Center for Infrastructure, Transportation, and the Environment (CITE)

Carlos

Behavioral Microsimulation (BMS)

By

A major component of the project is the development of a freight flow modeling tool to support the design and implementation of EEL initiatives. The Behavioral Microsimulation (BMS) is a custom-made computational system developed by RPI. The objective of the BMS is to assess the impacts of EEL initiatives by simulating all the tours required for delivering supplies to commercial establishments in a study area. The BMS considers a complete representation of the supply chain as shown in Figure 1, and the tours are simulated based on real life data about delivery stops and employment, as well as economic interconnections among industry sectors.
Figure 1: Supply Chain Interactions Modeled by the BMS
Figure 2 shows the main logic of the BMS. It uses real life data to simulate delivery tour. First, delivery tours are simulated for a base case, then they are simulated in scenarios considering the implementation of EEL initiatives. With the simulated delivery tours, it is possible to estimate indicators such as emissions, costs and VMT, and compare the indicators of the various scenarios with the base case.
Figure 2: Logic Behind the BMS
As an example of application of the BMS, it was used to assess land use initiatives in the Capital District. Three scenarios were considered:
  • Introduce a new distribution center in Colonie
  • Introduce a new distribution center in Amsterdam
  • Relocate an existing distribution center from Amsterdam to Colonie
Figure 3: Location of Colonie and Amsterdam Within the Capital District
Differences in VMT from base case and the three scenarios considered (Figure 4) were computed for different freight flows of the supply chain modeled by the BMS: from gateways to large establishments, from large establishments to other large establishments, and from large establishments to small establishments.
Results show that:
  • Locating the DC in a more central area (Colonie) generates less freight VMT than locating it in the outskirts of the area (Amsterdam)
  • The central position of Colonie allows shorter trips to reach other establishments in the area
  • A new DC in Colonie generates an increase of 2.89% in VMT of freight vehicles going from large establishments to other large establishments, while locating a new DC in Amsterdam increases VMT by 4.08%
  • The relocation of an existing DC from Amsterdam to Colonie reinforces that the central location is more adequate to reach commercial establishments in the Capital District, as it would cause the VMT of trips going from large establishments to other large establishments to decrease 1.02%.
Figure 4: Results of Simulating Land Use Initiatives in the Capital District

Catalog of Initiatives and Energy-Efficiency Framework

By

A key outcome of this project is to propose initiatives that have the highest potential at fostering Energy Efficient Logistics (EEL). In this sense, “initiatives” refer to projects, programs, regulations, policies, or other mechanisms that can help to achieve this goal. The purpose of the Catalog of EEL Initiatives is to characterize a wide spectrum of initiatives that can enhance freight energy efficiency. The catalog works as a state-of-the-art inventory of sustainable freight initiatives. The 52 initiatives presented in the catalog are based on the characterization of the supply chain going from supply-related to demand-related initiatives.
The initiatives can be classified into seven major categories with supply initiatives at one end and demand related/land use management related at the other. The seven groups of initiatives are:
  1. Infrastructure management
  2. Parking/loading areas management
  3. Vehicle-related strategies
  4. Traffic management
  5. Pricing, incentives, and taxation
  6. Logistical management
  7. Freight demand/ land use management
To qualitatively assess the degree to which the various initiatives could foster EELs, the team identified the various ways in which the initiatives could increase energy efficiency and created an energy efficiency framework tailored for freight transportation (Figure 1). The existing energy efficiency frameworks in the literature were developed for person-travel decisions and are not necessarily aligned with the decisions made in logistics. For instance, mode and travel (routing) are decisions made separately from the decision of mode choice.
Thus, the team proposes a framework that considers the following components of efficiency:
  • Vehicle efficiency
  • Travel efficiency (routing, driving and traffic)
  • Mode efficiency
  • Demand/land use efficiency
  • Network level efficiency
Figure 1: Framework for the Identification of Energy Efficient Initiatives
To facilitate the analyses of various initiatives, one-page summaries were created for each of the 52 initiatives included in the catalog. The one-pagers describe the attributes of the initiatives in terms of their potential contributions to EEL, and the factors that ought to be taken into account to assess feasibility for implementation. Figure 2 shows an example of one of the one-pagers.
Figure 2: Example of One-Pager From the Initatives Catalog

DOE: Energy-Efficient Logistics

By

The project “Collaborative Approaches to Foster Energy-Efficient Logistics in the Albany – New York City Corridor” is funded by the Department of Energy (DoE). It is done in collaboration with Argonne National Laboratory and George Mason University. The main goals of the project are:
  • Foster the adoption of Energy Efficient Logistics (EEL) along supply chains
  • Develop collaborative approaches between shippers, carriers and receivers
  • Induce carriers to incorporate energy efficient Technologies and Operations (Tech/Ops) and induce receivers to modify their demand patterns to exploit synergies with Tech/Ops
  • Develop analytical tools to estimate impact of EEL initiatives
  • Gain insight into ways to induce behavioral changes in the participants of supply chains
  • Foster the transformation of supply chains
At the current status of the project, the following tasks are either in progress or have been completed:
  • A new energy-efficiency framework tailored for freight transportation was developed, and a catalog of initiatives to foster energy-efficient logistics was produced.
  • A behavioral microsimulation (BMS) that models freight activity and supply chain’s interactions to assess the effectiveness of EEL initiatives is in progress.
  • A traffic simulation to assess the impacts of changing working hours of a port on the fuel consumption of all vehicles in the area of the port was produced.
  • Archival GPS data was acquired to estimate baseline conditions of emissions and fuel consumption in the Albany-New York City corridor.
  • A multi-method qualitative/quantitative approach compounded of in-depth interviews, behavioral surveys and behavioral modelling is being developed to identify which are the freight management strategies are most likely to be used by receivers, receivers and carriers.
  • Surveys to households were implemented to gain insight on consumers’ perception of management strategies to make e-commerce deliveries more energy efficient.
For detailed information about the tasks of the project click on the following links: