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.

To better understand the interactions between physical built environment conditions and one’s well-being, we created a passive data collector for travellers and made the first step towards an explanatory model based on psychophysiological relations. By measuring biometric information from select trial participants we showed how different controlled factors are affecting the heart rate of the participants. A regression model with the impact factors such as speed, location, time and activity (accelerometer data) reveals how the factors relate to each other and how they correlate with the recorded individual’s heart rates throughout the observed period. For examples, the results show that the increase in movement speed is not linearly correlated with the heart rate. One’s heart rate would increase significantly when the individual reaches brisk walking and running speed, but not before nor after. Early morning and early evening time slots were the time where the observed individuals have the highest heart rates, which may correlate to individuals’ commute activities. Heart rates at the office would be lower than at home, which might correlate to more physical activities in the household. 

This study aimed to provide a multiangled comparison of the impact of real and virtual setups on the behaviour and perception of electric scooter (e-scooter) riding to examine the external validity of the virtual environments in the micro-mobility context. For this purpose, a within-subject design experiment was conducted to collect data on the behaviour of e-scooter riders. Furthermore, self-reported data on mental and physical demand as well as physiological data in the form of heart rate measurements and electroencephalography (EEG) were recorded to provide an additional insight into the behavioural results. The analysis was based on the multinomial logit model (MNL) for the behavioural data, ordered logit models for self-reported measures. Parametric and non-parametric tests were performed to capture the differences in physiological data. The results of the behavioural data showed significant differences in braking and acceleration patterns between virtual and real scenarios, which undermined the external validity of virtual environments in the current context. Further, self-reported measures painted a mixed picture when looked at jointly with biometric measures, where the questionnaires indicated that both setups were indifferent with respect to mental demand, while the physiological data suggested that virtual scenarios were more mentally engaging for the e-scooter riders.

Understanding how built environments affect travellers is crucial when building sustainable cities. Making big changes to the infrastructure requires substantial time and money. By instead performing changes in a virtual environment mimicking the target environment, allows testing scenarios in efficient ways before real-world implementation. In this work, psychophysiological indicators in form of biometric data have been used while e- scooter riders drove in virtual and real-world environments. With the rise of commercially available devices for recording electrocardiography (ECG) and electroencephalography (EEG), it is now possible to compare the built environment’s impacts on the participants with less intrusive measurement methods.

Results show that methods for collecting psychophysiological indicators seem promising. It might still be long until virtual scenarios are comparable with real-world ones. Utilising technologies as proposed in this paper enables mimicking reality by iteratively changing the virtual scenarios through rapid and cost-efficient test procedures, providing planners with powerful tools for understanding impact on travellers when designing environments.

Results also show that ECG seems more versatile than EEG given the scenarios analysed, where participants rode an e-scooter on track in both augmented virtuality (AV) simulator and real-world. Biometric data required less demographic information than subjective survey data, while providing seemingly similar results.

This paper aims to provide a cognitive perspective on the hazard perception process in the traffic situation based on the two theories of brain information processing, namely, Signal Detection Theory and Predictive Coding Theory. The theories are empirically validated in an augmented virtuality scenario encompassing a simplified traffic situation, where participants are faced with hazard cues characterised by a different degree of predictability. Throughout the experiment, the acceleration and braking behaviour of an e-scooter rider together with the electroencephalography data is collected. The developed experimental setup allows for testing the applicability of brain theories in explaining behaviour and cognitive processing of the perception of potential hazards. Current findings show that produced predictions and the subsequent behaviour are modulated by the degree of ambiguity of hazard cues in line with Signal Detection Theory. Following Predictive Coding Theory, the predictions improve as more external input is gathered and the mental model is updated. Moreover, the alpha wave is used as a neural marker of hazard predictability. The results provide implications for road safety researchers and practitioners to guide the more-informed design of road infrastructure as well as in-vehicle human support systems to be more aligned with the processing mechanisms of human cognition.

Recent advancements in computer graphics and human-computer interaction have made it possible to create traffic simulatorsthat contain complex environments for the participants to navigate. These can be used to understand how changes to theenvironment affect travellers without having to perform the changes in real life. There have also been improvements in how tocollect information about what the user is experiencing in these simulators. There is a wide range of variables that could be usedto better understand what the user is focusing on, but which of these are giving the most information?This paper aims to compare and uncover what the movements of the head and the eyes can explain regarding where a person isfocusing their attention when searching for information. Using a VR HMD with built-in eye-tracking, participants were asked tosearch for objects in static and dynamic environments. The results showed that eye-tracking had a higher hit rate than the headtracking,as expected. Information from the head-tracking was found in the eye-tracking to a higher degree than the eye-trackingwas found in the head-tracking across all scenarios. In conclusion, eye-tracking shows signs that it is the preferred method forunderstanding information searching among travellers.