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Technical Report

Insights from Driver Parking Decisions in a Truck Simulator to Inform Curb Management Decisions

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Publication Date: 2023

Millions of people who live and work in cities purchase goods online. As ecommerce and urban deliveries spike, there is an increasing demand for curbside loading and unloading space. To better manage city curb spaces for urban freight, city planners and decision makers need to understand commercial vehicle driver behaviors and the factors they consider when parking at the curb.

Urban freight transportation is a diverse phenomenon. Commercial vehicle drivers must overcome several obstacles and adapt to various rules and policies to properly navigate the intricate metropolitan network and make deliveries and pick-ups. However, other road users and occasionally municipal planners generally view them as contributing considerably to urban congestio, responsible for unauthorized parking, double parking, and exceeding their legal parking time.

These realities reflect the need for a thorough comprehension of commercial vehicle operators’ core decision-making procedures and parking habits to inform and adjust curb management policies and procedures. However, more robust corroborated literature on the subject is needed. The information used in these studies is typically obtained from empirical field research, which, while valuable, is limited to certain situations and case scenarios. Therefore, to improve the operation of urban transportation networks, it is necessary to study commercial vehicle drivers’ parking behavior in a controlled environment.

This project used a heavy vehicle driving simulator to examine commercial vehicle drivers’ curbside parking behaviors in various environments in shared urban areas. Also observed were the interactions between commercial vehicle drivers and other road users.

The experiment was successfully completed by 12 participants. Five independent variables were included in this experiment: number of lanes (two-lane and four-lane roads), bike lane existence, passenger vehicle parking space availability, commercial vehicle loading zones (CVLZs) (no CVLZ, occupied CVLZs, and unoccupied CVLZs), and parking time (short-term parking: 3 to 5 minutes and long-term parking: 20 to 60 minutes). The heavy vehicle driving simulator also collected data regarding participants’ driving speed, eye movement, and stress level.

Results from the heavy vehicle driving simulator experiment indicated that the presence of a bike lane had significant effects on commercial vehicle drivers’ parking decisions., but only a slight effect on fixation duration times. The average fixation duration time, representing how long participants looked at a particular object, on the road with a bike lane was 4.81 seconds, whereas it was 5.25 seconds on roads without a bike lane. Results also showed that the frequency of illegal parking (not parking in the CVLZs) was greater during short-term parking activities, occurring 60 times (45 percent of parking maneuvers). Delivery times also had a slight effect on commercial vehicles’ speed while searching for parking (short-term parking was 17.7 mph; long term parking was 17.2 mph) and on drivers’ level of stress (short-term parking was 8.16 peaks/mins; long-term parking was 8.36 peaks/mins). Seven percent of participants chose to park in the travel lane, which suggested that commercial vehicle operators prioritize minimizing their walking distance to the destination over the violation of parking regulations.

The limited sample size demonstrated the value of our experimental approach but limited the strength of the recommendations that can be applied to practice. With that limitation acknowledged, our preliminary recommendations for city planners include infrastructure installation (i.e., convex mirrors installed at the curbside and CVLZ signs) to help drivers more easily identify legal parking spaces, and pavement markings (i.e., CVLZs, buffered bike lanes) to improve safety when parking. Parking time limits and buffers for bike lanes could improve efficient operation and safety for cyclists and other road users.

For future work, larger sample sizes should be collected. Additional factors could be considered, such as increased traffic flow, pedestrian traffic, conflicts among multiple delivery vehicles simultaneously, various curb use type allocations, and different curb policies and enforcement. Including a larger variety of commercial vehicle sizes and loading, zone sizes would also be of value. A combination of field observations and a driving simulator study could also help validate this investigation’s outcomes.

Authors: Dr. Andisheh RanjbariDr. Anne GoodchildDr. Ed McCormackRishi Verma, David S. Hurwitz (Oregon State University), Yujun Liu (Oregon State University), Hisham Jashami (Oregon State University)
Recommended Citation:
Goodchild, A., McCormack, E., Hurwitz, D., Ranjbari, A., Verma, R., Liu, Y., & Jashami, H. (2023). Insights from Driver Parking Decisions in a Truck Simulator to Inform Curb Management Decisions. PacTrans. 
Technical Report

Using Truck Fleet Management GPS Data to Develop the Foundation for a Performance Measures Program

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Publication: Washington State Transportation Center (TRAC)
Publication Date: 2011

