SPR-821: Develop New Methods to use ODOT Weigh-in-Motion Data for Predicting Freight Flow and/or Commodity Patterns

Authors

Avinash Unnikrishnan, Portland State UniversityFollow
Miguel Figliozzi, Portland State UniversityFollow
Jason C. Anderson, Portland State UniversityFollow
Salvador Hernandez, Oregon State University
Oregon. Department of Transportation. Research Section
United States. Federal Highway Administration

Sponsor

Fedral Highway Administration, contract number SPR821

Document Type

Dataset

Publication Date

11-2019

Subjects

Freight and freightage -- Oregon -- Statistics, Transportation -- Oregon -- Statistics, Traffic flow--Oregon--Statistics, Weigh-in-motion systems, Transportation -- Oregon -- Planning

Abstract

The objective of this research is to evaluate weigh-in-motion (WIM) data for use by Oregon Department of Transportation (ODOT) for short-term and long-term highway investment prioritization and the tools and methods used to conduct freight analysis. This research will recommend methods of using the data to produce information, i.e. dashboards, related to heavy truck patterns, ultimately leading to improved analytical tools and methods based on current and emerging patterns of truck movement. The research will also identify and evaluate other data sources (both public and private) with the potential to enhance the information generated using WIM data, such as truck speed data, automatic traffic recorders and commodity flow data. This study will produce an inventory of potential data sources available to ODOT, identifying the pros and cons associated with each and gaging the usefulness to meet the needs of freight mobility.

Description

Data description 1 - Oregon Weight Regulations

This file summarizes current Oregon weight regulations as it pertains to commercial motor vehicles.

Data description 2 - Summary of Weight-Mile Tax

This file summarizes state weight-mile tax laws for the four states that currently implement a weight-mile tax: Kentucky, New Mexico, New York, and Oregon.

Data description 3 - Vehicle Classification Plots

As part of the WIM data quality control analysis for ODOT Class 11 trucks, various visual assessments were made. The visual assessments consisted of generating specific plots for each month in each year of WIM data. The first of these plots consists of vehicle classification, in which ODOT Class 01 should account for the largest proportion.

Data description 4 - Speed Distribution Plots

The fourth set of plots consists of speed distribution, where distributions were used to identify any outlying speed observations.

Data description 5 - Noon-Midnight Hour Volume

Comparison Plots This series of plots assesses the noon-hour volumes and midnight-hour volumes, where the noon-hour volumes should always be greater than the midnight-hour volumes.

Data description 6 - Number of Trucks by Hour Plots

The second series of plots consist of the number of trucks per hour. This is to assess if there were any consecutive hours in which no trucks were counted.

Data description 7 - Steering Axle Weight Distribution Plots

The final set of plots were related to steering axle weight and their distributions. For these plots, there should be a clear peak in the distribution at around 10,000 pounds.

Data description 8 - Observed Weight Distribution Plots

The fifth series of plots were that of the observed weight distribution, the weight recorded at the WIM station as the truck travels. For these plots, there should be a clear lower and upper peak to differentiate unload and loaded trucks, respectively.

Data description 9 - Summary Statistics Plots by Classification Group

This file presents summary statistics plots by classification group: ODOT Class 03 to ODOT Class 10, ODOT Class 11, ODOT Class 12 to ODOT Class 19, and all trucks (ODOT Class 03 to ODOT Class 19, excluding ODOT Class 04 and ODOT Class 07). Statistics presented include the total number of trucks, average monthly observed weight, average monthly observed truck weight, average monthly observed median truck weight, and average monthly observed 95th percentile truck weight.

Data description 10 - Directional and Seasonal Trends by Classification Group and WIM Station

This file presents directional and seasonal trends by classification group and select WIM stations based on the total number of observed trucks and average monthly observed weight (truck and cargo). Regarding directional trends, trends are given at each select WIM station by classification group. Regarding seasonal trends, as to not overlap years of WIM data, trends are given at each select WIM station based on the following aggregations: January to April, May to August, and September to December.

Data description 11 - Monthly Truck Volume and Total Observed Weight Percentages

This file presents the monthly percentages of truck volume and observed weight by WIM station. Included is a comparison across years consisting of the maximum number of observed trucks/weight, the minimum number of trucks/observed weight, the range (different between maximum and minimum observed values), and average.

Data description 12 - Observed Weight Density Plots for ODOT Class 11 to ODOT Class 12 Trucks

This file includes observed weight density plots used to calculate empirical truck weight. With Woodburn accounting for both the highest volumes and weights, the presented plots are for Woodburn.

Data description 13 - EROAD and WIM Weight Comparisons

This file shows plots comparing declared weights in the EROAD data to observed weights in the WIM data.

Data description 14 - Distance Traveled Summary

This file includes a summary of distance traveled based on origins and destinations as provided in the EROAD data. Origins and destinations were provided at the county-level. Therefore, all distance calculations are based on the assumptions that origins and destinations are at the count seats. To ensure driving distance was calculated, all distances were obtained used the Google Maps API. Each plot shows distances by frequency, density, and an empirical cumulative distribution function.

Rights

This work is marked with CC0 1.0 Universal

DOI

10.15760/cee-data.02

Persistent Identifier

https://archives.pdx.edu/ds/psu/30498

Recommended Citation

Unnikrishnan, A., Figliozzi, M., Anderson, J. C., Hernandez, S., Oregon. Department of Transportation. Research Section, United States. Federal Highway Administration. "SPR-821: Develop New Methods to use ODOT Weigh-in-Motion Data for Predicting Freight Flow and/or Commodity Patterns" (2019). Civil and Environmental Engineering Datasets. 2. https://doi.org/10.15760/cee-data.02