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Age-related cognitive diseases are becoming a growing problem in Sweden. With the fast ageing population and lowered mortality rate comes the spread of cognitive diseases related to dementia. In order to accommodate this growing target group in transport and the built environment, it is crucial to understand the mobility and travel behaviour of patients suffering from these diseases. However, the adopted techniques to uncover travel behaviour of today do not allow for errors caused by cognitive impairment, since they require retrospective validation. Such design choices make it hard to understand how to improve the environment to accommodate the target group. Recently, technologies have emerged that allow for new design methods which can be beneficial for the said target group. This paper aims to address the issue of how to collect and analyse data regarding the mobility of the target group, and roles of the built environment in affecting their behaviour. A literature review has been conducted to 1) uncover the state of the art of the technologies and design methods that relate to automated data collection about the travel behaviour, 2) understand the limits of the user related to software interaction and, in turn, data collection and 3) find possibilities for new solutions to collect travel data from patients who have dementia., This work is currently under review for the special issue “Smart Technologies and Urban Life: A Behavioural and Social Perspective” of the journal “Sustainable Cities and Society”.QC 20191022

As the population grows older, age-induced illnesses related to cognitive impairments arise. Little is known regarding what and how the built environment affects that target group. It is theorized that external factors in the built environment might play a part in elderlies getting lost because of conditions related to illnesses such as dementia. To accommodate the target group in a future society, it is crucial to understand any possible correlation between locations and psychophysiological conditions. Technological advancements of wearable devices allow for the creation of software that collects data relevant to location as well as biometric data automatically, without affecting the user. By utilising consumer-grade hardware, it is possible to scale up the studies that the software allows for indefinitely. This paper covers the development of such a tool, by detailing what has become possible because of previous advancements in research regarding automatic travel diaries and the recognition of psychophysiological conditions through biometric data collection. Initial testing shows, that while data can be collected as proposed, there are drawbacks in terms of run time due to the battery capacity of wearable devices. More data is required to indicate whether the data collected can be used for correlation and causality analysis., This work is currently under review for the journal “Human-Computer Interaction”.QCR 20191022

The utilisation of travel surveys can uncover layers of information regarding travel behaviour, travel needs, and more. The collected information is utilised to make strategic planning choices when reorganising or planning new built environments. Over the years, the methods for conducting travel surveys have changed from manual interviews and paper forms to automated travel diaries which are monitoring the trips made by the survey participants. With the fast progression of technological advancements, new possibilities for operationalising said types of automated travel diaries can be changed from utilising mobile devices to wearable devices. Wearable devices are often equipped with sensors which can collect continuous biometric data from sources which are not reachable from standard mobile devices such as smartphones. The biometric data that can be collected through wearable devices ranging from heart rate and blood pressure to temperature and perspiration, given the proper sensors. This advancement opens for 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 more in-depth knowledge regarding stress and emotions, given the right variables and sample rate. This paper aims to explore the possibilities in terms of data analysis on a data set collected through a software combining traditional travel survey data, such as position and time, with biometric data, in this case; heartrate, to gain knowledge of the implications of such collected data. The knowledge about the implications of spatial configurations can be used in the planning phase of new areas, in order to create more accessible environments, as the information could be used to make neutral, or even encouraging, environments for travellers., This work is currently not under review but is intended to be submitted to the “International Conference on Transport Survey Methods” once the call for submissions is opened.QCR 20191022

The utilisation of travel surveys can uncover layers of information regarding travel behaviour, travel needs, and more. The collected information is utilised to make strategic planning choices when reorganising or planning new built environments. Over the years, the methods for conducting travel surveys have changed from manual interviews and paper forms to automated travel diaries which are monitoring the trips made by the survey participants. With the fast progression of technological advancements, new possibilities for operationalising said types of automated travel diaries can be changed from utilising mobile devices to wearable devices. Wearable devices are often equipped with sensors which can collect continuous biometric data from sources which are not reachable from standard mobile devices such as smartphones. The biometric data that can be collected through wearable devices ranging from heart rate and blood pressure to temperature and perspiration, given the proper sensors. This advancement opens for 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 more in-depth knowledge regarding stress and emotions, given the right variables and sample rate. This paper aims to explore the possibilities in terms of data analysis on a data set collected through a software combining traditional travel survey data, such as position and time, with biometric data, in this case; heartrate, to gain knowledge of the implications of such collected data. The knowledge about the implications of spatial configurations can be used in the planning phase of new areas, in order to create more accessible environments, as the information could be used to make neutral, or even encouraging, environments for travellers., This work is currently not under review but is intended to be submitted to the “International Conference on Transport Survey Methods” once the call for submissions is opened.QCR 20191022

