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.
Activities of commercial vehicles just before or just following international border crossings are not well understood. Logistical responses to border crossings are believed to increase miles traveled empty, total travel times, and total vehicle emissions.
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.
Smart growth design, a strategy for improving the quality of life in urban areas, has typically focused on the areas of passenger travel, land use and nonmotorized transport adoption. The role of goods movement is often ignored in discussions of smart growth. This article reports on National Cooperative Freight Research Program (NCFRP) Report 24, which addresses the importance of the relationship between smart growth and goods movement.
While researchers have found relationships between passenger vehicle travel and smart growth development patterns, similar relationships have not been extensively studied between urban form and goods movement trip making patterns. In rural areas, where shopping choice is more limited, goods movement delivery has the potential to be relatively more important than in more urban areas.
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.
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 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.
Shippers and motor carriers are impacted by and react differently to travel time variability due to their positions within the supply chain and end goals. Through interviews and focus groups these differences have been further examined. Shippers, defined here as entities that send or receive goods, but do not provide the transportation themselves, are most often concerned with longer-term disruptions, which are typically considered within the context of transportation system resilience.