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Urban Freight Lab

Publication Type: Technical Report

Technical Report

Freight Data from Intelligent Transportation System Devices

 
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URL: http://depts.washington.edu/trac/bulkdisk/pdf/566.1.pdf
Publication: Washington State Transportation Center (TRAC)
Publication Date: 2006
Summary:
As congestion increases, transportation agencies are seeking regional travel time data to determine exactly when, how, and where congestion affects freight mobility. Concurrently, a number of regional intelligent transportation systems (ITS) are incorporating various technologies to improve transportation system efficiency. This research explored the ability of these ITS devices to be used as tools for developing useful historical, and perhaps real-time, traffic flow information.
Regional transponder systems have required the installation of a series of readers at weigh stations in ports, along freeways, and at the Washington/British Columbia border. By linking data from these readers, it was possible to anonymously track individual, transponder-equipped trucks and to develop corridor-level travel time information. However, the research found that it is important to have an adequate number of data points between readers to identify non-congestion related stops. Another portion of this research tested five GPS devices in trucks. The research found that the GPS data transmitted by cellular technology from these vehicles can provide much of the facility performance information desired by roadway agencies. However, obtaining sufficient amounts of these data in a cost effective manner will be difficult. A third source of ITS data that was explored was WSDOT’s extensive loop-based freeway surveillance and control system.
The output from of each of the ITS devices analyzed in this research presented differing pictures (versions) of freight flow performance for the same stretch of roadway. In addition, ITS data often covered different (and non-contiguous) roadway segments and systems or geographic areas. The result of this wide amount of variety was an integration task that was far more complex then initially expected.
Overall, the study found that the integration of data from the entire range of ITS devices potentially offers both a more complete and more accurate overall description of freight and truck flows.

 

 

Authors: Dr. Ed McCormack, Mark Hallenbeck, Duane Wright, Jennifer Nee
Recommended Citation:
Hallenbeck, M. E., McCormack, E., Nee, J., & Wright, D. (2003). Freight Data from Intelligent Transportation System Devices (No. WA-RD 566.1,). The Center.
Technical Report

Cascadia Border Operations, Issues, and Consequences for the Agrifood Market

 
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URL: https://www.researchgate.net/publication/237468811_Cascadia_Border_Operations_Issues_and_Consequences_for_the_Agrifood_Market
Publication Date: 2008
Summary:

In this paper we present a profile of US/Canada border operations in the Western Cascadia Region, which lies between the Greater Vancouver and Puget Sound megacities. We show how this border is distinct from the more commonly discussed US/Canada border between New York, Michigan, and Ontario, in that commodities are typically less time sensitive, and a larger proportion of trips are made intra-regionally. Border procedures are described, as well as current programs for expedited crossings. Results from qualitative interviews with shippers are also presented and discussed, which show the supply chain’s current responses both to mean border crossing delay and the variability of these crossing times. Finally, we consider the consequences of these responses for the agrifood industry in Cascadia, for whom the consequences of delay and variability of delay are more significant.

Authors: Dr. Anne Goodchild, Li Leung
Recommended Citation:
Goodchild, Anne, and Li Leung. Cascadia Border Operations, Issues, and Consequences for the Agrifood Market. No. 1177-2016-93391. 2008.
Technical Report

Developing a GPS-Based Truck Freight Performance Measure Platform

 
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URL: https://rosap.ntl.bts.gov/view/dot/18003
Publication: TransNow, Transportation Northwest, U.S. Department of Transportation, University Transportation Centers Program.
Publication Date: 2010
Summary:

Although trucks move the largest volume and value of goods in urban areas, relatively little is known about their travel patterns and how the roadway network performs for trucks. The Washington State Department of Transportation (WSDOT), Transportation Northwest (TransNow) at the University of Washington, and the Washington Trucking Associations have partnered on a research effort to collect and analyze global positioning system (GPS) truck data from commercial, in-vehicle, truck fleet management systems used in the central Puget Sound region. The research project is collecting commercially available GPS data and evaluating their feasibility to support a state truck freight network performance monitoring program.

