Abstract
Travel surveys can uncover information regarding travel behaviour, needs, and more. Collected information is utilised to make choices when reorganising or planning built environments. Over the years, methods for conducting travel surveys have changed from interviews and forms to automated travel diaries in order to monitor trips made by travellers. With the fast progression of technological advancements, new possibilities for operationalising such travel diaries can be implemented, changing from utilising mobile to wearable devices. Wearable devices are often equipped with sensors which collect continuous biometric data from sources that are not reachable from standard mobile devices. Data collected through wearable devices range from heart rate and blood pressure to temperature and perspiration. This advancement opens new possible layers of information in the collection of travel data. Such biometric data can be used to derive psychophysiological conditions related to cognitive load, which can uncover in-depth knowledge regarding stress and emotions. This paper aims to explore the possibilities of data analysis on the data collected through a software combining travel survey data, such as position and time, with heartrate, to gain knowledge of the implications of such data. The knowledge about the implications of spatial configurations can be used to create more accessible environments.
Highlights
Travel surveys have been used for decades to observe patterns, locations, and choices made by travellers, in an attempt to understand their needs and behaviour [1,2]
One participant’s dataset which was most consistent and contained the most data points was chosen to be the dataset for the analysis part of this trial
The K-means clustering visualisations indicate that an increased amount of collected data points in an area give more opportunity for peak heart rates to be collected in the same area
Summary
Travel surveys have been used for decades to observe patterns, locations, and choices made by travellers, in an attempt to understand their needs and behaviour [1,2] By utilising this information, it is possible to make strategic planning decisions and monitor the realisations of such decisions. Recent technological advancement has led to the development of biometric sensors being implemented in consumer-grade hardware [9,10,11,12,13,14] This development means that biometric data become available in even more substantial quantities than before, since it is possible to create software implementing biometric data collection for widely available platforms, such as Android Wear [30] and watchOS [31]. But are not limited to, accelerometers and gyroscopic sensors (from here on referred to as “motion sensors”) for motion detection, ECG and/or
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