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Combining GPS Tracking and Surveys for a Mode Choice Model: Processing Data from a Quasi-Natural Experiment in Germany

Discussion Papers 2047, 26 S.

Heike Link, Dennis Gaus, Neil Murray, Maria Fernanda Guajardo Ortega, Flavien Gervois, Frederik von Waldow, Sofia Eigner

2023

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Abstract

This paper deals with the data generation process implemented for an analysis of the impact of the 9-Euro ticket on mode choice. We discuss the assumptions made and procedures used to process a raw dataset that is based on GPS traces of individuals’ movements and on survey data into the choice-set for a discrete choice model. Several steps of cleaning and merging are described in order to a) obtain a reliable dataset; b) define available modal alternatives with attributes such as distance, duration, and costs; and c) impute the travel purpose for each movement to form. Our main contribution is to show that a systematic analysis of the sample obtained at different stages of data processing is important to make sure that the final sample is unbiased. Furthermore, we contribute by analysing the difference between observed travel time and travel time calculated by routing tools such as Google Maps. We show that the often- employed approach of estimating RP based choice models on the basis of observed travel times for the chosen mode of transport but calculated travel times for the non-chosen alternatives can introduce a structural bias into the sample.

Neil Murray

Research Associate in the German Socio-Economic Panel study Department

Dennis Gaus

Research Associate in the Energy, Transportation, Environment Department

Heike Link

Research Associate in the Energy, Transportation, Environment Department



JEL-Classification: C55;C81;R41
Keywords: Data processing, travel behaviour, GPS traces, discrete choice models, revealed preferences

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