WSDOT is interested in using this program to monitor truck travel times and system reliability and to guide freight investment decisions. The researchers reviewed truck freight performance measures that could be extracted from the data and that focused on travel times and speeds, which, analyzed over time, determine a roadway system’s reliability. The utility of spot speeds and the GPS data, in general, was evaluated in a case study of a three-week construction project on the Interstate-90 bridge. The researchers also explored methods for capturing regional truck travel performance.

Although trucks move the largest volume and value of goods in urban areas, relatively little is known about their travel patterns and how the roadway network performs for trucks. Global positioning systems (GPS) used by trucking companies to manage their equipment and staff and meet shippers’ needs capture truck data that are now available to the public sector for analysis. The Washington State Department of Transportation (WSDOT), Transportation Northwest
(TransNow) at the University of Washington (UW), and the Washington Trucking Associations (WTA) have partnered on a research effort to collect and analyze GPS truck data from commercial, in-vehicle, truck fleet management systems used in the central Puget Sound region. The research project is collecting commercially available GPS data and evaluating their feasibility to support a state truck freight network performance monitoring program. WSDOT is interested in using this program to monitor truck travel times and system reliability and to guide freight investment decisions.

  • The success of the truck freight performance measurement program will depend on developing the capability to
    efficiently collect and process GPS devices’ output
    extract useful truck travel time and speed, roadway location, and stop location information and
    protect the identity of the truckers and their travel information so that business-sensitive information is not released.

While earlier studies have evaluated commercial vehicles’ travel characteristics by using GPS devices, these researchers did not have access to commercial fleet data and had to estimate corridor travel speeds from a limited number of portable GPS units capable of making frequent (1-to-60-second) location reads (Quiroga and Bullock 1998, Greaves and Figliozzi 2008, Due and Aultman-Hall 2007). This read frequency permitted a fine-grained analysis of truck movements on specific segments of the road network but did not provide enough data points to reliably track regional or corridor network performance.

This research project is taking a different approach. The data analyzed in this project are drawn from GPS devices installed to meet the trucking sector’s fleet management needs. So the truck locations are collected less frequently (typically every 5 to 15 minutes) but are gathered from a much larger number of trucks over a long period of time. The researchers are collecting data from 2,000 to 3,000 trucks per day for one year in the central Puget Sound region.

This report discusses the steps taken to build, clean, and test the data collection and analytic foundation from which the UW and WSDOT will extract network-based truck performance statistics. One of the most important steps of the project has been to obtain fleet management GPS data from the trucking industry. Trucking companies approached by WSDOT and the UW at the beginning of the study readily agreed to share their GPS data, but a lack of technical support from the
firms made data collection difficult. The researchers overcame that obstacle by successfully negotiating contracts with GPS and telecom vendors to obtain GPS truck reads in the study region. The next challenge was to gather and format the large quantities of data (millions of points) from different vendors’ systems so that they could be manipulated and evaluated by the project team. Handling the large quantity of data meant that data processing steps had to be automated,
which required the development and validation of rule-based logic that could be used to develop algorithms.

Because a truck performance measures program will ultimately monitor travel generated by trucks as they respond to shippers’ business needs, picking up goods at origins (O) and dropping them off at destinations (D), the team developed algorithms to extract individual truck’s O/D information from the GPS data. The researchers mapped (geocoded) each truck’s location (as expressed by a GPS latitude and longitude) to its actual location on the Puget Sound region’s roadway
network and to traffic analysis zones (TAZs) used for transportation modeling and planning.

The researchers reviewed truck freight performance measures that could be extracted from the data and that focused on travel times and speeds, which, analyzed over time, determine a roadway system’s reliability. Because the fleet management GPS data from individual trucks typically consist of infrequent location reads, making any one truck an unreliable probe vehicle, the researchers explored whether data from a larger quantity of trucks could compensate for infrequent location reads. To do this, the project had to evaluate whether the spot (instantaneous) speeds recorded by one truck’s GPS device could be used in combination with spot speeds from other trucks on the same portion of the roadway network.

The utility of spot speeds and the GPS data in general was evaluated in a case study of a three-week construction project on the Interstate-90 (I-90) bridge. The accuracy of the spot speeds was then validated by comparing the results with speed data from WSDOT’s freeway management loop system (FLOW).

