A Study on Commuting Therapy
Designing a Human-Vehicle Interaction System to Enhance 
the Commuting Experience with Emotion-based Multisensory 
Strategies

Master’s Thesis in Industrial Design Engineering

XIAONAN LU

DEPARTMENT OF INDUSTRIAL AND MATERIALS SCIENCE

CHALMERS UNIVERSITY OF TECHNOLOGY
Gothenburg, Sweden 2024
www.chalmers.se

www.chalmers.se




Master’s thesis 2024

A Study on Commuting Therapy

Designing a Human-Vehicle Interaction System to Enhance the
Commuting Experience with Emotion-based Multisensory Strategies

XIAONAN LU

Department of Industrial and Materials Science 
Division Design & Human Factors

Chalmers University of Technology 
Gothenburg, Sweden 2024



A Study on Commuting Therapy
Designing a Human-Vehicle Interaction System to Enhance the Commuting Expe-
rience with Emotion-Based Multisensory Strategies
XIAONAN LU

© XIAONAN LU, 2024.

Examiner & Supervisor: Bijan Aryana, Division Design & Human Factors

Master’s Thesis 2024
Department of Industrial and Materials Science
Division Design & Human Factors
Chalmers University of Technology
SE-412 96 Gothenburg
Telephon +46 31 772 1000

Typeset in LaTeX
Gothenburg, Sweden 2024

iv



A Study on Commuting Therapy
Designing a Human-Vehicle Interaction System to Enhance the Commuting Expe-
rience with Emotion-Based Multisensory Strategies
XIAONAN LU
Department of Industrial and Materials Science
Chalmers University of Technology

Abstract
Commuting is often perceived as mundane and time-consuming. However, commute
also offers an opportune space and time for design interventions that can enhance
well-being during the daily commute.

This thesis project explores the design opportunities to enhance the leisure expe-
rience during commuting, with a focus on Jordan’s Four Product Pleasures. This
project reimagines commute as a transition period aimed at improving human well-
being, transforming it into a more pleasurable experience. As a result, this project
introduces an affective human-vehicle interaction system within the smart cabin, em-
ploying multisensory emotion regulation strategies, including vision, aroma, music,
and haptics. Specifically, this project details the design of a multisensory experience
tailored to driver emotional states during commutes. The proposed design was eval-
uated through a VR car simulator in a qualitative user study, which revealed user
preferences for multisensory experiences.

Keywords: Commute, Driver’s Emotional States, Emotion regulation, Multisensory
Experience, Well-being.

v





Acknowledgements
I would like to express my gratitude to everyone who supported me throughout the
completion of this thesis. Your encouragement and invaluable contributions have
been essential in helping me achieve my goals and successfully conclude my research.

The journey of writing this thesis has been a fascinating experience, marked by
significant personal and professional growth. It has been a process of continuous
learning, and I am profoundly grateful for the knowledge and insights gained along
the way.

I would like to express my appreciation to all project participants, for giving me the
opportunity to create a design case study that rely on a real-life business context.
Your participation in this project was highly valuable for me, and I deeply value the
opportunity to have worked with you.

A special thank you to my thesis supervisor, Antonio Cobaleda Cordero, at Polestar,
for his invaluable guidance and support throughout the thesis process. His insight-
ful comments and continuous guidance are instrumental in shaping this work. I
would also like to extend my deep gratitude to Bijan Aryana, my supervisor and
examiner at Chalmers, for his valuable suggestions and constructive feedback, which
significantly enhanced the quality of this thesis.

Lastly, I would like to thank my family, dear ones, good friends, and colleagues.
Thank you for keeping me motivated and supporting me when I needed it the most.

Xiaonan Lu, Gothenburg, August 2024

vii





List of Acronyms

Below is the list of acronyms that have been used throughout this thesis listed in
alphabetical order:

AR Augmented Reality
AV Autonomous Vehicles
CAV Conditional Autonomous Vehicles
EVs Electric Vehicles
PAD Pleasure-Arousal-Dominance (Scale)
PrEmos Product Emotion Measure
RtD Research through Design
SAD Seasonal Affective Disorder
UEQ User Experience Questionnaire
UX User experience
VR Virtual Reality

ix





Contents

List of Acronyms ix

List of Figures xv

1 Introduction 1

2 Literature review 5
2.1 Leisure experience . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.2 Commuting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

2.2.1 Current commuting situation . . . . . . . . . . . . . . . . . . 7
2.2.2 Commuting activities . . . . . . . . . . . . . . . . . . . . . . . 7

2.2.2.1 work and home commute . . . . . . . . . . . . . . . 7
2.2.2.2 Non-driving activities . . . . . . . . . . . . . . . . . 7

2.2.3 User experience themes for commuting . . . . . . . . . . . . . 8
2.2.4 Design for Commute . . . . . . . . . . . . . . . . . . . . . . . 8

2.2.4.1 Car as a space for stimulation . . . . . . . . . . . . . 8
2.2.4.2 Car as a space for Socialization . . . . . . . . . . . . 9
2.2.4.3 Car serves as a care taker . . . . . . . . . . . . . . . 9

2.3 Human emotions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.3.1 Emotion theories . . . . . . . . . . . . . . . . . . . . . . . . . 10

2.3.1.1 Discrete emotion theory . . . . . . . . . . . . . . . . 10
2.3.1.2 Dimensional emotion theory . . . . . . . . . . . . . . 10

2.3.2 Human emotion expressions . . . . . . . . . . . . . . . . . . . 10
2.3.2.1 Behavioral expressions . . . . . . . . . . . . . . . . . 11
2.3.2.2 Physiological expression . . . . . . . . . . . . . . . . 12

2.3.3 Driver emotions in automotive context . . . . . . . . . . . . . 12
2.4 Emotion detection in car . . . . . . . . . . . . . . . . . . . . . . . . . 13

2.4.1 Physiological measurements . . . . . . . . . . . . . . . . . . . 13
2.4.2 Behavioral measurements . . . . . . . . . . . . . . . . . . . . 13
2.4.3 Self-reported scales . . . . . . . . . . . . . . . . . . . . . . . . 13
2.4.4 Other contextual factors . . . . . . . . . . . . . . . . . . . . . 14

2.5 Emotion regulation in car . . . . . . . . . . . . . . . . . . . . . . . . 14
2.5.1 Visual stimuli . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

2.5.1.1 Ambient light . . . . . . . . . . . . . . . . . . . . . . 15

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Contents

2.5.1.2 Visual intervention . . . . . . . . . . . . . . . . . . . 15
2.5.1.3 State feedback . . . . . . . . . . . . . . . . . . . . . 15

2.5.2 Auditory stimuli: Adaptive music . . . . . . . . . . . . . . . . 15
2.5.3 Olfactory stimuli: Aroma . . . . . . . . . . . . . . . . . . . . . 16
2.5.4 Haptic Stimuli . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

2.6 Light . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.6.1 Light dynamic pattern . . . . . . . . . . . . . . . . . . . . . . 17
2.6.2 Light Placement . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.6.3 Light colors and brightness . . . . . . . . . . . . . . . . . . . . 18

2.6.3.1 Information transmission through colorful lights . . . 18
2.6.3.2 Colors on emotion . . . . . . . . . . . . . . . . . . . 18
2.6.3.3 Colorful lights on emotion . . . . . . . . . . . . . . . 19

