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- 저자 : Stephen G. Ritchie (검색결과 2 건)
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A GPS Data Processing Framework for Analysis of Drayage Truck Tours
Soyoung Iris You,Stephen G. Ritchie 대한토목학회 2018 KSCE Journal of Civil Engineering Vol.22 No.4
A Clean Trucks Program (CTP) has been enacted at California’s San Pedro Bay Ports (SPBP) of Long Beach and Los Angeles, tohelp address major environmental issues associated with port operations. “Clean trucks” (meeting 2007 model year emissionstandards) that utilized public funds to replace older, polluting drayage trucks were required to be fitted with GPS units forcompliance monitoring, with an expectation that freight truck movements could be investigated more precisely. Such implementationalso served as a prototype of emerging smart freight mobility concepts, which are often heavily data-driven processes, but whichshould provide data and insights that are useful to both researchers and practitioners. Accordingly, this paper reports on research todevelop a comprehensive framework for processing SPBP clean truck GPS data, to both interpret tour behavior of clean drayagetrucks, and to prepare sufficient tour data for clean truck modeling at the SPBP. An important finding is that clean trucks at the SPBPhave distinct tour characteristics. First, most completed a tour within one day, but one day of travel behavior is not necessarilyrepresentative of any other day. Second, the identified tour types contain repetitive trip patterns while other commercial trucks mostlytend to travel as circulative patterns. These insights into clean truck behavior at the SPBP potentially provide more accuratedepictions of current conditions and better projections of future conditions for freight related improvement plans and models.
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Inverse vehicle routing for activity-based urban freight forecast modeling and city logistics
You, Soyoung Iris,Chow, Joseph Y. J.,Ritchie, Stephen G. Taylor Francis 2016 Transportmetrica. A, Transport Science Vol.12 No.7
<P>Goods movement is one of the fastest growing transportation sectors, affecting both economic and environmental sustainability, particularly in dense urban areas with traffic congestion and air pollution. To meet this challenge, urban public agencies have paid attention to policies and systems to facilitate efficient and sustainable city logistics. This paper proposes a modeling framework to consider both spatial-temporal constraints and a means to calibrate the model from observable data, based on an adaptation of an activity-based passenger model called the household activity pattern problem. Conceptual comparisons with a state-of-the-art freight forecasting methodology are made using an example. Application of the model is illustrated through formulating and implementing a Sequential Selective Vehicle Routing Problem associated with drayage truck activities at the San Pedro Bay Ports in Southern California.</P>
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