Estimating the perturbed utility route choice model with individual-level data

Abstract

We provide an estimator for the perturbed utility route choice (PURC) model that works with data at the level of individual trips. The estimator, labeled microPURC, is a nested fixed point algorithm that combines a bias-corrected linear regression problem with the individual-level perturbed utility maximization problem. We establish the statistical properties of the microPURC estimator and confirm these results with an experiment using simulated data. We then [this is work in progress] apply the microPURC estimator to a dataset from the ongoing Danish national road pricing experiment. This comprises a large number of individual trip trajectories, the national road network, and a choice set that includes all possible paths through the network.