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Paper

Choosing My Own Path: Revealing Differences in Route Choice Preferences Across Long-Haul, Medium-Haul, and Short-Haul Trucking

Publication Date: 2023
Summary:

The rapid growth in e-commerce activities and the constant specialization of industries have aroused an unparalleled demand for trucking in urban areas, leading to growing concern over its interference to the transportation system. Understanding truck route choice preferences across long-haul, medium-haul, and short-haul trips can offer insights for designing the truck route network tailored to specific freight demand types, so as to effectively reduce their interference to passenger transportation. However, limited research has been conducted to explore the heterogeneity or similarity of route choice preferences across those freight demand types. This study utilizes the Path Size Logit Model to explore the characteristics of preferred route across long-haul, medium-haul, and short-haul trips, and reveal the underlying route choice mechanism behind enormous trucking activities. By employing truck GPS data from China, we find that (1) although the characteristics of preferred routes vary across long-haul, medium-haul, and short-haul trips, those trips collectively reflect full consideration of travel efficiency, safety, and reliability; (2) all these freight demand types incline to the routes with shortest travel distances instead of those with shortest travel time, while short-haul trips exhibit the highest sensitivity to travel distance; (3) drivers in both long-haul and medium-haul trips favor routes that combine motorways and sub-arterial roads, while long-haul trips present higher sensitivity; (4) drivers in short-haul trips show preferences for routes featuring fewer turns, and sub-arterial roads given last-mile delivery demand. Finally, we propose suggestions for designing urban truck route network to accommodate diverse freight demand in high-density urban areas with limited road resources.

Authors: Dr. Anne Goodchild, Zhengtao Qin, Ruixu Pan, Chengcheng Yu, Tong Xiao, Chao Yang, Quan Yuan (Tongji University)
Recommended Citation:
Qin, Zhengtao and Pan, Ruixu and Yu, Chengcheng and Xiao, Tong and Yang, Chao and Goodchild, Anne and Yuan, Quan, Choosing My Own Path: Revealing Differences in Route Choice Preferences Across Long-Haul, Medium-Haul, and Short-Haul Trucking. http://dx.doi.org/10.2139/ssrn.4853521
Paper

GPS Truck Data Performance Measures Program in Washington State

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

The Washington State Department of Transportation (WSDOT), Transportation Northwest at the University of Washington (UW), and the Washington Trucking Associations (WTA) have partnered on a research effort to collect and analyze global positioning systems (GPS) truck data from commercial, invehicle, truck fleet management systems. This effort was funded by the Washington State Legislature, and its purpose is to develop a statewide freight performance measures program for use by WSDOT. This document reviews the program’s previous phases and provides details about the latest phase of the program. The report also provides references to the technical documents that support the program.

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.
Student Thesis and Dissertations

Economic Implications of the Use of Technology in Commercial Vehicle Operations

Publication Date: 2012
Summary:

The effective and efficient movement of freight is essential to the economic well-being of our country but freight transport also adversely impacts our society by contributing to a large number of crashes, including those resulting in injuries and fatalities. Technology has been used increasingly to facilitate safety and operational improvements within commercial vehicle operations, but motor carriers operate on small profit margins, limiting their ability to make large investments without also seeing an economic benefit from such technologies. This dissertation explores the economic implications associated with using onboard monitoring systems to enhance safety in commercial vehicle operations.

First, to better understand how electronic on-board systems work, paper-based methods of recording driver hours of service are compared to automated (or electronically recorded) hours of service for three motor carriers using process analysis. This analysis addressed the differences between manual (paper-based) and electronic methods of recording hours of service, specifically as they relate to the frequencies and magnitude of the errors. Potential errors are categorized by operations within an information-based process and the findings suggest that a reduction of errors can be achieved with an electronic system.