Global positioning systems (GPS) used for fleet management by trucking companies provide probe data that can support a truck performance-monitoring program. This paper discusses the steps taken to acquire fleet management data and then process those data so they can eventually be used for a network-based truck performance measures program. While other studies have evaluated truck travel by using GPS, they have used a limited number of project-specific and temporary devices that have collected frequent location reads, permitting a fine-grained performance analysis of specific roadway segments. In contrast, this fleet management GPS data project involved infrequent reads but a relatively large number of different trucks with ongoing data collection. The most effective approach to obtaining the fleet management data was to purchase the data directly from GPS vendors. Because a performance measures program ultimately monitors trips generated by trucks as they travel between origins and destinations, an algorithm was developed to extract trip end information from the data. The large volume of data required automated processing without manual intervention. Because performance measures require travel times and speeds, it was also necessary to evaluate whether speed data from a large number of trucks could compensate for infrequent location reads. Spot speeds recorded by the trucks’ GPS devices were compared to speed data from roadway loops. The researchers concluded that spot speed data can indicate free flow conditions, but sufficient quantities of data are probably necessary to measure congested travel.


Authors: Dr. Ed McCormack, Wenjuan Zhao
Recommended Citation:
McCormack, E. D., Zhao, W., & Tabat, D. (2011). GPS truck data performance measures program in Washington State. Washington State Department of Transportation, Office of Research. 
Technical Report

Development of a Freight Benefit/Cost Methodology for Project Planning

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Publication: Washington State Department of Transportation, Pacific NW Transportation Consortium (PacTrans)
Publication Date: 2013
Future reauthorizations of the federal transportation bill will require a comprehensive and quantitative analysis of the freight benefits of proposed freight system projects. To prioritize public investments in freight systems and to ensure consideration of the contribution of freight to the overall system performance, states and regions need an improved method to analyze freight benefits associated with proposed highway and truck intermodal improvements that would lead to enhanced trade and sustainable economic growth, improved safety and environmental quality, and goods delivery in Washington State.
This project develops a process to address this need by building on previous and ongoing research by some project team members to develop an agency-friendly, data-supported framework to prioritize public investments for freight systems in Washington and Oregon. The project integrates two ongoing WSDOT-funded efforts: one to create methods to calculate the value of truck and truck-intermodal infrastructure projects and the other to collect truck probe data from commercial GPS devices to create a statewide Freight Performance Measures (FPM) program. This integration informs the development of a framework that allows public agencies to quantify freight investment benefits in specific areas such as major freight corridors and across borders.



Authors: Dr. Anne GoodchildDr. Ed McCormack, Ken Casavant, Zun Wang, B Starr McMullen, Daniel Holder
Recommended Citation:
Casavant, Ken, Anne Goodchild, Ed McCormack, Zun Wang, B. Starr McMullen, and Daniel Holder. "Development of a Freight Benefit/Cost Methodology for Project Planning." 
Technical Report

Field Test of Unmanned Aircraft Systems (UAS) to Support Avalanche Monitoring

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Publication: Norwegian Public Roads Administration Report
Volume: Geohazard Survey from Air (GEOSFAIR)
Publication Date: 2022

The Norwegian Public Roads Administration, the Norwegian Geotechnical Institute, and SINTEF conducted a field test with a unmanned aerial system (UAS) with various instruments at the research station Fonnbu in Stryn. The purpose of the test was to evaluate the use of instrumented drones for monitoring and assessing avalanche danger. The instruments tested included optical and thermal imaging, laser scanning and ground-penetrating radar. Resulting datasets included 3D models (point clouds and height maps), multispectral and radiometric, thermal images and radargrams.

Authors: Dr. Ed McCormack, Regula Frauenfelder, Sean Salazar, Halgeir Dahle, Tore Humstad, Emil Solbakken, Trine Kirkhus, Richard Moore, Bastien Dupuy, Pauline Lorand
Technical Report

Technology and Safety on Urban Roadways: The Role of ITS in WSDOT

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Publication: Washington State Transportation Center (TRAC)
Publication Date: 2006

This report examines the relationship between Intelligent Transportation Systems (ITS) and safety from an urban perspective.

Existing urban ITS systems are either system-level or site-level applications. System-level ITS, such as freeway management systems or traffic signal networks, address safety concerns only indirectly. These systems are designed to improve traffic flows and thus indirectly reduce collisions caused by congestion. Other system-level ITS used to increase the efficiency of transit, commercial vehicle, and emergency service operations also benefit safety indirectly. Site-level ITS applications, such as railroad/highway crossing warnings or work zone systems, are installed to directly address safety concerns. However, these applications are limited to specific locations identified as hazardous.

