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

Abstract

Sponsoring Agency Code Supplementary Notes AbstractThe 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, weighin-motion data from each of the twenty-two stations in Oregon were assembled, processed, and uploaded in the WIM data archive 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 successful 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 greatest are 258 miles apart. The first algorithm matched transponders between 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 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 17.

Analysis of Travel Time Reliability for Freight Corridors Connecting the Pacific Northwest

“…Algorithms must be incorporated to filter out trucks that have not traveled through the corridor without stopping because their travel-time information would present a bias in the data (slower travel time due to stopping/resting or delivery). Secondly, the number of trucks equipped with transponders is relatively low, and a large sample size must be required to accurately estimate link travel time based on the truck data (11).…”

“…Recent work at Portland State University (PSU), under the sponsorship of the U.S. DOT University Transportation Centers Program, investigated the use of transponder-equipped trucks to make travel-time estimations between weigh stations in rural Oregon (11). Similar to previous research, this work incorporated algorithms to identify trucks deviating from the freeway between WIM stations by matching unique truck IDs between stations, and using time thresholds and comparisons between trucks to identify those traveling through the corridor without stopping.…”

“…Similar to previous research, this work incorporated algorithms to identify trucks deviating from the freeway between WIM stations by matching unique truck IDs between stations, and using time thresholds and comparisons between trucks to identify those traveling through the corridor without stopping. This research was successful in developing an effective algorithm to identify through trucks, and deriving additional measures of performance by quantifying overweight vehicles, ton-miles on corridors, empty vehicles, the penetration of trucks with truck transponders, origin-destination estimations, and seasonal variability in various measures as well as travel-time estimations (11).…”

Algorithms for Studying the Impact of Travel Time Reliability along Multisegment Trucking Freight Corridors

“…However, truck transponder data presents several challenges (10). First, there are generally long distances between WIM stations.…”

Bayesian Models for Reidentification of Trucks Over Long Distances on the Basis of Axle Measurement Data

“…An exploration of using transponder (or AVI) data for truck travel times can be found in the study by Monsere, Wolfe, Alawakiel, and Stephens (2009). However, vehicle reidentification methods that are based on the vehicle attribute data collected by sensors already installed on roadways enable tracking vehicles anonymously and do not require 1 Downloaded by [Universidad de Sevilla] at 04:13 20 November 2014 substantial additional investment.…”