations was a primary challenge to directly adapting the WIM data to real-time use. Recommendations were given on increased sensor spacing and filter improvement. Finally, potential performance metrics for station level, matched trucks, and filtered matched truck data were shown.

Developing Corridor-Level Truck Travel Time Estimates And Other Freight Performance Measures From Archived ITS Data