A Simulation-based Approach for Constructing All-day Travel Chains from Mobile Phone Data

Abstract

The purpose of this work is to investigate replacing travel diaries with sets of call detail records (CDRs) as inputs for an agent-oriented traffic simulation. We propose constructing an agent population directly from a CDR dataset and fusing it with link volume counts to reduce spatio-temporal uncertainty and correct for underrepresented traffic segments. The problem of finding a set of travel plans which realizes a set of CDR trajectories and is consistent with a set of link volume counts is rephrased in terms of calibrating a choice model. This enables us to make use of an existing calibration scheme for agent-oriented simulations. We demonstrate our approach by an illustrative scenario with synthetic data.

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