The researchers also explored methods for capturing regional truck travel performance. The approach identified zones that were important in terms of the number of truck trips that were generated. Trucks’ travel performance as they traveled between these economic zones could then be monitored over time and across different times of day.

Authors: Dr. Ed McCormack, Xiaolei Ma, Charles Klocow, Anthony Curreri, Duane Wright
Recommended Citation:
McCormack, Edward D., Xiaolei Ma, Charles Klocow, Anthony Curreri and Duane Wright. “Developing a GPS-Based Truck Freight Performance Measure Platform.” (2010).
Technical Report

Washington State Freight System Resiliency

 
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URL: https://rosap.ntl.bts.gov/view/dot/17237
Publication: Transportation Northwest (TransNow)
Publication Date: 2009
Summary:

The economic viability and well-being of Washington State is significantly influenced by the freight transportation system serving the region. An increased understanding of the vulnerability of this freight system to natural disasters, weather, terrorist acts, work stoppages and other potential freight transportation disruptions will provide the State with the information necessary to assess the resiliency of the transportation system, and provide policy makers with the information required to improve it. This research project: a) Identifies a set of threats or categories of threats to be analyzed. b) Assesses the likelihood of each event occurring within certain time horizons. c) With the threats and their probabilities, analyzes the resiliency of the Washington transportation system.

Authors: Dr. Anne GoodchildDr. Ed McCormack, Eric Jessup, Derek Andreoli, Kelly Pitera, Chilan Ta
Recommended Citation:
Goodchild, A., Jessup, E., McCormack, E., Ta, C., Pitera, K., & Andreoli, D. (2009). Washington state freight system resiliency (No. TNW2009-01). Transportation Northwest (Organization).
Technical Report

Developing a System for Computing and Reporting MAP-21 and Other Freight Performance Measures

 
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URL: https://www.wsdot.wa.gov/research/reports/fullreports/844.1.pdf
Publication: Washington State Transportation Center (TRAC)
Publication Date: 2015
Summary:

This report documents the use of the National Performance Monitoring Research Data Set (NPMRDS) for the computation of freight performance measures on Interstate highways in Washington state. The report documents the data availability and specific data quality issues identified with NPMRDS. It then describes a recommended initial set of quality assurance tests that are needed before WSDOT begins producing freight performance measures.

The report also documents the initial set of performance measures that can be produced with the NPMRDS and the specific steps required to do so. A subset of those metrics was tested using NPMRDS data, including delay and frequency of congestion, to illustrate how WSDOT could use the freight performance measures. Finally, recommendations and the next steps that WSDOT needs to take are discussed.

This report describes the outcome of the initial exploration of the National Performance Research Monitoring Data Set (NPMRDS), supplied by the Federal Highway Administration (FHWA) to state transportation agencies and metropolitan planning organizations for use in computing roadway performance measures.

The NPMRDS provides roadway performance data for the national highway system (NHS). The intent of the NPMRDS was to provide a travel time estimate for every 5-minute time interval (epoch) of the year for all roadway segments in the NHS. The NPMRDS data are derived from instantaneous vehicle probe speed data supplied by a variety of GPS devices carried by both trucks and cars. The data are supplied on a geographic information system (GIS) roadway network, which divides the NHS into directional road segments based on the Traffic Message Channel (TMC) standard.

The report describes the availability, attributes, quality, and limitations of the NPMRDS data on the Interstates in the state of Washington.

Based on the review of the NPMRDS data, this report recommends a set of performance metrics for WSDOT’s use that describe the travel conditions that trucks moving freight within the state experience. It describes specific steps for computing those measures. And it uses a subset of those measures produced with the NPMRDS to illustrate how WSDOT can use those measures in its reporting and decision-making procedures.