2.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

3 Method 23
3.1 Design framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3.2 Study design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

3.2.1 Preliminary Expert Interview Study . . . . . . . . . . . . . . . 24
3.2.1.1 Process . . . . . . . . . . . . . . . . . . . . . . . . . 24
3.2.1.2 Participants . . . . . . . . . . . . . . . . . . . . . . . 25
3.2.1.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . 25

3.2.2 Ideation workshops . . . . . . . . . . . . . . . . . . . . . . . . 29
3.2.2.1 On-site workshop . . . . . . . . . . . . . . . . . . . . 30
3.2.2.2 Online workshop . . . . . . . . . . . . . . . . . . . . 33
3.2.2.3 Concept Screening . . . . . . . . . . . . . . . . . . . 36

3.2.3 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
3.2.3.1 Study Design . . . . . . . . . . . . . . . . . . . . . . 38
3.2.3.2 Participants . . . . . . . . . . . . . . . . . . . . . . . 38
3.2.3.3 Methods . . . . . . . . . . . . . . . . . . . . . . . . . 39
3.2.3.4 Apparatus . . . . . . . . . . . . . . . . . . . . . . . . 41
3.2.3.5 Procedure . . . . . . . . . . . . . . . . . . . . . . . . 42
3.2.3.6 Limitations . . . . . . . . . . . . . . . . . . . . . . . 42

4 Concept: Commuting Therapy 43
4.1 Driver Emotion detection in Polestar . . . . . . . . . . . . . . . . . . 43
4.2 Driver Emotion Regulation in Polestar . . . . . . . . . . . . . . . . . 44

4.2.1 Desired emotional state . . . . . . . . . . . . . . . . . . . . . . 44
4.2.2 Affective state regulation modes . . . . . . . . . . . . . . . . . 45

4.3 Emotion-based multi-sensory interaction . . . . . . . . . . . . . . . . 45
4.3.1 Visual stimuli . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

4.3.1.1 Ambient light . . . . . . . . . . . . . . . . . . . . . . 46
4.3.1.2 Nebula animation . . . . . . . . . . . . . . . . . . . . 47
4.3.1.3 State feedback . . . . . . . . . . . . . . . . . . . . . 48

4.3.2 Adaptive music . . . . . . . . . . . . . . . . . . . . . . . . . . 48
4.3.3 Aroma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
4.3.4 Haptic Stimuli . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

4.3.4.1 Force . . . . . . . . . . . . . . . . . . . . . . . . . . 51

xii



Contents

4.3.4.2 Temperature and Airstreams . . . . . . . . . . . . . 51
4.3.4.3 Vibration . . . . . . . . . . . . . . . . . . . . . . . . 52

5 Results 53
5.1 Emotional assessment under different sensations . . . . . . . . . . . . 53

5.1.1 Auditory stimuli: Adaptive music . . . . . . . . . . . . . . . . 54
5.1.1.1 Positive feedback . . . . . . . . . . . . . . . . . . . . 54
5.1.1.2 Suggestions and Preferences . . . . . . . . . . . . . . 55

5.1.2 Visual stimuli: Nebula Animation . . . . . . . . . . . . . . . . 55
5.1.2.1 Divergent Attitudes . . . . . . . . . . . . . . . . . . 55
5.1.2.2 Suggestions and Preferences . . . . . . . . . . . . . . 56

5.1.3 Visual stimuli: Ambient lights . . . . . . . . . . . . . . . . . . 56
5.1.3.1 Divergent Attitudes . . . . . . . . . . . . . . . . . . 56
5.1.3.2 Suggestions and Preferences . . . . . . . . . . . . . . 57

5.1.4 Olfactory stimuli: Aroma . . . . . . . . . . . . . . . . . . . . . 57
5.1.4.1 Positive feedback . . . . . . . . . . . . . . . . . . . . 57
5.1.4.2 Suggestions and Preferences . . . . . . . . . . . . . . 57

5.1.5 Tactile stimuli: Temperature, Massage and Air stream . . . . 57
5.1.5.1 Positive feedback . . . . . . . . . . . . . . . . . . . . 58
5.1.5.2 Suggestions and Preferences . . . . . . . . . . . . . . 58

5.2 Overall experience assessment . . . . . . . . . . . . . . . . . . . . . . 58
5.2.1 Ideo-Pleasure . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

5.2.1.1 Attractiveness . . . . . . . . . . . . . . . . . . . . . . 59
5.2.1.2 Stimulation and Novelty . . . . . . . . . . . . . . . . 59

5.2.2 Physio-Pleasure . . . . . . . . . . . . . . . . . . . . . . . . . . 59
5.2.2.1 Psycho-Pleasure . . . . . . . . . . . . . . . . . . . . 59
5.2.2.2 Socio-Pleasure . . . . . . . . . . . . . . . . . . . . . 60

6 Discussion and conclusions 61
6.1 Discussion and conclusions . . . . . . . . . . . . . . . . . . . . . . . . 61

6.1.1 Visual stimuli . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
6.1.2 Olfactory stimuli . . . . . . . . . . . . . . . . . . . . . . . . . 63
6.1.3 Auditory stimuli . . . . . . . . . . . . . . . . . . . . . . . . . 63
6.1.4 Tactile stimuli . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
6.1.5 Other design suggestions . . . . . . . . . . . . . . . . . . . . . 65

6.2 Future work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
6.3 The practical implications of the research . . . . . . . . . . . . . . . . 66
6.4 Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

6.4.1 Precise Emotion Regulation . . . . . . . . . . . . . . . . . . . 67
6.4.2 Technological Issues of In-car Emotion Detection . . . . . . . 67
6.4.3 Color and colored lights . . . . . . . . . . . . . . . . . . . . . 67
6.4.4 Privacy Considerations in Emotion Sensing . . . . . . . . . . . 67

A User Study scripts I
A.1 Greetings: 5 minutes from the entrance to the VR room . . . . . . . I
A.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . I
A.3 Consent form . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II

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Contents

A.4 VR Experiences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II
A.4.1 What happens before opening the APP . . . . . . . . . . . . . II
A.4.2 Get started on VR Similator . . . . . . . . . . . . . . . . . . . II
A.4.3 Ask me Questions . . . . . . . . . . . . . . . . . . . . . . . . . III
A.4.4 Assessment instruments . . . . . . . . . . . . . . . . . . . . . III

A.4.4.1 PrEmo under four sensations . . . . . . . . . . . . . III
A.4.4.2 Overall Experience Assessment: User experience ques-

tionnaire . . . . . . . . . . . . . . . . . . . . . . . . III
A.5 Interview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III

A.5.1 Physio-Pleasure . . . . . . . . . . . . . . . . . . . . . . . . . . III
A.5.2 Ideo-Pleasure . . . . . . . . . . . . . . . . . . . . . . . . . . . IV
A.5.3 Socio-Pleasure . . . . . . . . . . . . . . . . . . . . . . . . . . . IV
A.5.4 General Experience . . . . . . . . . . . . . . . . . . . . . . . . IV

B Consent Form for Participation in Commuting Therapy V

C Guide for Expert Interview VII
C.1 Guideline for Engineering Expert Interview . . . . . . . . . . . . . . . VII

C.1.1 Opening and Ice-breaking . . . . . . . . . . . . . . . . . . . . VII
C.1.2 Main parts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII

