Publications

Summary:
The Clean Trucks Program is a Clean Air Action Plan initiative currently being adopted by the Ports of Los Angeles and Long Beach. This paper examines each of the Clean Trucks Program’s current requirements and estimates the impact on terminal operations. Using terminal operations data supplied by three terminal operating companies, we conduct a simple queuing analysis and present a regression model which allow us to consider the potential impact of the policy changes.

Summary:
The Clean Trucks Program is a Clean Air Action Plan initiative currently being adopted by the Ports of Los Angeles and Long Beach. This paper examines the Clean Trucks Program’s current requirements and estimates the impact on terminal operations. Using terminal operations data supplied by three terminal operating companies, we conduct a simple queuing analysis and present a regression model that allows us to consider the potential impact of the policy changes.

Summary:
Loading ships as they are unloaded (double cycling) can improve the efficiency of a quay crane and container port. This paper describes the double-cycling problem, and presents solution algorithms and simple formulae to determine reductions in the number of operations and operating time using the technique. We focus on reducing the number of operations necessary to turn around a row of a ship. The problem is first formulated as a scheduling problem, which can be solved optimally.

Summary:
A case study of the University of Washington Mailing Services, which operates a heterogeneous fleet of vehicles, provides insight into the impact of operational changes on cost, service quality, and emissions. An emissions minimization problem was formulated and solutions were identified with a creation and local search algorithm based on the I1 and 2-opts heuristics.

Summary:
Freight systems are a critical yet complex component of the transportation domain. Understanding the dynamic of freight movements will help in better management of freight demand and eventually improve freight system efficiency. This paper presents a series of data-mining algorithms to extract an individual truck’s trip-chaining information from multi-day GPS data.

Summary:
Predicting truck (heavy vehicle) travel time is a principal component of freight project prioritization and planning. However, most existing travel time prediction models are designed for passenger vehicles and fail to make truck specific forecasts or use truck specific data. Little is known about the impact of this limitation, or how truck travel time prediction could be improved in response to freight investments with an improved methodology.

Summary:
Truck probe data collected by global positioning system (GPS) devices has gained increased attention as a source of truck mobility data, including measuring truck travel time reliability. Most reliability studies that apply GPS data are based on travel time observations retrieved from GPS data. The major challenges to using GPS data are small, nonrandom observation sets and low reading frequency.

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.

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.

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.

Summary:
Despite their heavy use of the road transportation system, little data is available on trip generation rates for trucks. In this paper, truck trip rates from grocery stores are used in a case study to evaluate and compare two simple methods for collecting data on truck trip generation: telephone interviews and manual counts. The findings from this study showed that grocery stores generated an average of 18 truck trips per day on a typical peak period weekday. The results also...

Summary:
This paper documents the development of data collection methodologies that can be used to measure truck movements along specific roadway corridors in Washington State cost-effectively. The intent of this study was to design and test methodologies that could provide information to ascertain the performance of freight mobility roadway improvement projects. The benchmarks created would be used to report on speed and volume improvements that resulted from completed roadway projects.

Summary:
Many urban planning efforts have supported development in dense, mixed-use areas, but tools are not widely available to help understand the relationship between urban form and goods movement. A review is presented on the status of urban goods movement forecasting models to account for the impacts of density and mixed land use. A description is given of a series of forecasting model runs conducted with state-of-the-practice tools available at the Puget Sound Regional Council.

Summary:
Roadway tolls are designed to raise revenue to fund transportation investments and manage travel demand and as such may affect transportation system performance and route choice. Yet, limited research has quantified the impact of tolling on truck speed and route choice because of the lack of truck-specific movement data.

Summary:
Freight transport is a challenging economic sector, as it is essential for the functioning of production and distribution systems but and the same time is at the origin of many nuisances such as congestion, greenhouse gas emissions, pollution and noise. When responding to these issues, planners dispose nowadays of a growing body of freight data that can be used for the implementation of policies towards achieving smart mobility.