Utilising physiological data for augmenting travel choice models: methodological frameworks and directions of future research

Abstract

Recent technological and methodological advances have led to the possibility of a wider range of data being incorporated into travel choice models. In particular, physiological data such as eye-tracking information, skin conductance, heart rate recordings and electroencephalogram (EEG) have emerged as promising sources of information that could be used to gain insights into the decision-making process as well as the decision-maker's state of mind. However, research on methodologies to utilise these data sources and to integrate them with mobility data for advancing state-of-the-art travel behaviour models is still very limited. In this paper, we discuss the key benefits of using these emerging sources of physiological data, review applications of different types of physiological data and highlight their strengths and weaknesses. Particular attention is paid to two different generic frameworks for integrating these types of data into econometric choice models of travel behaviour. The first framework involves using physiological sensor data as indicators of latent variables while in the second framework, they are used as exogenous variables. We identify the research gaps and outline the directions for future methodological and applied research required to better utilise the physiological data for travel choice models.