C.1.2.1 Project Specific . . . . . . . . . . . . . . . . . . . . . VII
C.1.2.2 Built in technologies . . . . . . . . . . . . . . . . . . VIII
C.1.2.3 Core Value of Polestar . . . . . . . . . . . . . . . . . VIII
C.1.2.4 Users . . . . . . . . . . . . . . . . . . . . . . . . . . VIII
C.1.2.5 Leisure Experiences . . . . . . . . . . . . . . . . . . VIII
C.1.2.6 Wellness or Wellbeing Specific . . . . . . . . . . . . . IX
C.1.2.7 Trends . . . . . . . . . . . . . . . . . . . . . . . . . . IX
C.1.2.8 Future Polestar cars . . . . . . . . . . . . . . . . . . IX

xiv



List of Figures

3.1 Workshop preparation . . . . . . . . . . . . . . . . . . . . . . . . . . 30
3.2 Online workshop . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
3.3 Measure instruments . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
3.4 Product Emotion Measure [1] . . . . . . . . . . . . . . . . . . . . . . 39
3.5 Basic setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
3.6 VR scene on screen . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

4.1 Driver state taxonomy based on Russel’s circumplex arousal-valance
model [2] and the Yerkes-Dodson law [3]. Positive valance and medium
arousal values have been shown to be the desired states in driving [4] 45

4.2 Nebula animation high fidelity prototypes . . . . . . . . . . . . . . . 47
4.3 Adaptive music high fidelity prototypes . . . . . . . . . . . . . . . . . 50
4.4 Aroma high fidelity prototypes . . . . . . . . . . . . . . . . . . . . . . 50

5.1 The emotional assessment of different sensations . . . . . . . . . . . . 54
5.2 The results of UEQ . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

xv



List of Figures

xvi



1
Introduction

Most of the key use cases for individual transportation can be classified as leisure
experiences [5] [6], highlighting the growing importance of designing for leisure expe-
riences within vehicles. Current in-car leisure options often include video streaming,
karaoke, and on-screen games. However, the fierce competition within the auto-
motive industry emphasizes the necessity for exceeding customer expectations [7].
Consequently, Polestar, as a luxury brand, is actively differentiating itself by offering
distinctive leisure experiences that go beyond these conventional offerings.

Everyday, 87% of the workforce in the United States, approximately 127 million
people, spend an average of one hour commuting by car [8]. For many, car-based
commuting (hereafter referred to as commuting) has become a daily routine, requir-
ing a significant amount of time spent in vehicles [9]. Millions of people consider
their commuting a daily stressful hassle [10]. However, commuting also provides
an opportune time and space for design interventions that can enhance the in-car
experience [8] and improve driver health [10].

The development of technologies is a decisive factor in designing the leisure expe-
rience for commuting. Autonomous Vehicle (AV) technology promises relief from
driving-related stress and may fundamentally change the commuting experience [10],
which are anticipated to offer the opportunity to utilize commuting time for vari-
ous activities, thereby reducing or even eliminating the costs associated with travel
[11]. Although much of the research [5] [10] [12] and design [13] [14] in academia
is centered on AVs, there are still many technical and organizational issues to be
addressed before reaching the fully autonomous driving [12]. Furthermore, several
experts expressed their belies that the fully autonomous driving will not arrive in
10 years in the interviews.

In this thesis project, the aim was not only to create an innovative and unique
leisure experience during commuting but also to ensure that the design could be
implemented in future Polestar vehicles. To balance innovation with feasibility,
the autonomous driving level was set between Level 3 and Level 4, where drivers
are not required to intervene in driving tasks under specific conditions [12]. This
technological context can be called as Conditional Autonomous Vehicle (CAV) [12].
Although the technological setting is not fully advanced, recent advancements in

1



1. Introduction

sensor and communication technologies are offering new possibilities for enhancing
the in-car leisure experience.

• Human-Machine Interfaces: Innovations in interfaces can provide more
intuitive and engaging interactions, such as head-up displays, brain-computer
interfaces [15], haptic interfaces [16], augmented reality interfaces [17], adap-
tive voice interfaces [18], smell interfaces [19].

• Emotion Recognition Technology: Identifying and responding to the
driver’s emotional state can personalize the commuting experience [20] [21]
[22].

• Health Monitoring and Management Systems: These systems can track
and improve the driver’s well-being during the commute [23].

• Augmented Reality: AR can offer immersive experiences that enhance nav-
igation and entertainment [17] [24].

The research was set to start from exploring the general user experience (UX) de-
sign opportunities for in-car leisure experiences during commuting. To conduct the
research, I formulate the main research question:

R1: How can a mundane commute be transformed into a more pleasurable experi-
ence through leisure experience?

Several UX themes were identified in a previous study [25] to enhance the commuting
experience, where the car is perceived as a caretaker [8] [13] [26] [27], a space for
stimulation [28] [29] [24] [30], a space for socialization [31] [32], Car as a space for
transition [10] [9] [25] [33]. In addition, numerous proposals have been made to
rethink the commute as a period of enhancing human well-being through various
leisure activities aligned with the last three UX themes, while the transition aspect
remains largely unexplored.

Initially, I was exploring the UX opportunities for both passengers and drivers. How-
ever, I found that solo driving is still the number one choice for commuting despite
the high costs and stressful traffic congestions [9] [34]. Additionally, I conducted two
rounds of ideation workshops. After gathering and screening the concepts based on
the previously made criteria from expert interview in Polestar, I decided to focus
on driver experience during commuting, which is also align with the driver-centric
philosophy of Polestar. Moreover, I found that most commuters use daily commute
as a "transition time" between work and home [9] [25]. However, there were few
studies that focused on the transition of drivers during commuting between home
and work. Thus, I decided to focus on exploring leisure experiences for drivers that
help them prepare for the upcoming workday or evening.

2



1. Introduction

I presented the work Commuting Therapy, aiming to help drivers prepare for their
next stage of the day during commutes. However, instead of helping drivers to be
productive or seek socialization, I put the focus on the driver’s emotional states
during the transition, which is more plausible in the autonomous and technological
context, and more suitable for the leisure experience theme of this project. Specif-
ically, Commuting Therapy focus on the emotional states of the driver, trying to
regulate the driver’s emotion to the optimal level, preparing them for the upcoming
workday or evening. Many studies stated emotion states, especially anger, have a
great impact on driving performance and safety [35][36] [37] [38], emotional well-
being has also been a key focus in the design of in-car systems [39] [40] [41] [14].
Commuting Therapy is to keep the driver in a desired state of mood by providing
different stimulus to regulate drivers’ states, contributing to flourish well-being af-
ter taking commuting as a transition. Regulative efforts will be taken place when
the current driver’s mood is not desirable. Regarding the desired emotional state,
I found that the medium activation is seen as an optimal level of arousal [3], and
positive valence is generally considered as a sign of a good user experience [42] in
the driving context, which is also the optimal states for high driving performance.

To enable the emotion-based interaction system within the cabin, it’s crucial to
thoroughly research how the car detects the driver’s emotions and how the system
can influence them. Therefore, two subsidiary research questions are formulated as
follows:

R2: How can an in-car system accurately detect driver emotions?

R3: How can driver emotions be regulated to achieve a desired emotional state
through different strategies?