Authors: Dr. Ed McCormackSaravanya (Sara) Sankarakumaraswamy, Mark E. Hallenbeck
Recommended Citation:
Hallenbeck, Mark E., Ed McCormack, and Saravanya Sankarakumaraswamy. Developing a system for computing and reporting MAP-21 and other freight performance measures. No. WA-RD 844.1. Washington (State). Dept. of Transportation. Research Office, 2015. 
Technical Report

Managing Increasing Demand for Curb Space in the City of the Future

 
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URL: http://hdl.handle.net/1773/48599
Publication Date: 2022
Summary:

The rapid rise of on-demand transportation and e-commerce goods deliveries, as well as increased cycling rates and transit use, are increasing demand for curb space. This demand has resulted in competition among modes, failed goods deliveries, roadway and curbside congestion, and illegal parking. This research increases our understanding of existing curb usage and provides new solutions to officials, planners, and engineers responsible for managing this scarce resource in the future. The research team worked with local agencies to ensure the study’s relevance to their needs and that the results will be broadly applicable for other cities. This research supports the development of innovative curb space designs and ensures that our urban streets may operate more efficiently, safely, and reliably for both goods and people.

The research elements included conducting a thorough scan and documenting previous studies that have examined curb space management, identifying emerging urban policies developed in response to growth, reviewing existing curb management policies and regulations, developing a conceptual curb use policy framework, reviewing existing and emerging technologies that will support flexible curb space management, evaluating curb use policy frameworks by collecting curb utilization data and establishing performance metrics, and simulating curb performance under different policy frameworks.

Authors: Anna Bovbjerg AlligoodDr. Ed McCormackDr. Andisheh Ranjbari, Kevin Chang
Recommended Citation:
Chang, K., Goodchild, A., Ranjbari, A., and McCormack, E. (2022). Managing Increasing Demand for Curb Space in the City of the Future. PacTrans Final Project Report.
Technical Report

Understanding Pacific Highway Commercial Vehicle Operations to Support Emissions Reduction Programs

 
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URL: https://rosap.ntl.bts.gov/view/dot/18660
Publication: Transportation Northwest (TransNow)
Publication Date: 2011
Summary:
This research, enabled by a data collection effort at the international commercial vehicle crossing at Blaine, WA, addressed three key questions regarding commercial vehicle border operations and near border operations. First, what are the unique features of border operations at Blaine, WA, that are not captured within the standard simulation tools (such as Border Wizard)? Second, what logistical inefficiencies are created by the border that increase empty miles traveled, emissions and total travel time between origin and destination? Third, what has the impact of electronic manifest filing been on primary inspection time? The research objectives were to (1) describe near border operations and identify possible solutions to reduce empty truck miles, (2) improve the understanding of the relationship between primary processing time and border crossing time, and (3) identify the impact of ACE (the commercial trade processing system being developed by Customs and Border Protection to facilitate legitimate trade and strengthen border security) electronic manifest filing on primary processing and primary processing time. The report is organized as follows: Chapter 1 describes near border operations through analysis of survey data, current knowledge of the impact of policy on near border facilities, and suggests changes to improve near border operations. Chapter 2 describes the features of processing at Blaine discovered during the data analysis that contribute processing time and border crossing time. Chapter 3 evaluates the impact of ACE on interview time, and compares interview times, crossing times, and volume in the 2009, 2006, and 2001 studies.

 

 

 

Authors: Dr. Anne Goodchild, Matthew Klein
Recommended Citation:
Goodchild, A., & Klein, M. (2011). Understanding Pacific Highway Commercial Vehicle Operations to Support Emissions Reduction Programs (No. TNW2010-11). Transportation Northwest (Organization).
Technical Report

An Examination of the Impact of Commercial Parking Utilization on Cyclist Behavior in Urban Environments

 
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URL: http://depts.washington.edu/pactrans/research/projects/an-examination-of-the-impact-of-increasing-commercial-parking-utilization-on-cyclist-safety-in-urban-environments/
Publication Date: 2016
Summary:

There is little research on the behavioral interaction between bicycle lanes and commercial vehicle loading zones (CVLZ) in the United States. These interactions are important to understand, to preempt increasing conflicts between truckers and bicyclists. In this study, a bicycling simulator experiment examined bicycle and truck interactions. The experiment was successfully completed by 48 participants. The bicycling simulator collected data regarding a participant’s velocity and lateral position. Three independent variables reflecting common engineering approaches were included in this experiment: pavement marking (L1: white lane markings with no supplemental pavement color, termed white lane markings, L2: white lane markings with solid green pavement applied on the conflict area, termed solid green, and L3: white lane markings with dashed green pavement applied on the conflict area, termed dashed green), signage (L1: No sign and L2: a truck warning sign), and truck maneuver (L1: no truck in CVLZ, L2: truck parked in CVLZ, and L3: truck pulling out of CVLZ).

