An Agent-Based Model for Estimating Consumer Adoption of PHEV Technology

We present here a prototype of a spatially explicit and socially embedded agent based model to study plug-in hybrid vehicle (PHEV) penetration under a variety of scenarios. Heterogeneous agents decide whether or not to buy a PHEV by weighing environmental benefits and financial considerations (based on their personal driving habits, their projections of future gas prices, and how accurately they can compute lifetime fuel costs), subject to various social influences. Proof-of-concept results are presented to illustrate the types of questions which could be addressed by such a model, and how they may help to inform policy-makers and/or vehicle manufacturers. For example, our results indicate that simple web-based tools for helping consumers to more accurately estimate relative fuel costs could dramatically increase PHEV penetration. We identify new types of data that must be collected and future model extensions (including additional vehicle models, manufacturer and dealer agents, and up-scaling to larger regions) in order to make such a model more reflective of current and future U.S. vehicle consumers.