A benefit-cost analysis provides a better understanding of the economic implications of onboard monitoring systems from the perspective of the carrier. In addition to the benefits of reduced crashes, benefits associated with electronic recording of hours of service, reduced mileage, and reduced fuel costs are considered. A sensitivity analysis is used and demonstrates that on-board monitoring systems are economically viable under a wide range of conditions. Results indicate that, for some fleet types, reducing crashes and improving hours of service recording, provides a net benefit of close to $300,000 over the five-year expected lifespan of the system. Furthermore, when exploring additional benefits such as reduced fuel consumption and reduced vehicle miles, benefits can be upwards of seven times more than safety-related benefits. This research also shows that net positive benefits are possible in large and small-sized fleets. Results can be used to inform policies for motivating or mandating carriers to use such systems and to inform carriers regarding the value of system investment.

Authors: Kelly A. Pitera
Recommended Citation:
Pitera, Kelly Ann. "Economic Implications of the Use of Technology in Commercial Vehicle Operations." PhD diss., 2012.
Thesis: Array
Paper

Evaluating the Accuracy of GPS Spot Speeds for Estimating Truck Travel Speed

 
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Publication: Transportation Research Record
Volume: 2011
Pages: 101–110
Publication Date: 2011
Summary:

A number of trucking companies use Global Positioning System (GPS) devices for fleet management. Data extracted from these devices can provide valuable traffic information such as spot (instantaneous) speeds and vehicle trajectory. However, the accuracy of GPS spot speeds has not been fully explored, and there is concern about their use for estimating truck travel speed. This concern was addressed by initially comparing GPS spot speeds with speeds estimated from dual-loop detectors. A simple speed estimation method based on GPS spot speeds was devised to estimate link travel speed, and that method was compared with space mean speed estimation based on GPS vehicle location and time data. The analysis demonstrated that aggregated GPS spot speeds generally matched loop detector speeds and captured travel conditions over time and space. Speed estimation based on GPS spot speeds was sufficiently accurate in comparison with space mean speeds, with a mean absolute difference of less than 6%. It is concluded that GPS spot speed data provide an alternative for measuring freight corridor performance and truck travel characteristics.

Authors: Dr. Anne GoodchildDr. Ed McCormack, Wenjuan Zhao
Recommended Citation:
Zhao, Wenjuan, Anne V. Goodchild, and Edward D. McCormack. "Evaluating the accuracy of spot speed data from global positioning systems for estimating truck travel speed." Transportation Research Record 2246, no. 1 (2011): 101-110.
Paper

GPS Tracking of Freight Vehicles to Identify and Classify Bottlenecks

Publication: Intelligent Transportation Systems (ITSC), 2012 15th International IEEE Conference
Publication Date: 2012
Summary:

This paper presents a systematic methodology for identifying and ranking bottlenecks using probe data collected by commercial GPS fleet management devices. This methodology is based on the hypotheses that truck speed distributions can be represented by either a unimodal or bimodal probability density function, and it proposes a new reliability measure for evaluating roadway performance.

Authors: Dr. Ed McCormack, Wenjuan Zhao, Daniel J. Dailey
Recommended Citation:
McCormack, E., Zhao, W., & Dailey, D. J. (2012, September). GPS Tracking of Freight Vehicles to Identify and Classify Bottlenecks. In 2012 15th International IEEE Conference on Intelligent Transportation Systems (pp. 1245-1249). IEEE.
Student Thesis and Dissertations

Economic Characteristics of Drayage Drivers at the Port of Seattle

Publication Date: 2014
Summary:

The Port of Seattle surveyed drayage truckers serving the port in 2006, 2008, and surveyed drivers again in 2013 in partnership with the University of Washington. This thesis describes the methodology used to survey drayage drivers at the Port of Seattle, describes the economic conditions of drayage drivers at the port and changes in economic conditions since previous surveys, and attempts to model driver earnings based on other driver characteristics.

By increasing the number of days that the survey was distributed, and by soliciting driver feedback to make the survey understandable and relevant to drivers, the 2013 survey was able to gather a larger survey size than previous efforts (290 responses in 2013, compared to 99 responses in 2008 and 167 responses in 2006).

