The procedure for estimating a household model of mode choice is described. The tour-based mode choice model incorporates interpersonal interactions within the household explicitly in an agent-based random utility modeling framework. Household interactions include vehicle allocation, ridesharing to joint activities, and drop-off and pickup. Because of the complex nature of the model decision structure, choice probabilities are simulated from direct generation of random utilities rather than through an analytical probability expression. The computational requirements for the simulation are large. Therefore a grid of computers is used in parallel to perform the necessary calculations and a genetic algorithm is used for parameter estimation. A brief description of the model, the full model results, and a discussion of the computational techniques used in parameter estimation are presented.

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Figure 1: A generic Vega specification is automatically partitioned by the VegaFusion Planner into a runtime specification for the VegaFusion Middleware (describing operations on large datasets) and a client specification for Vega (describing the visualization of the output of these operations as well as client-side interactions). The Middleware dynamically responds to interaction signals from Vega by querying an out-of-browser, natively-compiled VegaFusion Runtime instance and relaying the results back to Vega. The pseudocode on the right illustrates a typical partition for a brushed histogram specification, including the dependencies between data and signals.