As a result, I proposed the Commuting Therapy concept, an emotion-based multi-
sensory design, intended to help drivers achieve the desired emotional states during
commutes and thus prepare them for the next stage of their day. The Commut-
ing Therapy utilizes multisensory stimulations to create an adaptive environment
that mitigates negative emotions during commutes, aiming to transform the daily
commute into a pleasurable experience.

In this thesis project, I presented only two typical modes of the Commuting Therapy
due to time limitations:

• Home to Work: The refreshing mode is designed to reduce drowsiness and
keep the driver alert in the morning, particularly during winter when many
people experience seasonal affective disorder (SAD).

• Work to Home: The relaxing mode is intended to help drivers unwind after
a day at work.

3



1. Introduction

In the end of this thesis project, I evaluated the Commuting Therapy design through
a VR car simulator experience, utilizing the Product Emotion Measure (PrEmo),
User Experience Questionnaires (UEQ), and semi-structured interviews. The goal
was to understand participants’ perceptions of the concept itself, based on which
several suggestions for the future development of this concept were made.

In summary, this study addresses the gap in the existing literature by focusing on
driver-centric leisure experience design in the context of partially autonomous vehi-
cle. Specifically, it contributes to three key areas: (1) exploring leisure experience
design for drivers in CAVs, (2) examining emotion-based multisensory experiences
to support transitions between home and work, and (3) integrating multiple affec-
tive strategies into a single in-car system to create a comprehensive multisensory
experience.

4



2
Literature review

The preliminary study was aimed to understand the background of leisure experi-
ences and the commuting context to define the scope and direction of the design.
Firstly, the concept of leisure experience within the automotive context was defined,
establishing the scope of this thesis project. This helped clarify which types of de-
sign can be categorized as leisure experiences, thereby shaping the design directions.
Furthermore, several UX themes were identified to enhance the commuting experi-
ence, where the car is perceived as a space for transition, stimulation, socialization,
or as a caretaker. In addition, I explore the general background of commute and
existing design cases for commute. I found numerous proposals have been made to
rethink the commute as a period of enhancing human well-being through various
leisure activities aligned with three UX themes, while the transition aspect remains
largely unexplored. Furthermore, I observed that emotional well-being is also a key
focus in the design of car systems [39] [40] [41] [14]. Regarding target users, I did
not define a specific target user group at the outset. However, I discovered that solo
driving remains the most common option for commutes despite its high costs and
the stress of traffic congestion [9]. Therefore, I decided to focus on improving the
driver experience during commuting.

Following the preliminary study, I decided to focus on the design direction of the
transition during commuting, specifically focusing on emotional well-being. My
goal was to facilitate a positive transition in driver emotional states during their
commute, effectively preparing them for the next phase of their day. To achieve
this, it was essential to address the second and third research questions, which led
me to the main study.

The main study focused on exploring emotion detection and regulation within the
automotive context. To gain a deeper understanding of human emotions, I re-
searched various emotion theories and how humans express their emotions, with
particular attention to driver emotions in the automotive setting. By investigating
different emotion detection technologies and emotion regulation strategies, I was able
to determine which approaches are most suitable for this project’s conditions. This
study provides a comprehensive foundation for understanding how emotional re-
sponses can be detected, regulated, and influenced in a vehicle environment through
various sensory modalities, including vision, aroma, music, and haptics.

5



2. Literature review

All in all, the preliminary study started with a broad exploration of the leisure ex-
perience domain to identify design opportunities within the automotive field, specif-
ically focusing on commuting. Through the preliminary review, I established a
research direction centered on emotional well-being, aiming to help users transition
their emotional states during commutes. Consequently, the main study focused on
researching emotion-based multisensory interactions to enhance leisure experiences
during car commutes. This literature review provides a solid foundation for propos-
ing future design solutions.

2.1 Leisure experience

Mansourian [6] categorizes leisure into three primary types. The first type is serious
leisure, which involves a committed and focused pursuit of a hobby or volunteer work
that requires the acquisition of specialized skills, knowledge, and experience. Exam-
ples of serious leisure include activities such as woodworking, car repair, and glass
blowing. The second type is casual leisure, characterized by activities that require
no formal training and are typically undertaken for relaxation or enjoyment, such
as watching television, relaxing, or leisure reading. The third type is project-based
leisure, which is more complex and time-bound, involving activities like organizing
a wedding, participating in an exhibition, or attending a cultural ceremony. Addi-
tionally, Allaby and Shannon [43] offer a similar categorization, dividing leisure into
structured and unstructured leisure. Structured leisure is typically voluntary, orga-
nized, and scheduled, aligning closely with Mansourian’s serious and project-based
leisure [6]. In contrast, unstructured leisure aligns with casual leisure, encompass-
ing activities that are enjoyable and spontaneous. Polestar aims to develop leisure
experiences that fall into the category of casual leisure, focusing on providing spon-
taneous and enjoyable activities without the need for formal planning or training.

Given the focus on casual leisure, it is crucial to explore how these leisure expe-
riences manifest within the automotive context and to assess the potential design
opportunities. A global survey identified key use cases for autonomous individual
transportation, including Sleeping & Relaxing, Working & Being Productive, Eating
& Drinking, Entertainment, Beauty & Well-being, and Fitness [5]. Notably, with
the advent of full driving autonomy, most of these use cases align with casual or
unstructured leisure experiences, aside from working and being productive. This
trend manifests the growing importance of designing for leisure within vehicles. Au-
tonomous driving promises to free users from the demands of driving, offering them
greater opportunities to engage in leisure activities with enhanced safety. However,
to align with Polestar’s vision and to contribute meaningfully to the next generation
of vehicles over the coming decade, our focus will be on harnessing conditional or
high driving autonomy, rather than full autonomy. This project aims to enrich ca-
sual leisure experiences during commutes, potentially encompassing activities such
as Sleeping & Relaxing, Eating & Drinking, Entertainment, Beauty & Wellbeing,
and Fitness.

6



2. Literature review

2.2 Commuting

2.2.1 Current commuting situation

Commuting is defined as the daily travel between home and work-place, which does
not include work-related travel, but includes trips to work at variable locations [9].
Commute becomes a daily routine that involves driving at the start and end of each
day. However, the time spent traveling long distances to work may be considered
unproductive and wasteful. The environment surrounding the car commuter, often
referred to as the smart cabin, falls short in offering supplementary activities beyond
driving [33].

Despite its high costs and stressful traffic congestions, solo driving is still the number
one choice for commuting [9]. The report on commuting patterns and trends [34]
shows a steady growth in the last decade in driving alone. Therefore, I concluded
that the driver experience is essential to improving the overall commuting experience.

2.2.2 Commuting activities

2.2.2.1 work and home commute

Several commuter studies have shown that work and home commute are two dif-
ferent situations, where time is used for different purposes[33] [10] [9] [25]. Most
of the commuters use daily commute as "transition time" between work and home
[9] [25]. While driving to work is dominated by doing office work cooperatively,
traveling home involves more collaborative leisure activities. The work commute
tends to be quiet and monotonous, with activities primarily focused on work-related
tasks, such as planning the day and coordinating with colleagues. In contrast, the
home commute is more leisure-oriented, often used for planning evening or weekend
activities, and commuters tend to seek social interactions during this time. These
tendencies suggest that the design focus for the work commute should be on men-
tally stimulating, work-related activities, while the home commute should prioritize
leisure activities.