From 2008 to 2013, there was a reduction in the number of drivers working five or more days per week, from 80% in 2008 to 70% in 2013. The percentage of drivers doing work other than port trucking has increased from 8% in 2008 to 37% in 2013. Findings suggest that due to changing conditions at the Port of Seattle, there is a growing population of drivers that do port trucking as a part-time job in combination with other forms of work, rather than a full-time occupation.

Attempts at modeling driver earnings based on other factors (English as a second language, trip type, doing work other than port trucking, and average hours worked per week) did not discover strong relationships between these factors and earnings. It is recommended that future efforts in this area use higher resolution earnings data than the data available from the 2013 survey.

Authors: Jerome Drescher
Recommended Citation:
Drescher, Jerome (2014). Economic Characteristics of Drayage Drivers at the Port of Seattle, University of Washington Master's Degree Thesis.
Thesis: Array
Paper

Processing Commercial GPS Data to Develop Web-Based Truck Performance Measure Program

 
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Publication: Transportation Research Record
Volume: 2011
Pages: 92–100
Publication Date: 2011
Summary:

Although trucks move larger volumes of goods than other modes of transportation, public agencies know little about their travel patterns and how the roadway network performs for trucks. Trucking companies use data from the Global Positioning System (GPS) provided by commercial vendors to dispatch and track their equipment. This research collected GPS data from approximately 2,500 trucks in the Puget Sound, Washington, region and evaluated the feasibility of processing these data to support a statewide network performance measures program. The program monitors truck travel time and system reliability and will guide freight investment decisions by public agencies. While other studies have used a limited number of project-specific GPS devices to collect frequent location readings, which permit a fine-grained analysis of specific roadway segments, this study used data that involved less frequent readings but that were collected from a larger number of trucks for more than a year. Automated processing was used to clean and format the data, which encompassed millions of data points. Because a performance measurement program ultimately monitored trips generated by trucks as they travel between origins and destinations, an algorithm was developed to extract this information and geocode each truck’s location to the roadway network and to traffic analysis zones. Measures were developed to quantify truck travel characteristics and performance between zones. To simplify the process and provide a better communications platform for the analysis, the researchers developed a Google Maps-based online system to compute the measures and show the trucks’ routes graphically.

Authors: Dr. Ed McCormack, Xiaolei Ma, Yinhai Wang
Recommended Citation:
Ma, Xiaolei, Edward D. McCormack, and Yinhai Wang. "Processing commercial global positioning system data to develop a web-based truck performance measures program." Transportation Research Record 2246, no. 1 (2011): 92-100.
Article

Developing Roadway Performance Measures Using Commercial GPS Data from Trucks

 
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Publication: Institute of Transportation Engineers. ITE Journal,
Volume: 84(6)
Pages: 36-40
Publication Date: 2014
Summary:
Global positioning system (GPS) devices that are installed in trucks and used for fleet management are increasingly common. Raw data from these devices present an opportunity for public agencies to use these trucks as probe vehicles to better monitor roadway operations and to quantify transportation system efficiency. Several North American programs have demonstrated that these truck GPS data can be used for a variety of performance measurement applications including locating roadway bottlenecks for trucks, providing travel reliability data, and informing planning and engineering processes. This paper discusses why these private sector GPS truck data are available, suggests how a public agency might acquire these data, provides some examples of the use of these data by transportation organizations, and covers some of the steps needed to make the GPS useful. In a performance measurement program, the GPS-equipped trucks are a small subset of all trucks on the network.

