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Enriching Automated Travel Diaries Using Biometric Information
KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, System Analysis and Economics.ORCID iD: 0000-0003-1558-382x
2019 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The methods for collecting travel data about travellers today incorporate either fully manual or semi-automatic elements, which makes the methods susceptible to errors. The travellers might respond subjectively rather than objectively or even wholly incorrect, albeit with or without purpose. For certain types of studies, these are still valid methods for collecting data. However, for specific target groups, it might be hard to respond using these methods, either because of physical or psychological limitations.

One of these target groups that is increasing rapidly is elderly in general, and dementia patients in particular, who suffer from fluctuating cognitive skills and memory. These conditions affect the recipient’s ability to answer truthfully and correctly. However, in the strive to form more accessible urban environments, the information regarding the need and behaviour of the said target group is crucial, meaning that new methods for collecting travel data need to be created.

The three papers included in this licentiate thesis present the development and trial of a new method for fully automated data collection using biometric data as a dimension. The method attempts to determine how the recipient is affected by the elements presented to them while they travel, such as the built environment, based on the variations in the biometric data dimension.

With the rapid advancements in information and communication technology, many new artefacts which open for new possible methods of data collection has been launched and are widely available. The methods and artefacts are not capable of meeting the requirements for the type of data collection method that would be needed to cater to the target group by themselves. However, by combing several types of currently available artefacts and methods, it is theoretically possible to cover the gaps of each artefact and method to create versatile methods for data collection (Paper I).

Such methods require tools for physical operationalisation. An exploratory development process has led to the creation of a software tool which could be used with several types of consumer hardware, which means that it would theoretically be possible to conduct extensive surveys fast with low costs where participants utilise their own hardware (Paper II).

In order to uncover the usefulness of the tool, an analysis was conducted on a limited dataset which had been collected as a result of a trial of the tool. In an attempt to prove the hypothesis “it is possible to understand how much the dimensions of data collected in specific locations affect the stress of travellers using heart rate as the dependent variable”, data-driven methods of data analysis were explored and utilised. Simple clustering methods, which disregarded any weighting on the dimensions, uncovered if there was any valuable information in the dataset at all. A model had to be created in order to understand better how the different dimensions of the collected data affected the participant (Paper III).

This set of papers should indicate whether this type of method is feasible to pursue with the current means of widely available technology and what sort of significance the collected data might hold when analysed with appropriate analysis methods.

Abstract [sv]

Metoderna för att samla in resedata från dagens resenärer inkorporerar antingen helt manuella eller halvautomatiska element, vilket gör dessa metoder mottagliga för fel. Resenärerna kan svara subjektivt snarare än objektivet eller helt inkorrekt, antingen med eller utan avsikt. För vissa typer av studier så är dessa metoder fortfarande meningsfulla att använda för datainsamling. Men för särskilda målgrupper kan det vara svårt att svara på undersökningar som använder dessa metoder, antingen på grund av fysiologiska eller psykologiska begränsningar.

En av dessa målgrupper, som är stadigt växande, är den äldre befolkningen generellt, men framförallt demenspatienter, som lider av sviktande kognitiva förmågor och minne. Dessa tillstånd påverkar den svarandes förmåga att svara sanningsenligt och korret. Men i strävan efter att skapa mer tillgängliga stadsmiljöer så är informationen angående behovet och beteendet hos den nämnda målgruppen av yttersta vikt, vilket innebär att nya metoder för att samla in resedata behöver skapas.

De tre artiklar som har inkluderats i denna avhandling presenterar utvecklingen och försökstestandet av en ny metod för helt automatisk datainsamling med användandet av biometriska data som en dimension. Metoden försöker att avgöra hur den svarande blir påverkad av element de stöter på medan de reser, såsom det byggda samhället, baserat på variationer i den biometriska datadimensionen.

Med de snabba framstegen inom informations- och kommunikationsteknik så har nya artefakter som öppnar för nya möjliga metoder av datainsamling lanserats och är allmänt tillgängliga. Dessa metoder och artefakter är inte kapabla till att möta de krav som ställs för den typ av datainsamlingsmetod som krävs för att kunna tillgodose målgruppen på egen hand. Men genom att kombinera flera typer av de nu tillgängliga artefakterna och metoderna så är det teoretiskt möjligt att täcka luckorna som finns i varje artefakt och metod för att skapa en mer mångsidig metod för datainsamling (Artikel I).