2.2.2.2 Non-driving activities

A study conducted by Pfleging et al. [44] investigated the user needs for non-
driving related activities and entertainment during automated driving. The findings
indicate that besides traditional activities (talking to passengers, listening to music),
daydreaming, writing text messages, eating and drinking, browsing the Internet, and
calling are most wanted for highly automated driving. These insights suggest that
for a driver-centric experience, particularly when driving alone, activities such as
listening to music and daydreaming are among the most sought-after.

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2. Literature review

2.2.3 User experience themes for commuting
Several UX themes were identified in a previous study [25] to enhance the commuting
experience, where the car is perceived as a space for transition, stimulation, social
relatedness, or as a caretaker.

• Car serves as a caretaker: The car is designed to ensure users’ safety, meet
their needs, and provide convenience. For example, there are designs aimed at
helping users manage stress [8] and incorporate workout options [13] [26] [27].

• Car as a space for stimulation: The car has long symbolized freedom and
independence, offering thrilling driving experiences [28] or engaging gaming
experiences [29] [24] [30] .

• Car as a space for socialization: The car serves as a space where users
can connect with people who matter to them [31] [32].

• Car as a space for transition: Time spent in the car can be used to prepare
for the next stage of the day. Users often handle work tasks during their drive
to the office and seek relaxation or social connection during their drive home
[10] [9] [25] [33].

2.2.4 Design for Commute
Commutes provide an opportune time and space for interventions that contribute to
well-being during the workday [8]. Recently, there have been numerous proposals to
rethink the commute and turn it into a time for enhancing human well-being through
various activities such as stress management, fitness, socialization, gamification and
more.

2.2.4.1 Car as a space for stimulation

1. Gamification: One approach to enhancing the commuting experience is
through gamification. Brunnberg [35] developed a multi-player game, Road
Ranger, which allows passengers in different cars to play against each other
while stuck in traffic. Similarly, Lakier et al. [29] identified opportunities
for "cross-car" multiplayer games played among occupants in nearby vehicles,
leveraging advancements in automotive technology such as autonomous driv-
ing, full-window heads-up displays, and ad hoc vehicle communication.

Another example is the work by Sundström et al. [45], who proposed full-body
interaction games designed to make proper sitting posture more engaging,
particularly for children traveling in cars. What is more, Broy et al. [46],
who designed a game where all car occupants participate together, fostering a
shared experience during the commute. Similarly, Togwell et al. [24] designed
a mixed reality gameplay for passengers through AR headset.

8



2. Literature review

2. Landmark Interaction: In addition to games, there are interactive appli-
cations that allow passengers to engage with their surroundings based on the
car’s location. Brunnberg et al. [47] suggested a new type of application
that provides information about landscapes based on the vehicle’s location,
enhancing the passenger’s connection with the external environment. Mat-
sumura et al. [48] described an interactive car window system designed to
support passengers in engaging with the environment during their journey.

3. Music improvisation: Music has always played a crucial role in creating
pleasurable driving experiences [49]. Kesson and Karl [33] demonstrated a
potential IT service that supports commuters by allowing them to sample
music directly from their car, moving beyond the conventional music shop ex-
perience. Additionally, Eckoldt and Schulz [50] conceptualized the car as a
musical instrument, allowing passengers to drum together, creating a positive
and collaborative in-car experience. Further exploring the integration of music
in the car environment, Krome et al. [30] explored the alignment of music cre-
ation with the progression of traffic conditions in an interactive music listening
experience, adding a dynamic layer to the traditional in-car music experience.

2.2.4.2 Car as a space for Socialization

Another important aspect of enhancing the commuting experience is fostering so-
cial relatedness. Schroeter et al. [31] investigated the potential of cars as social
platforms, designing interactive vehicle applications inspired by social networks and
urban informatics. Furthermore, Knobel and Hassenzahal [32] proposed Clique Trip,
an experience aimed at creating a sense of closeness and relatedness among friends
traveling in a "motorcade."

2.2.4.3 Car serves as a care taker

There has also been considerable research on integrating fitness and well-being in-
terventions into the commuting experience. Stephanie et al. [8] designed a haptic-
guided slow breathing intervention for drivers, using a portable vibrotactile seat
cover to guide the driver’s breathing, promoting relaxation during the commute.
Krome et al. [13] introduced the concept of AutoGym, an in-car fitness program
that transforms frustrating traffic situations into a fun exertion game. Deserno and
Tomas [26] explored the idea of using vehicles as private spaces to monitor health,
offering an alternative to smart wearables or smart clothes. Other studies have also
explored guided breathing exercises during commuting, using haptic or acoustic
feedback to encourage calmness and reduce stress [27] [51] [52].

Finally, emotional well-being has also been a key focus in the design of in-car
systems[39] [40] [41] [14]. Terken et al. [14] presented a concept for an in-car system
designed to support unwinding after work, incorporating a mood-sensing steering
wheel, an interactive in-car environment, and a tangible input device to help drivers
relax after a long day.

9



2. Literature review

2.3 Human emotions

2.3.1 Emotion theories
Emotions are generally defined as human responses characterized by distinctive
patterns of conscious and unconscious psychophysiological activities [53]. These
responses can vary widely between individuals, as they are shaped by personal cog-
nitive appraisals [54]. This inherent subjectivity highlights the need for real-time
detection to accurately understand an individual’s emotional state, rather than re-
lying on indirect measures.

Emotions can be classified through either discrete emotion theory, which identifies
specific emotional states, or dimensional emotion theory, which represents emotions
along continuous dimensions such as arousal and valence [53].

2.3.1.1 Discrete emotion theory

Discrete emotion theory proposes that there are a small number of distinct emotions,
each characterized by specific patterns of physiological responses, brain activity, and
facial expressions. Major models within this framework include six basic emotions
proposed by Ekman [55] and the emotion wheel model proposed by Plutchik [56],
which illustrates how these basic emotions can combine to form more complex emo-
tional experiences. Among these two discrete emotion models, the basic emotion
model [55] is widely acknowledged, summarising six basic emotions as happiness,
sadness, anger, fear, surprise, and disgust. Other emotions were regarded as combi-
nations of these basic emotions.

2.3.1.2 Dimensional emotion theory

Dimensional emotion theory suggests that emotional states can be accurately de-
picted as combinations of various psychological dimensions, such as valence and
arousal. According to Desmet et al. [57], a widely accepted dimensional scale of
emotions is the Pleasure-Arousal-Dominance Scale (PAD) developed by Russell and
Mehrabian [58]. These dimensional models contain valence and arousal. Valence
refers to the degree of pleasure associated with emotions, while arousal refers to the
intensity of the experienced emotions. Furthermore, another dimension that exists
in PAD model is called dominance, which reflects the control ability of humans on
emotions, ranging from submissive to dominant [53].

2.3.2 Human emotion expressions
The emotions of humans can be expressed in forms including behavioral expressions
and physiological changes [53]. Emotional expressions in humans are crucial for rec-
ognizing and managing emotions, especially in driving contexts. These expressions
are multimodal, involving various channels such as the face, speech, body gestures,
and physiological changes [41]. As Li et al. [22] explain, emotions can manifest in
both behavioral and physiological forms.