The results showed that truck presence does have an effect on bicyclist’s performance, and this effect varies based on the engineering and design treatments employed. Of the three independent variables, truck maneuvering had the greatest impact by decreasing mean bicyclist velocity and increasing mean lateral position. It was also observed that when a truck was present in a CVLZ, bicyclists had a lower velocity and lower divergence from right-edge of bike lane on solid green pavement, and a higher divergence from the right-edge of bike lane was observed when a warning sign was present.

Authors: Dr. Anne GoodchildDr. Ed McCormackManali Sheth, David S. Hurwitz, Masoud Ghodrat Abadi
Recommended Citation:
Hurwitz, David S., Ed McCormack, Anne Goodchild, Masoud Ghodrat Abadi, and Manali Sheth. An Examination of the Impact of Commercial Parking Utilization on Cyclist Behavior in Urban Environments. 2018.
Technical Report

Transit Corridor Study

 
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URL: https://mic.comotion.uw.edu/wp-content/uploads/2021/07/TransitCorridorStudy_InterimReport_June2021.pdf
Publication Date: 2021
Summary:

This study is sponsored by Amazon, Bellevue Transportation department, Challenge Seattle, King County Metro, Seattle Department of Transportation, Sound Transit, and Uber, with support from the Mobility Innovation Center at UW CoMotion.

Population and extended economic growth in many Seattle neighborhoods are driving increased demand for private car travel along with transportation services such as ridehailing and on-demand delivery. Together, these trends are adding to existing demand for loading and unloading operations throughout the city, and exacerbating traffic congestion. Anecdotal evidence indicates that passenger/delivery vehicle stops at or next to transit stops can interfere with bus operations, causing longer or more volatile delays. The increased travel times and reduced reliability further erode the attractiveness of transit to travelers. Thus, it is important to understand how transit, ridehailing, and goods delivery vehicles interact in terms of both operations and travel demand.
This project focuses on the analysis of open-source transit data to screen for locations with slow and/or unreliable bus travel times, and couple that data with interference observation, environmental, and traffic-related data to potentially predict the likely causes. We have developed tools to identify transit corridors with high levels of interference from other road users, including passenger cars, ridehailing vehicles and goods delivery vehicles. These tools are applied to transit corridors in Seattle and Bellevue, and methods have been developed to identify likely sources of interference from available data.
We drew on multiple data sources for identifying high-interference corridors in the region, including:
  • a virtual workshop with participants from beneficiary agencies and stakeholders to solicit input;
  • an online crowdsourcing survey to engage the community and gather feedback from all road users;
  • route-level ridership data from King County Metro; and
  • aggregated pick-up/drop-off data on ridehailing activities from SharedStreets.
Data was consolidated and 10 corridors were selected based on their likelihood of containing interference between buses and other road users, transit ridership levels, and stakeholder and community feedback.
In addition, we have developed a tool for identifying corridors with slow and/or unreliable bus travel times from open-source real-time transit data. We implemented a pipeline for ingesting and analyzing King County Metro’s real-time Generalized Transit Feed Specification data (GTFS-RT) at 10-second intervals. Using this pipeline, active bus coordinate and schedule adherence data has been scraped and stored to an Amazon Web Services (AWS) server since September 2020. We developed efficient methods to aggregate tracked bus locations and assign them to roadway segments, and quantified delays in terms of schedule deviation and ratio of median to free-flow speeds, among other metrics. We have developed a web based visualization tool to display this data, and it is being updated daily with aggregated performance metrics from our database.
To collect ground truth validation data along selected corridors, we implemented an online data collection tool for field observations, and recruited research assistants to observe bus operations along the study corridors and record information on bus traversals and instances of interference. This dataset is analyzed alongside the GTFS-RT data, environmental, and traffic related data to identify instances of delay and predict the likely causes.
Field data was collected for three weeks along eight of the selected corridors in March 2021, but was later paused due to depressed levels of transportation activity during the COVID-19 pandemic and the current unstable condition of travel choices and city traffic (and thus interferences). Preliminary analysis on the collected data revealed that there is not a substantial effect shown in the GTFS-RT data when a bus is interfered with; however, there were not a lot of interference observations in the collected field data. So, it remains to be seen whether the lack of an identifiable effect is due to the lack of ground truth data, lack of precision in the automatic vehicle location system, or the relatively low impact of an interference when compared to the effects of general traffic congestion, signals, and other roadway conditions. A linear regression model was also generated to determine the extent to which roadway characteristics can predict segment performance, which produced mildly predictive results.
As businesses and transit services continue to reopen, there will likely be an increase in the amount of transit interference experienced between buses and other roadway users, which will potentially allow for the gathering of more ground truth validation data. Field observations will resume in late Summer/early Fall 2021 and will continue until enough data is collected to either (1) model connections between observed interference and bus delays in the GTFS-RT data; or (2) determine whether significant delays cannot be linked to observed instances of interference in the study corridors. The GTFS-RT data scraping will continue daily, and summarized in the developed interactive visualization tool.
The major anticipated benefits of the project can be summarized as follows:
  • This work will help identify network-wide road and route segments with slow and/or unreliable bus travel times. We may also be able to identify main causes of delay in the study corridors.
  • Moreover, we expect that this work will generate reusable analytical tools that can be applied by local agencies on an ongoing basis, and by other researchers and transportation agencies in their own jurisdictions.
  • The outcomes of this work will enable identifying corridors with slow and/or unreliable bus travel times as candidates for specific countermeasures to increase transit performance, such as increased enforcement, modified curb use rules, or preferential bus or street use treatments. Targeting such countermeasures towards priority locations will result in faster and more reliable bus operations, and a more efficient transportation network at a lower cost to transit agencies.
Authors: Dr. Andisheh Ranjbari, Zack Aemmer, Borna Arabkhedri, Don MacKenzie
Technical Report

