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Abstract

Vehicle ownership decisions are central to estimates of emissions, gas tax revenues, energy security, pavement management, and other concerns. This work combines an auction-style microsimulation of vehicle prices and random-utility-maximizing choices, producing a market model for the evolution of new and used personal-vehicle fleets. All available vehicles compete directly, with demand, supply, and price signals endogenous to the model. The framework is described, analyzed, and implemented to show its capabilities in predicting outcomes of varying inputs. Application of the model system using Austin, Texas, survey data over a 20-year period highlight the model’s flexibility and reasonable response to multiple inputs, as well as potential implementation issues.

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