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2. Literature review

2.3.2.1 Behavioral expressions

Behavioral expressions include a variety of observable actions, such as facial expres-
sions, speech patterns, and body movements. For instance, a smile or frown, the
tone of voice, and gestures like clenched fists or a relaxed posture all communicate
emotional states.

Ekman and Friesen [59] demonstrated that at least six core emotions (anger, fear,
disgust, happiness, sadness, and surprise) can be universally recognized across dif-
ferent cultures through facial expressions. The six discrete emotions are universally
identifiable and provide clear reference points for understanding human emotional
experiences. Additionally, Research by Russell [60] shows that facial expression ap-
pears to reliably indicate the valence of a person’s emotional state. For example,
Duchenne smiles that involve wrinkling of muscles around the eyes are reported to
be associated with positive emotional experiences. In contrast, negative emotion
inductions are often associated with visible facial behavior in which the eyebrows
are raised and brought closer together [61].

What is more? Speech conveys emotional information through both linguistic and
acoustic cues, reflecting how words are spoken [62]. The linguistic content of speech
carries emotional information that can be directly inferred from the surface features
of words, as summarized in emotional word dictionaries [63]. Additional emotional
meaning can be understood by considering the broader semantic context, such as
discourse information. Beyond linguistic messages, acoustic cues also convey rich
information, including age, gender, and hometown. Acoustic expressions are defined
by speech prosody (pitch, loudness, rhythm); for example, a happy voice typically
has a higher pitch, louder volume, and faster rate, while a sad voice features a lower
pitch and slower speech rate.

Acoustic expressions are effective in distinguishing between basic emotions [64].
Each of the six basic emotions—anger, fear, disgust, happiness, sadness, and sur-
prise—correlates with distinct acoustic changes, such as variations in pitch, inten-
sity, duration, and spectral qualities. In addition, acoustic expressions vary along
the continuous dimensions of valence and arousal. Research consistently shows a
strong relationship between arousal and pitch, with higher arousal associated with
higher pitched vocal expressions [65]. However, while pitch is a reliable indicator of
arousal, finding acoustic characteristics sensitive to valence is more challenging, as
valence often relates more closely to the textual content of the speech rather than
its acoustic properties [66].

Lastly, numerous studies have highlighted the crucial role that body language plays
in the transmission of emotions [53]. Nonverbal cues such as facial expressions, body
postures, gestures, eye movements, touch, and the use of personal space communi-
cate specific information about an individual’s emotional state.

Based on the dimensional emotion model, Glowinski et al. [67] found that the tra-
jectory of head and hand movements can distinguish emotion groups in the valence-

11



2. Literature review

arousal space. These were divided into four categories: high-positive, high-negative,
low-positive, and low-negative. Kosti et al. [68] analyzed emotional expressions by
examining features of the body and background, focusing on intensity, arousal, and
dominance. Research also extends to discrete emotion models. Gunes and Piccardi
[69] showed that simple representations of the upper body can categorize postures
into six emotions: anger, disgust, fear, happiness, sadness, and uncertainty. Castel-
lano et al. [70] demonstrated that dynamic body postures could be classified into
anger, joy, happiness, or sadness. Saha et al. [21] identified gestures associated with
five basic emotions: anger, fear, happiness, sadness, and relaxation, using geometric
skeletal features.

2.3.2.2 Physiological expression

At the same time, physiological changes, such as variations in heart rate, skin con-
ductance level or skin temperature, offer internal indicators of our emotions. Al-
though individuals may not always clearly express their emotions through speech,
gestures, or facial expressions, changes in their physiological patterns are inevitable
and detectable [71]. Each emotion is believed to have a specific and consistent
autonomic response pattern. Various physiological responses, such as changes in
galvanic skin response, heart rate, blood pressure, finger temperature, and heart
rate variability , are associated with different basic emotions [53].

2.3.3 Driver emotions in automotive context

Negative emotions, such as anger and fear, are often sparked by various driving-
related factors. The triggers include traffic-related events caused by other drivers [72]
[73], environmental conditions [72] [37] and participation in near-accidents [72] [74].
Zepf et al. [73] also noted that frustration often arises from poor interactions with
vehicle user interfaces, particularly navigation systems. Other sources of negative
feelings include dissatisfaction with one’s own driving performance [72] [73], stressful
conversations with passengers [74], time pressure [74], and insufficient capabilities
of the car [72].

Given that the goal of this emotion-based project is to avoid fostering negative
emotions and not to steer users towards them, it is crucial to consider the factors
that trigger such feelings. These factors can serve as valuable input for the system
in assessing the user’s emotional state more accurately. By recognizing the elements
that lead to negative emotions, the system can better assess and respond to the
user’s current emotional status.

Unlike negative emotions, positive states are usually not elicited through other driver
behaviors, but rather influenced by nice surroundings [72] [73] and personal inter-
actions with passengers [72] [74]. Moreover, drivers gave account of their ability to
drive well and their car’s performance features to cause positive emotions [72] [73].

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2. Literature review

2.4 Emotion detection in car
For effective human-vehicle interactions, it is essential to accurately, consistently,
and efficiently detect the emotional states of drivers and passengers [53]. In the
context of human emotion research in driving, several measurement techniques are
employed. Desmet et al. [75] stated that existing measurement instruments can be
divided into two general categories, psychophysiological measurement instruments
and self-report measurement instruments. Li et al. [53] further classified these
measurements into three categories: physiological measurements, behavioral mea-
surements and self-reported scales.

2.4.1 Physiological measurements
As Li et al. [53] stated, physiological measurements involve capturing and analyzing
biological signals from the body, such as heart rate or pupil dilation, to understand
how emotions affect physiological responses. Physiological measures like heart rate
variability, skin conductance levels, skin temperature, breathing rate, or EEG can
be used to deduce driver states [76] [77] [78]. For example, heart rate gives an
indication of the driver’s state of arousal [79] [80]. Lower heart rates indicate a
more relaxed state, while higher heart rates occur during high driver activation.
Respiration rate is also connected to arousal states, slower and shallower breathing
indicates a relaxed state whereas alerted or active states result faster breathing and
indicate emotional excitement. Skin conductance levels are associated with measures
of emotion, arousal, and attention[81]. EEG signals measured from the top of the
scalp give information about the cognitive and emotional state of the user [82] [83].

However, according to Desmet et al. [75], physiological measures cannot be used to
distinguish emotions since they only indicate the amount of arousal, which is part
of emotion [84].

2.4.2 Behavioral measurements
Behavioral measurements focus on observing and analyzing how individuals act or
react when exposed to emotional stimuli, such as changes in facial expressions or
body movements. Most behavioural measurements are unobtrusive contactless tech-
nologies, such as audio-visual sensors, eye-tracking, and facial expression analysis,
which are more likely to be accepted in cars due to their low initial barriers [85] [86].
In addition, detection of emotion from driving style, posture in sitting, and motion
should be taken into consideration.

2.4.3 Self-reported scales
Self-reported scales, on the other hand, use questionnaires or surveys in which par-
ticipants describe and rate their own emotional experiences in response to specific
stimuli.

