This paper quantifies the benefits to drayage trucks and container terminals from a data-sharing strategy designed to improve operations at the drayage truck-container terminal interface. This paper proposes a simple rule for using truck information to reduce container rehandling work and suggests a method for evaluating yard crane productivity and truck transaction time.
This study employs a multilevel model to compare the influence of land use on transportation emissions in urban and suburban areas when considering trip speed and vehicle characteristics.
Purpose: To provide insight into the role and design of delivery services to address CO2, NO x , and PM10 emissions from passenger travel.
This paper introduces a novel quay crane design, double girder bridge crane (DGBC). DGBC is capable of handling containers of two adjacent bays simultaneously, avoiding crane collisions, saving travelling and reposition cost, and eventually improving terminal efficiency. This problem is formulated as a resource-constrained project scheduling with objective to minimize the maximum completion time.
Increasingly, private sector trucks are equipped with global positioning system devices for business efficiency. Acquiring data from these devices provides public transportation organizations with an opportunity to quantify roadway performance. There are challenges due to privacy concerns and data processing requirements. Several organizations have addressed these challenges and have successful performance measurement programs.
As available data have increased and as the national transportation funding bills have moved toward objective evaluation, departments of transportation (DOTs) throughout the United States have begun to develop tools to attempt to measure the effects of different projects. Increasingly, DOTs recognize that the freight transportation system is necessarily multimodal. However, no DOTs have clearly stated objective tools with which to evaluate multimodal freight project comparisons.
Travel demand models are used to aid infrastructure investment and transportation policy decisions. Unfortunately, these models were built primarily to reflect passenger travel and most models in use by public agencies have poorly developed freight components. Freight transportation is an important piece of regional planning, so regional models should be improved to more accurately capture freight traffic.
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.
Currently, knowledge of actual freight flows in the US is insufficient at a level of geographic resolution that permits corridor-level freight transportation analysis and planning. Commodity specific origins, destinations, and routes are typically estimated from four-step models or commodity flow models. At a sub-regional level, both of these families of models are built on important assumptions driven by the limited availability of data.
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.