Vehicle availability significantly affects household travel behaviors and consequently affects the requirements for modeling and forecasting of household travel decisions under future or alternative scenarios. Household vehicle fleets are not acquired instantaneously, but evolve over time as a result of fleet transactions, which include vehicle (i) disposal or retirement, (ii) replacement and (iii) acquisition decisions. Parallel to this forecasting need, is the increasing diversification of household vehicle fleets from all gasoline vehicles fleets towards mixed-modal fleets that include alternative-fuel and non-motorized vehicles, such as EVs and bikes. This diversification provides the backdrop for the proposed exploratory study, which characterizes and models household vehicle transactions for non-motorized vehicles in addition to personal automobiles. To accomplish this overarching objective 

(i) a retrospective vehicle ownership and transaction survey is developed, guided by the recent Oregon Travel and Activity Survey (OTAS) dataset, and 
(ii) a set of econometric models for observed vehicle transactions that is
estimated with respect to the (a) duration between transactions and the (b) probability of transactions. 

The evolution of household vehicle fleets is important for assessing GHG emissions and the livability of communities, as households may move towards or away from more sustainable and "green" vehicle fleets due to life cycle changes, fluctuating transportation costs and household member migration decisions. The findings of the proposed work have implications for integrating household fleet evolution into existing travel demand forecasting tools. Additionally, the findings will help identify the most effective policy levers, such as household/workplace location parking supply, vehicle costs and attributes for positively influencing household fleet transactions towards more sustainable and livable options. 

This work extends the body of literature by considering the multi-modal vehicle transactions of households, more specifically motor vehicle transactions, and their relationship with transactions for other non-motorized vehicle types, such as bicycles.