Structural and Geographic Shifts in the Washington Warehousing Industry: Transportation Impacts for the Green River Valley

 
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URL: https://rosap.ntl.bts.gov/view/dot/17233
Publication: Transportation Northwest (TransNow)
Publication Date: 2009
Summary:
Establishment level employment data indicate that the warehousing industry has experienced rapid growth and restructuring since 1998. This restructuring has resulted in geographic shifts at the national, regional, and local scales. Uneven growth in warehousing establishments across the Pacific Northwest has likely exerted a significant impact on the regional transportation system, but the extent of these transportation impacts remains unknown. Identifying these impacts is the goal of our proposed study. Recent and ongoing research indicates that growth in the warehousing industry is profound. County Business Patterns data published by the US Census Bureau indicates that at the national level, the number of warehousing establishments grew by just over 100 percent from 1998 to 2005. In 1998 there were 6,712 warehousing establishments in the US. By 2005, that number had increased to 13,483. Although a wide range exists within the warehousing industry, interview data collected by the authors of this proposal indicate that each warehouse handles between 25 and 100 trucks, or 50 and 200 trips, hence the location of warehousing establishments has a significant impact on transportation systems. At the county level, we see that in Washington, King County experienced the strongest absolute growth, adding 59 establishments to the 61 reported in 1998. In relative terms, however, Pierce County added warehousing establishments at a faster rate (159 percent) than any other county. The preliminary data produced in Goodchild and Andreoli’s report clearly indicate that there has been strong growth in warehousing establishments at the national and state levels, but that the growth has not been even across states and counties. From a transportation perspective, these findings suggest that future research needs to focus on how these structural and geographic shifts impact regional and local transportation systems.

 

 

Authors: Dr. Anne Goodchild, Derek Andrioli
Recommended Citation:
Goodchild, A., & Andrioli, D. (2009). Structural and Geographic Shifts in the Washington Warehousing Industry: Transportation Impacts for the Green River Valley (No. TNW2009-04). Transportation Northwest (Organization).