No abstract

Plug-in hybrid electric vehicles (PHEVs) offer the potential to significantly reduce greenhouse gas emissions, if vehicle consumers are willing to adopt this new technology. Consequently, there is much interest in exploring PHEV market penetration models. In prior work, we developed an agent-based model (ABM) of potential PHEV consumer adoption that incorporated several spatial, social, and media influences to identify nonlinear interactions among potential leverage points that may impact PHEV market penetration. In developing that model, the need for additional data to properly inform both the decisionmaking rules and agent initialization became apparent. To address these issues, we recently conducted and analyzed an extensive consumer survey; in this paper, we modify the ABM to reflect the survey findings. A unique aspect is a one-to-one correspondence between agents in the model and survey respondents, and thus yielding distributions and cross correlations in agent attributes that accurately reflect the survey population. We also implement a used-PHEV market, and allow agents to purchase new or used compact PHEVs or vehicles of their current type. Based on our prior survey response analysis, our modified model includes a PHEV-technology threshold component, a multinomial logistic prediction of willingness to consider a compact PHEV based on dynamically changing attitudes, and agent-specific delay discounting functions that predict the amount agents are willing to pay up front for greater fuel savings. We thus independently account for agents' discomfort with the new PHEV technology, their desire to drive a more environmentally friendly vehicle, and their willingness to pay a higher sticker price for a PHEV. Results of ten survey-based ABM scenarios are reported with implications for policy-makers and manufacturers. We believe close integration of the design of consumer surveys and the development of ABMs is a key step in developing useful decision-support models; this paper serves as an example of one way to achieve that.INDEX TERMS Plug-in hybrid electric vehicles (PHEVs), agent-based model, market penetration, electric vehicle adoption, vehicle choice simulation, vehicle choice survey.

Created in 1978, the Solid Waste Authority of Palm Beach County (Authority) has developed an “award winning” solid waste management system that includes franchised solid waste collections and the following facilities to service the residents and businesses in Palm Beach County, Florida: • North County Resource Recovery Facility (NCRRF); • Residential and Commercial Recovered Materials Processing Facility; • Five Transfer Stations; • Class I Landfill; • Class III Landfill; • Biosolids Pelletization Facility; • Ferrous Processing Facility; • Woody Waste Recycling Facility; • Composting Facility; and • Household Hazardous Waste Facility. The Authority has proactively planned and implemented its current integrated solid waste management program to ensure disposal capacity through 2021. However, like many communities, the Authority anticipates continued population growth and associated new development patterns that will significantly increase demands on its solid waste system, requiring it to reevaluate and update its planning to accommodate future growth. The NCRRF, the Authority’s refuse derived fuel waste-to-energy facility, has performed very well since its start up in 1989 processing over 13 million tons of MSW, saving valuable landfill space and efficiently producing clean, renewable energy. As the NCRRF approached the end of its first 20 year operating term, it became necessary to complete a comprehensive refurbishment to ensure its continued reliable service for a second 20 year term and beyond providing for continued disposal capacity and energy production for the Authority’s customers. The Authority renegotiated and extended its operating agreement with the Palm Beach Resource Recovery Corporation (PBRRC), a Babcock & Wilcox Company, for an additional 20-year term. The Authority selected BE&K Construction Company (BE&K) and entered into an Engineering, Procurement, and Construction contract (EPC Contract) to perform the refurbishment. The Authority, with assistance from its Consulting Engineer, Malcolm Pirnie, Inc., developed the minimum technical requirements and negotiated the EPC Contract with BE&K. The design and procurement efforts were completed in early 2009 and on-site construction refurbishment activities commenced in November 2009. The refurbishment has a total estimated cost of $205 million. The refurbishment work is sequenced with the intent that one boiler train will remain operational to reduce the impact to the Authority’s landfill and maximize electrical production and revenues during the refurbishment period. This presentation will focus on the improvements to operations as a result of the refurbishment and its positive effects on the Authority’s integrated solid waste management system.

We present a real-world application utilizing a Genetic Algorithm (GA) for exploratory multivariate association analysis of a large consumer survey designed to assess potential consumer adoption of Plug-in Hybrid Electric Vehicles (PHEVs). The GA utilizes an intersection/union crossover operator, in conjunction with high background mutation rates, to achieve rapid multivariate feature selection. We experimented with two alternative fitness measures based on classification results of a naïve Bayes quadratic discriminant analysis; one fitness function rewarded only for correct classifications, and the other penalized for the degree of misclassification using a quadratic penalty function. We achieved high classification accuracy for three different survey outcome questions (with 3-, 5-, and 7-outcome classes, respectively). The quadratic penalty function yielded better overall results, returning smaller feature sets and overall more accurate contingency tables of predicted classes. Our results help to identify what consumer attributes best predict their likelihood of purchasing a PHEV. These findings will be used to better inform an existing agent-based model of PHEV market penetration, with the ultimate aim of helping auto manufacturers and policy makers identify leverage points in the system that will encourage PHEV market adoption.