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In this paper an estimation is made of a joint household-level model of the number of vehicles owned by a household, the vehicle type choice of each vehicle, the annual mileage on each vehicle, and the individual assigned as the primary driver for each vehicle. A version of the proposed model system currently serves as the engine for a household vehicle composition and evolution simulator, which itself has been embedded in the larger Simulator of Activities, Greenhouse Emissions, Energy, Networks, and Travel (SimAGENT), an activity-based travel and emissions forecasting system for the Southern California Association of Governments planning region.

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The population of Jerusalem, Israel, can be divided into three distinct ethnic sectors: secular Jewish, ultra-Orthodox Jewish, and Arab. Not only do these population sectors tend to inhabit and work in different areas of the city, but they each have unique household structures, activity patterns, mobility tendencies, and, ultimately, travel behavior. These substantial variations in behavior, largely driven by differences in culture and lifestyle that are not captured by other personal characteristics, are essential to representing travel behavior in the Jerusalem travel model. In this paper, sector differences were traced through the activity-based travel demand model framework by using the 2010 Jerusalem Household Travel Survey. Significant variations in behavior were seen both in direct relation to the population sector and in interactions with other socioeconomic and demographic characteristics such as income and gender. This is the first known travel demand model in practice to incorporate ethnic differences so extensively in its application.

Most modern activity-based travel demand models (ABMs) in practice and research do not fully capture the central idea that travel is derived from activities. The basic unit adopted in ABMs for travel analysis is the tour, which is borrowed largely from tour-based travel demand models. To a certain extent, this approach contradicts the basic idea of ABMs in which the unit for travel analysis is the activity. In reality, individuals plan to participate in various activities in a day, and the tours and corresponding trips emerge from activity participation, potential activity location, and activity sequence choices coupled with time and space constraints imposed by activities with relatively lower spatial and temporal flexibility. The model discussed in this paper is an effort to better mimic this decision-making process. This model is a part of the latest version of the coordinated travel and regional activity modeling platform (CT-RAMP) adopted for the Jerusalem, Israel, and Phoenix, Arizona, ABMs.