Most urban crashes in Washington involve multiple vehicle collisions caused by driver error at locations that have not been identified as hazardous. Future ITS systems known collision avoidance systems (CAS) hold considerable promise for urban roadway safety because these in-vehicle devices will inform drivers of judgment errors and can do so at many locations along an urban roadway system.

A handful of ITS applications are so well tested that they can be aggressively pursued by WSDOT as tools to reduce urban crashes. Most of these applications include the various systems, such a ramp meters and incident detection, used for freeway management. Other ITS safety applications, while promising, still need to be fully documented and are best used as demonstration applications. Most of these applications involve sensor technology used to warn drivers about road and roadside hazards at specific sites. The greatest safety benefit from ITS may come from in-vehicle collision warning systems. These applications should evolve from a number of large federal research projects and private industry initiatives that are under way. Given their potential impact on safety, WSDOT should monitor applications of these projects.

Authors: Dr. Ed McCormack, Bill Legg
Recommended Citation:
McCormack, E., Legg, B. (2000). Technology and Safety on Urban Roadways: The Role of ITS in WSDOT. Research Report, Washington State Transportation Center (TRAC). Washington State Transportation Center, U.S. Department of Transportation. 
Technical Report

Development and Analysis of a GIS-Based Statewide Freight Data Flow Network

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Publication: Washington State Department of Transportation
Publication Date: 2009
In the face of many risks of disruptions to our transportation system, this research improves WSDOT’s ability to manage the freight transportation system so that it minimizes the economic consequences of transportation disruptions.
Faced with a high probability that major disruptions to the transportation system will
harm the state’s economy, the Washington State Department of Transportation
(WSDOT), in partnership with Transportation Northwest (TransNow) commissioned
researchers at the University of Washington and Washington State University to
undertake freight resiliency research to:
  • Understand how disruptions of the state’s freight corridors change the way
    trucking companies and various freight-dependent industries route goods,
  • Plan to protect freight-dependent sectors that are at high risk from these disruptive
    events, and
  • Prioritize future transportation investments based on the risk of economic loss to
    the state
To accurately predict how companies will route shipments during a disruption,
this research developed the first statewide multimodal freight model for Washington
State. The model is a GIS-based portrayal of the state’s freight highway, arterial, rail,
waterway and intermodal network and can help the state prioritize strategies that protect industries most vulnerable to disruptions.
The report features two case studies showing the model’s capabilities: the potato growing and processing industry was chosen as a representative agricultural sector, and diesel fuel distribution for its importance to all industry sectors. The case studies are found in sections 5.2 and 5.3 in the report and show how the statewide freight model can:
  • Predict how shipments will be re-routed during disruptions, and
  • Analyze the level of resiliency in various industry sectors in Washington State
The two case studies document the fragility of the state’s potato growing and processing
sectors and its dependence on the I-90 corridor, while showing how the state’s diesel
delivery system is highly resilient and isn’t linked to I-90.
As origin-destination data for other freight-dependent sectors is added to the model,
WSDOT will be able to evaluate the impact of freight system disruptions on each of
them. This will improve WSDOT’s ability to develop optimal strategies for highway
closures, and prioritize improvements to the system based on the relative impact of the
This research addressed several technical areas that would need to be resolved by any
organization building a state freight model. First, the researchers had to decide on the
level of spatial and temporal detail to include in the statewide GIS freight model. This
decision has significant consequences for data resolution requirements and results.
Including every road in Washington would have created a cumbersome model with a
large number of links that weren’t used. However, in order to analyze routing during a
disruption all possible connections must exist between origin and destination points in the model. While the team initially included only the core freight network in the model,
ultimately all road links were added to create complete network connectivity.
Second, as state- and corridor-level commodity flow data is practically non-existent, data
collection for the two case studies was resource intensive. Supply chain data is held by
various stakeholders and typically not listed on public websites, and it isn’t organized by
those stakeholders for use in a freight model. In most cases it’s difficult to assure data
quality. The team learned that the most difficult data to obtain is data on spatially or
temporally variable attributes, such as truck location and volume. So they developed a
method to estimate the importance of transportation links without commodity flow data.