Sådana metoder kräver verktyg för att fysiskt operationaliseras. En explorativ utvecklingsprocess har lett till skapandet av ett mjukvaruverktyg som skulle kunna användas med flera typer av konsumenttillgänglig hårdvara, vilket betyder att det skulle vara teoretiskt möjligt att genomföra stora undersökningar snabbt med låga kostnader där deltagarna använder sin egen hårdvara (Artikel II).

För att förstå användbarheten av verktyget så gjordes en analys på ett begränsat data-set som hade blivit insamlat som ett resultat av ett försökstestande av verktyget. I ett försök att bevisa hypotesen ”det är möjligt att förstå hur mycket dimensionerna av data som samlats in vid specifika platser påverkar stressen hos resenärer med hjälp av puls som den beroende variabeln” så utforskades och användes data-drivna metoder av dataanalys. Enkla metoder, som inte la någon särskild vikt vid någon särskild dimension, användes för att visa om det fanns någon värdefull information i data-setet överhuvudtaget. En modell behövde skapas för att bättre förstå hur de olika dimensionerna av den insamlade datan påverkar deltagaren (Artikel III).

Denna samling artiklar är tänkt att ge en indikation på om denna typ av metodik är rimlig att fortsätta utveckla givet de nu tillgängliga teknologierna och vilken sorts signifikans den insamlade datan kan innehålla när den har analyserats med lämpliga analysmetoder.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2019. , p. 26
Series
TRITA-ABE-DLT ; 1941
National Category
Transport Systems and Logistics Human Computer Interaction Interaction Technologies
Research subject
Transport Science, Transport Systems
Identifiers
URN: urn:nbn:se:kth:diva-262880ISBN: 978-91-7873-352-1 (print)OAI: oai:DiVA.org:kth-262880DiVA, id: diva2:1363156
Presentation
2019-11-18, E2, Lindstedtsvägen 3, Stockholm, 10:00 (English)
Opponent
Supervisors
Funder
EU, Horizon 2020, 769980Available from: 2019-10-22 Created: 2019-10-22 Last updated: 2019-10-22Bibliographically approved
List of papers
1. Using Smart Technologies to Understand Travellers Who have Dementia: Potentials and Challenges
Open this publication in new window or tab >>Using Smart Technologies to Understand Travellers Who have Dementia: Potentials and Challenges
Show others...
(English)Manuscript (preprint) (Other academic)
Abstract [en]

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.

Keywords
Ageing society, internet of things, travel needs, built environment, automated data collection, implicit interaction
National Category
Transport Systems and Logistics Human Computer Interaction Interaction Technologies
Research subject
Transport Science, Transport Systems
Identifiers
urn:nbn:se:kth:diva-262859 (URN)
Funder
EU, Horizon 2020, 769980
Note

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

Available from: 2019-10-22 Created: 2019-10-22 Last updated: 2019-10-22Bibliographically approved
2. Developing and Trialling an Implicit Interaction Platform to Monitor Elderly Travellers
Open this publication in new window or tab >>Developing and Trialling an Implicit Interaction Platform to Monitor Elderly Travellers
(English)Manuscript (preprint) (Other academic)
Abstract [en]

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.

Keywords
Ageing society, built environment, position data, biometric data, automated data collection, implicit interaction
National Category
Transport Systems and Logistics Human Computer Interaction Interaction Technologies
Research subject
Transport Science, Transport Systems
Identifiers
urn:nbn:se:kth:diva-262861 (URN)
Funder
EU, Horizon 2020, 769980
Note

This work is currently under review for the journal “Human-Computer Interaction”.

QCR 20191022

Available from: 2019-10-22 Created: 2019-10-22 Last updated: 2019-10-22Bibliographically approved
3. Built Environment Characteristics, Daily Travel, and Biometric Readings: Creation of an Experimental Tool based on a Smartwatch Platform
Open this publication in new window or tab >>Built Environment Characteristics, Daily Travel, and Biometric Readings: Creation of an Experimental Tool based on a Smartwatch Platform
(English)Manuscript (preprint) (Other academic)
Abstract [en]

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.

Keywords
Built environment, position data, biometric data, automated data collection, urban planning, traveller needs, traveller behaviour
National Category
Transport Systems and Logistics Human Computer Interaction Interaction Technologies
Research subject
Transport Science, Transport Systems
Identifiers
urn:nbn:se:kth:diva-262879 (URN)
Funder
EU, Horizon 2020, 769980
Note

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

Available from: 2019-10-22 Created: 2019-10-22 Last updated: 2019-10-22Bibliographically approved

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