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2. Literature review

2.4.4 Other contextual factors
Emotions naturally arise in various situations, including during driving [4]. A
driver’s affective state is continuously influenced by environmental factors (such
as road conditions and weather), situational factors (such as traffic conditions),
and interpersonal factors (such as conversations and user interfaces). These factors
cause the driver’s emotions to fluctuate. Among these, situational factors, such as
the specific circumstances drivers encounter, can enhance the accuracy of emotional
assessments. For instance, a driver rushing to work might experience heightened
anxiety and anger when faced with a traffic jam [53].

All in all, a system that considers emotion measurement in detail from different re-
sources through multiple measurement methods is vital for understanding emotions.
An in-car environment provides a great starting point for such systems, as users are
confined to a limited space and all kinds of sensors are highly common in the interior
of a modern car and widely accepted by users [4].

2.5 Emotion regulation in car
As noted by James [87], emotion regulation involves a wide range of both conscious
and unconscious strategies aimed at modulating our emotional responses. These
strategies can either amplify, sustain, or diminish various aspects of our emotions.

In the context of driving, car systems can employ various techniques to regulate
emotional states and induce desired emotions. Common methods in driving-related
emotion experiments include emotional video clips, traffic scenarios, and music.
Siedlecka and Denson [88] categorize these emotion induction techniques into five
primary types: situational procedures, visual stimuli, auditory stimuli, standardized
imagery, and autobiographical recall. Moreover, emotional behavior itself can act
as an emotional stimulus.

When it comes to emotion regulation, two primary strategies are highlighted. Emo-
tion Regulation, where a target mood different from the current one is set as a
goal; and Emotion Maintenance, where the driver is already in a suitable mood, and
actions are taken to sustain it.

2.5.1 Visual stimuli
Vision is the dominant sense during driving, making visual methods the most preva-
lent for emotion regulation. Research by Siedlecka and Denson [88] indicates that
visual stimuli are particularly effective in inducing basic emotions.

However, at lower levels of vehicle automation, using visual stimuli for emotion reg-
ulation may lead to potential distractions for the driver. This risk can be mitigated
as the vehicle reaches higher levels of automation, allowing for greater flexibility in
visual regulation techniques.

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2. Literature review

Current studies on visual regulation of driver emotions explore various approaches,
including the use of ambient light, visual interventions, state feedback, and visual
relaxation techniques.

2.5.1.1 Ambient light

Ambient light involves using cockpit illumination to regulate driver emotions [53].
Research indicates that ambient light can evoke various emotional responses, influ-
enced by factors such as colors, brightness, positioning, and the driver’s familiarity
with the system [4] [89] [90] [91]. Due to the complexity of this strategy, it will be
discussed in detail in the following section.

2.5.1.2 Visual intervention

Visual interventions are inherently distractive, so their use while driving must be
carefully planned [53]. These interventions, such as film clips or static images, are
chosen to evoke specific emotions. For example, a dramatic movie scene might create
tension, while a serene landscape photo could foster calmness.

2.5.1.3 State feedback

State feedback refers to the visual display that allows drivers to understand their
current emotional states clearly. Researchers’ studies found that direct feedback on
the detected drivers’ states had little value for emotional regulation because visual
state feedback could amplify the driver’s negative emotional states, which was unac-
ceptable to the driver and needed to be avoided examined the visual state feedback
of drivers’ negative emotions [92] [93]. Besides, participants preferred to receive only
safety-critical notifications of the driver’s state [93]. Thus, it is feasible to blatantly
intervene when the possibly dangerous emotional state is likely to occur, such as
providing a simple notification, telling the driver to take a break, and distracting
the driver from the source of negative emotions, as well as presenting a positive
notification to decrease drivers’ negative emotions [94] [92] [93].

2.5.2 Auditory stimuli: Adaptive music
Auditory stimuli can achieve similar effects through sounds such as music or the
comforting voice of a smart car assistant, both of which can soothe or energize the
driver [53]. Dibben and Williamson [95] reported that 70% of drivers listen to music
while driving, and since the introduction of the first car radios, listening to music
has remained one of the most popular activities among drivers. The concept of
emotionally adaptive music in driving contexts to positively influence the driver’s
emotions has been explored in numerous studies [96] [72] [97] [98] [38]. Music, re-
gardless of its type, generally has a calming effect on the driver’s state and enhances
driving behavior [99].

Previous research [72] [97] [98] shows that positive emotional reinforcement occurs
with preferred and familiar music, when singing, and when improvising for musical

15



2. Literature review

individuals. In contrast, complexity, dissonance, and unexpected sounds generally
have a rather negative impact [100]. However, the perception of music and ac-
companying emotions is highly subjective. Thus, one piece of music can hardly be
classified into a category of emotions it will induce. As a solution to this uncertainty
problem, approaches have emerged to annotate music titles with crowd-sourced val-
ues of arousal and valence, such as the DEAM Database for Emotional Analysis
in Music [101]. Researchers are increasingly relying on such databases instead of
subjectively selected music to recommend music. Another challenge in emotion reg-
ulation through music is the recommendation process itself. While offering adaptive
music to influence emotional states is an effective technique, it may lead to user
resistance if they feel manipulated. However, subtly recommending calming mu-
sic to drivers in high-arousal states can help them relax and interrupt the cycle of
emotional reinforcement caused by self-selected music [53].

These findings are crucial for designing music recommendation systems and emotion
regulation strategies, as they highlight how selecting appropriate music can foster
positive emotional responses while avoiding the induction of negative ones. In order
to regulate emotions of users in car, a contextual mood-based music recommending
system capable of regulating the driver’s mood will have to be designed, which uses
various sources of information for tuning their recommendations.

2.5.3 Olfactory stimuli: Aroma
Lenochova et al. [102] stated that human psychological functioning, including per-
ception, mood, cognitive processes, and behaviors, can be influenced by aromas.
Johnson [103] also noted that aroma affects human performance across various con-
texts. Research suggests that certain aromas, such as peppermint and cinnamon,
can enhance driving performance by maintaining alertness during prolonged driving,
potentially reducing accidents and fatalities [104] [105].

The sense of smell is notably sensitive and can quickly detect aromas [104]. Mastafu
et al. [105] found that aromas like lavender and vanilla can positively affect drivers’
emotions, leading to relaxation, increased comfort, alertness, and a sense of fresh-
ness. However, it is also important to note that some individuals may prefer a
non-aroma environment [105]. Additionally, Dmitrenko et al. [106] discovered that
aromas such as rose and peppermint can shift drivers’ emotions toward a more
positive valence.

2.5.4 Haptic Stimuli
Temperature control has been demonstrated to alleviate the effects of high arousal,
creating a more comfortable and calming environment within the vehicle, thereby
enhancing overall user satisfaction [53]. Effective temperature management can mit-
igate high arousal [107] [108]. Schmidt et al. [76] found that cool airstreams can
reduce low arousal, increase alertness, and stimulate sympathetic activity, which
improves driving performance and acceptance. Additionally, there is an intriguing

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2. Literature review

link between temperature and color perception. Research conducted in a light labo-
ratory indicated that room temperature was perceived differently based on the color
of the lighting. Specifically, the room appeared warmer under yellow light compared
to blue light [109].

2.6 Light
Light influences more than just visual perception, which also impacts mood and
emotion. Since lighting is a crucial aspect of this project, I have conducted extensive
research on its effects. Although it falls under the broader category of emotion
regulation, it warrants a standalone section for clarity and emphasis.