The utilisation of travel surveys can uncover layers of information regarding travel behaviour, travel needs, and more. The collected information is utilised to make strategic planning choices when reorganising or planning new built environments. Over the years, the methods for conducting travel surveys have changed from manual interviews and paper forms to automated travel diaries which are monitoring the trips made by the survey participants. With the fast progression of technological advancements, new possibilities for operationalising said types of automated travel diaries can be changed from utilising mobile devices to wearable devices. Wearable devices are often equipped with sensors which can collect continuous biometric data from sources which are not reachable from standard mobile devices such as smartphones. The biometric data that can be collected through wearable devices ranging from heart rate and blood pressure to temperature and perspiration, given the proper sensors. This advancement opens for 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 more in-depth knowledge regarding stress and emotions, given the right variables and sample rate. This paper aims to explore the possibilities in terms of data analysis on a data set collected through a software combining traditional travel survey data, such as position and time, with biometric data, in this case; heartrate, to gain knowledge of the implications of such collected data. The knowledge about the implications of spatial configurations can be used in the planning phase of new areas, in order to create more accessible environments, as the information could be used to make neutral, or even encouraging, environments for travellers., This work is currently not under review but is intended to be submitted to the “International Conference on Transport Survey Methods” once the call for submissions is opened.QCR 20191022

The utilisation of travel surveys can uncover layers of information regarding travel behaviour, travel needs, and more. The collected information is utilised to make strategic planning choices when reorganising or planning new built environments. Over the years, the methods for conducting travel surveys have changed from manual interviews and paper forms to automated travel diaries which are monitoring the trips made by the survey participants. With the fast progression of technological advancements, new possibilities for operationalising said types of automated travel diaries can be changed from utilising mobile devices to wearable devices. Wearable devices are often equipped with sensors which can collect continuous biometric data from sources which are not reachable from standard mobile devices such as smartphones. The biometric data that can be collected through wearable devices ranging from heart rate and blood pressure to temperature and perspiration, given the proper sensors. This advancement opens for 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 more in-depth knowledge regarding stress and emotions, given the right variables and sample rate. This paper aims to explore the possibilities in terms of data analysis on a data set collected through a software combining traditional travel survey data, such as position and time, with biometric data, in this case; heartrate, to gain knowledge of the implications of such collected data. The knowledge about the implications of spatial configurations can be used in the planning phase of new areas, in order to create more accessible environments, as the information could be used to make neutral, or even encouraging, environments for travellers., This work is currently not under review but is intended to be submitted to the “International Conference on Transport Survey Methods” once the call for submissions is opened.QCR 20191022

The utilisation of travel surveys can uncover layers of information regarding travel behaviour, travel needs, and more. The collected information is utilised to make strategic planning choices when reorganising or planning new built environments. Over the years, the methods for conducting travel surveys have changed from manual interviews and paper forms to automated travel diaries which are monitoring the trips made by the survey participants. With the fast progression of technological advancements, new possibilities for operationalising said types of automated travel diaries can be changed from utilising mobile devices to wearable devices. Wearable devices are often equipped with sensors which can collect continuous biometric data from sources which are not reachable from standard mobile devices such as smartphones. The biometric data that can be collected through wearable devices ranging from heart rate and blood pressure to temperature and perspiration, given the proper sensors. This advancement opens for 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 more in-depth knowledge regarding stress and emotions, given the right variables and sample rate. This paper aims to explore the possibilities in terms of data analysis on a data set collected through a software combining traditional travel survey data, such as position and time, with biometric data, in this case; heartrate, to gain knowledge of the implications of such collected data. The knowledge about the implications of spatial configurations can be used in the planning phase of new areas, in order to create more accessible environments, as the information could be used to make neutral, or even encouraging, environments for travellers., This work is currently not under review but is intended to be submitted to the “International Conference on Transport Survey Methods” once the call for submissions is opened.QCR 20191022