 

 

Recommended Citation:
McCormack, E. (2014). Developing Roadway Performance Measures Using Commercial GPS Data from Trucks. Institute of Transportation Engineers. ITE Journal, 84(6), 36-40.
Student Thesis and Dissertations

Truck GPS Data in Freight Planning: Methodologies and Applications for Measurement and Forecasting

Publication Date: 2014
Summary:

Efficient and reliable goods movement via our nation’s highway system is critical to the nation’s economy and quality of life. Truck mobility is one of the key performance measures for evaluating the conditions of goods movement and supporting freight planning. Truck GPS data can be useful in developing truck mobility measures and providing insights into freight planning. This dissertation employs truck GPS data and proposes a set of methodologies for measuring and forecasting truck mobility performance, with particular emphases on truck travel time and travel time reliability. It also examines how GPS data can be used to support freight planning, using the analysis of impacts of a tolling project on truck mobility and routing as a case study. The first part of this dissertation investigates how to measure truck travel time reliability given the characteristics of GPS data. An improved spot-speed distribution based travel time reliability measure is proposed. The proposed approach is compared with a number of commonly applied reliability measures. The correlations among these measures reveal that the reliability measures are not highly correlated, demonstrating that different measures provide different conclusions for the same underlying data and traffic conditions. The author presents recommendations of the appropriate measures for different applications. Quantitative freight project prioritization processes require both pre- and post-investment truck mobility performance. Therefore, the second part of this dissertation develops quantitative methods for forecasting truck specific travel time and travel time reliability. For travel time prediction, a speed-density based approach is proposed to predict truck travel time associated with segment density changes. Traffic regimes are segmented using a cluster analysis approach. The travel time estimates are compared with two widely applied traditional methodologies. The results demonstrate that the proposed method is able to estimate more accurate travel times. For reliability prediction, we analyze the changes of GPS spot speed distribution in response to different traffic conditions. A relationship between truck spot speed distribution coefficient of variation and segment density is proposed to forecast reliability. The approach is transferrable and sheds a light on forecasting travel time reliability. The third part of this dissertation focuses on examining how GPS data can be used to assist freight planning. The SR-520 toll bridge in the City of Seattle, Washington is selected as the case study. We quantify the toll project impacts on truck mobility and route choice. Truck GPS data is used to evaluate route choice and travel speed along SR-520 and the alternate toll-free route I-90. A logit model is developed to determine the influential factors in truck routing. The results indicate that travel time, travel time reliability and toll rate are all influential factors during both peak and off-peak periods. The values of truck travel time during different time periods are estimated, and the values vary with the definition of peak and off-peak periods. This dissertation provides decision makers with useful guidance and information on using GPS data for truck mobility measurement and forecasting. It also demonstrates the capability of GPS data in supporting freight planning.

Authors: Zun Wang
Recommended Citation:
Wang, Zun (2014). Truck GPS Data in Freight Planning: Methodologies and Applications for Measurement and Forecasting. University of Washington Doctoral Dissertation.
Thesis: Array
Paper

Using Truck Probe GPS Data to Identify and Rank Roadway Bottlenecks

 
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Publication: American Society of Civil Engineers (ASCE) Journal of Transportation Engineering
Volume: 139(1)
Pages: 7-Jan
Publication Date: 2013
Summary:

This paper describes the development of a systematic methodology for identifying and ranking bottlenecks using probe data collected by commercial global positioning system fleet management devices mounted on trucks. These data are processed in a geographic information system and assigned to a roadway network to provide performance measures for individual segments. The authors hypothesized that truck speed distributions on these segments can be represented by either a unimodal or bimodal probability density function and proposed a new reliability measure for evaluating roadway performance. Travel performance was classified into three categories: unreliable, reliably fast, and reliably slow. A mixture of two Gaussian distributions was identified as the best fit for the overall distribution of truck speed data. Roadway bottlenecks were ranked on the basis of both the reliability and congestion measurements. The method was used to evaluate the performance of Washington state roadway segments, and proved efficient at identifying and ranking truck bottlenecks.

Authors: Dr. Ed McCormack, Wenjuan Zhao, Daniel J. Dailey, Eric Scharnhorst
Recommended Citation:
Zhao, Wenjuan, Edward McCormack, Daniel J. Dailey, and Eric Scharnhorst. "Using truck probe GPS data to identify and rank roadway bottlenecks." Journal of Transportation Engineering 139, no. 1 (2012): 1-7.