Third, the freight model identified the shortest route, based on travel time, between any
origin and destination (O/D) pair in the state, and the shortest travel-time re-route for
each O/D pair after a disruption. The routing logic in the model is based on accepted
algorithms used by Google Maps and MapQuest. Phase III of the state’s freight
resiliency research was funded by WSDOT and will result in improved truck freight
routing logic for the model in 2011.
The two case studies showed how the state’s supply chains use infrastructure differently,
and that some supply chains have built flexibility into their operations and are resilient
while others are not, which leads to very different economic consequences. The results
of these case studies significantly contributed to WSDOT’s understanding of goods
movement and vulnerability to disruptions.
In the future, Washington State will need corridor-level commodity flow data to
implement the research findings and complete the state freight model. In 2009, the
National Cooperative Freight Research Program (NCFRP) funded development of new
methodology to collect and analyze sub-national commodity flow information. This
NCFRP project, funded at $500,000, will be completed in 2010 and provide a mechanism for states to accurately account for corridor-level commodity flows. If funds are available to implement the new methodology in Washington State, the state’s freight
model will use the information to map these existing origin destination commodity flows
onto the freight network, evaluate the number of re-routed commercial vehicles, and their increased reroute distance from any disruption. This will allow WSDOT to develop
prioritized plans for supply chain disruptions, and recommend improvements to the
system based on the economic impact of the disruption.
This report summarizes 1) the results from a thorough review of resilience literature and resilience practices within enterprises and organizations, 2) the development of a GIS-based statewide freight transportation network model, 3) the collection of detailed data regarding two important industries in Washington state, the distribution of potatoes and diesel fuel, and 4) analysis of the response of these industries to specific disruptions to the state transportation network.
The report also includes recommendations for improvements and additions to the GIS model that will further the state’s goals of understanding the relationship between infrastructure availability and economic activity, as well as recommendations for improvements to the statewide freight transportation model so that it can capture additional system complexity.
Authors: Dr. Anne GoodchildDr. Ed McCormack, Eric Jessup, Derik Andreoli, Kelly Pitera, Sunny Rose, Chilan Ta
Recommended Citation:
Goodchild, Anne V., Eric L. Jessup, Edward D. McCormack, Derik Andreoli, S Rose, Chilan Ta and Kelly Pitera. “Development and Analysis of a GIS-Based Statewide Freight Data Flow Network.” (2009).
Technical Report

Analyzing the Long-Term Impacts of COVID-19 Disruption on Travel Patterns

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Publication Date: 2020

The rapid spread of COVID-19 pandemic in the U.S. spurred many state governments to take extensive actions for social distancing and issue stay-at-home orders to reduce the spread of the virus. Washington State and all other States in the PacTrans region have issued stay-at-home orders that include school closures, telecommuting, bars/restaurants closures, and group gathering bans, among others. These actions create significant changes to daily life and while some travel patterns will gradually restore by the end of outbreak, some may remain changed for a much longer period.

Behaviors that may see a lasting response include commuting, grocery shopping, business meetings, and even social interactions. Working from home for 2-3 months may change people’s attitudes toward telecommuting, and some may continue to do so a few days a week once the stay-at-home orders are lifted. Some employers may also shift their telecommute policies and provide/encourage working from home. In recent years, with the growth of e-commerce, many grocery stores had started to offer home deliveries; however, online grocery shopping experienced a fast and sudden boom during the pandemic. This has resulted in quick service adoption, and therefore some people may continue to do online grocery shopping once things go back to normal. Moreover, as people shift to online grocery shopping, they may proactively make a list and place orders less frequently compared to them going to store, resulting in fewer shopping trips. Some business meetings and even personal gatherings may also move online as people learn about and try alternate ways of communicating during the outbreak. Some may also consider enrolling in distant learning programs instead of attending in-person educational programs. There may also be significant changes in modes of travel. Some transit commuters may choose other modes of transportation for a while, and people may choose to drive or bike instead of taking a ride-hailing trip.

The goal of this research is to understand how COVID-19 disruption has affected people’s activity and travel patterns during the pandemic, and how these changes may persist in a post-pandemic era.

Authors: Dr. Andisheh Ranjbari, Parastoo Jabbari, Don MacKenzie
Recommended Citation:
Mackenzie D., Jabbari P., Ranjbari A. Analyzing the Long-Term Impacts of COVID-19 Disruption on Travel Patterns. Pacific Northwest Transportation Consortium (PacTrans). 2020.
Technical Report

Freight Data from Intelligent Transportation System Devices

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Publication: Washington State Transportation Center (TRAC)
Publication Date: 2006
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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Publication Date: 2008

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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Publication: TransNow, Transportation Northwest, U.S. Department of Transportation, University Transportation Centers Program.
Publication Date: 2010

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).