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Paper

Smart Growth and Goods Movement: Emerging Research Agendas

Publication: Journal Urbanism: International Research on Placemaking and Urban Sustainability
Volume: 2-Aug
Pages: 115-132
Publication Date: 2015
Summary:

While recent urban planning efforts have focused on the management of growth into developed areas, the research community has not examined the impacts of these development patterns on urban goods movement. Successful implementation of growth strategies has multiple environmental and social benefits but also raises the demand for intra-urban goods movement, potentially increasing conflicts between modes of travel and worsening air quality. Because urban goods movement is critical for economic vitality, understanding the relation between smart growth and goods movement is necessary in the development of appropriate policies.

This paper reviews the academic literature and summarizes the results of six focus groups to identify gaps in the state of knowledge and suggest important future research topics in five sub-areas of smart growth related to goods movement: (1) access, parking, and loading zones; (2) road channelization and bicycle and pedestrian facilities; (3) land use; (4) logistics; and (5) network system management.

Authors: Dr. Anne GoodchildDr. Ed McCormack, Erica Wygonik, Alon Bassok, Daniel Carlson
Recommended Citation:
Wygonik, Erica, Alon Bassok, Anne Goodchild, Edward McCormack, and Daniel Carlson. "Smart Growth and Goods Movement: Emerging Research Agendas." Journal of Urbanism: International Research on Placemaking and Urban Sustainability 8, no. 2 (2015): 115-132.
Paper

Reducing Train Turn Times with Double Cycling in New Terminal Designs

 
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Publication: Transportation Research Record: Journal of the Transportation Research Board
Volume: 2238
Pages: 14-Aug
Publication Date: 2011
Summary:

North American rail terminals need productivity improvements to handle increasing rail volumes and improve terminal performance. This paper examines the benefits of double cycling in wide-span gantry terminals that use automated transfer management systems. The authors demonstrate that the use of double cycling rather than the currently practiced single cycling in these terminals can reduce the number of cycles required to turn a train by almost 50% in most cases and reduce train turn time by almost 40%. This change can provide significant productivity improvements in rail terminals, increasing both efficiency and competitiveness.

Authors: Dr. Anne Goodchild, J. G. McCall, John Zumerchik, Jack Lanigan
Recommended Citation:
Goodchild, Anne, J. G. McCall, John Zumerchik, and Jack Lanigan Sr. "Reducing Train Turn Times with Double Cycling in New Terminal Designs." Transportation Research Record 2238, no. 1 (2011): 8-14.
Paper

Freeway Truck Travel Time Prediction for Freight Planning Using Truck Probe GPS Data

 
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Publication: European Journal of Transport and Infrastructure Research.
Volume: 16
Pages: 76-94
Publication Date: 2016
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. In light of this, this paper proposes a pragmatic multi-regime speed-density relationship based approach to predict freeway truck travel time using empirical truck probe GPS data (which is increasingly available in North American and Europe) and loop detector data. Traffic regimes are segmented using a cluster analysis approach. Two case studies are presented to illustrate the approach. The travel time estimates are compared with the Bureau of Public Roads (BPR) model and the Akçelik model outputs. It is found that the proposed method is able to estimate more accurate travel times than traditional methods. The predicted travel time can support freight prioritization and planning.

Recommended Citation:
Wang, Zun, Anne V. Goodchild, and Edward McCormack. "Freeway truck travel time prediction for freight planning using truck probe GPS data." European Journal of Transport and Infrastructure Research 16, no. 1 (2016).