Research indicates that colors can affect emotional states [110] [111]. Blue light,
for instance, is effective in treating sleep disorders and depressive mood disorders,
particularly winter-based seasonal affective disorder (SAD) [112] [113] [114] [115].

Light affects mood by influencing the circadian system, which involves the interac-
tion between human biorhythms and the natural environment [116] [40]. Specifically,
light intensity impacts melatonin secretion, a hormone related to alertness [40].

Colored lighting is increasingly used in public spaces to reduce behaviors like suicide
and anti-social activities, though more research is needed to confirm its effectiveness
[113]. The emotional impact of lighting adds value when harmonized with user sce-
narios, influencing emotions such as anxiety or stress through changes in brightness,
color, placement, and behavior [117] [91].

Light positively affects both cognitive [118] [119] and physical [120] functions in
healthy individuals. For example, it can accelerate wound healing, reduce migraine
and tinnitus symptoms, and alleviate reading disorders [113]. In addition, qualitative
and quantitative aspects of workplace illumination are of paramount importance in
determining employee productivity, performance, and well-being [121] [122] [123].

2.6.1 Light dynamic pattern
Ambient light’s dynamic behaviors are often designed to warn or alert drivers, pro-
viding immediate responses and preventing fatigue [124]. Subjects responded more
positively and less attentively to smooth dimming lights, while tension increased
with "sudden-high frequency" patterns, similar to the effect of flickering lights, which
decreased user satisfaction [40].

According to ambient light design guidelines [124], Blink, Fade, and On patterns,
where the entire lighting is controlled simultaneously, are preferred over individually
controlled patterns like Collide, Spread, and Move. Fade behavior was seen as
unobtrusive and more advanced compared to the smooth blink.

Guidelines for dynamic ambient lights include [124]:

17



2. Literature review

1. Discrete blinking lights caused the highest levels of alertness and are suitable
for urgent notifications.

2. Smooth blink is appropriate for non-urgent notifications as it feels less intrusive
and energizing than discrete blinking.

3. On behavior, where the light turns on without a dynamic pattern, scored high
in satisfaction and was seen as the most relaxing.

4. Collide, Spread, and Move behaviors had lower satisfaction scores. Among
them, Spread was seen as more cutting-edge, obtrusive, and interesting, and
it evoked more energy, making it suitable for alerts that need to be attention-
grabbing.

2.6.2 Light Placement
Considering the project aims to implement solutions with minimal cost, I will max-
imize the use of existing in-car ambient lighting. Notably, Caberletti and his team
investigated whether subjects’ emotional responses would vary depending on light
placement, based on self-reports. The study suggested design guidelines for placing
lights to induce the desired mood, which could be useful for future modifications
[125].

2.6.3 Light colors and brightness

2.6.3.1 Information transmission through colorful lights

Research has utilized different light colors to convey signals [91] [90]. Red lights are
commonly used to warn drivers, with urgency indicated by blinking frequency or
additional colors like yellow or amber for less urgent warnings. Colors outside the
red-yellow-green spectrum, such as purple, blue, or white, can direct attention or
display non-safety-related information like temperature or battery status [91] [90].

Participants reported that orange light, due to its similarity to red, indicated some-
thing was wrong and heightened their awareness, although it was not very com-
fortable [89]. In contrast, blue light influenced their emotional state and driving
performance, making them feel more relaxed [89]. Blue lights were also effective in
reducing errors and heart rate, demonstrating a calming effect on drivers [89] [90].

2.6.3.2 Colors on emotion

Researchers have long studied the effect of color on emotion [126] [127] [128]. Valdez
and Mehrabian [126] generalized emotional patterns to different colors by assessing
pleasure (valence), arousal, and dominance. They found that brighter and more
saturated colors generally elicited greater pleasure, with this relationship being non-
linear. Pleasure was more influenced by brightness than by saturation. Colors

18



2. Literature review

like blue, blue-green, green, red-purple, and purple elicited higher pleasure levels
compared to green-yellow, yellow, and yellow-red.

Wright and Rainwater [129] found that higher color saturation and brightness cor-
related with increased arousal. Valdez and Mehrabian [126] elaborated that arousal
increased linearly with color saturation and had a ladle-shaped relationship with
color brightness. Green hues (green-yellow, blue-green, and green) elicited the high-
est arousal reactions.

Guilford and colleagues [127] [128] found that the most preferred colors were blue,
green, purple, violet, red, orange, and yellow, which aligns with the light color
preferences identified in Kim’s study [40]. Additionally, brighter colors (e.g., whites,
light grays) are generally more pleasant, less arousing, and less dominance-inducing
than darker colors (e.g., dark grays, blacks) [126] [127] [128] [130]. This finding
is consistent with research indicating that subjects tend to have better moods in
brighter light settings [131].

Conclusions from color psychology have been validated in experiments with a limited
range of light colors, supporting the applicability of color-guided mood theories to
the effects of lighting on mood in automotive environments.

2.6.3.3 Colorful lights on emotion

The effect of lighting color on health, well-being, mood, and performance has been
extensively studied [113]. Most research focuses on the calming effects of blue light,
which has been scientifically validated [40] [90] [89] [4] [124]. However, there is no
consensus on the emotional impacts of different light colors. For instance, blue and
orange-enriched lights have distinct emotional effects, but a theoretical framework
linking specific light values to emotional responses is lacking.

Current research offers some insights. For example, A study conducted by Kim
[40] found that subjects generally preferred blue, warm white, and cool white lights
over red and green, with red light causing more tension. Orange-enriched white
lighting creates a luxurious atmosphere, while blue-enriched white lighting enhances
alertness [125] [132]. Åkerstedt et al. found that bright, blue-enriched car interior
lighting increases morning alertness, with higher color temperatures (6500K) being
more effective than lower ones (3500K) [133] [134] [135] [136].

While specific lighting colors have been shown to influence emotions, more research
is needed to develop precise methods for using a broader range of colors of lights
to induce desired emotional states. However, the color effects on emotions could be
generalised on the colorful lights as well.

In general, evidence available from studies that have used a variety of color stimuli
(including colored objects, rooms, or clothing), when interpreted within the PAD
Emotion Model, tends to be consistent with the results obtained in the studies
by Valdez and Mehrabian [126]. Valdez and Mehrabian tentatively concluded that

19



2. Literature review

their results could be generalized to color stimuli encountered in everyday situations
[126]. Although these are speculative, they may help identify promising avenues
for developing a theoretical rationale to explain emotional reactions to light’s colors.
Given the limited color samples in light experiments, I propose applying the emotion
induction theory from color studies to the field of ambient lighting colors.

The light will be quantified by the PAD values. Valdez and Mehrabian [126] used
the abbreviations P for pleasure, A for arousal, and D for dominance, the effect of
brightness is summarized as follows:

Brightness = +P − A − D (1)

or
Darkness = −P + A + D (2)

Not only color can be measured by PAD values, emotions can be measured through
equation with PAD model as well. For example, Mehrabian and O’Reilly [137] ob-
tained Equation (3) for aggression, and Russell and Mehrabian [58]obtained Equa-
tion (4) for anger.

Aggression = −0.36P + 0.20A + 0.28D (3)

Anger = −0.74P + 0.36A + 0.09D (4)

By using the PAD values and those equations, I can systematically evaluate how
different lighting conditions impact emotional states and how to adjust different
light values to induce the desired states. This approach not only enhances the
understanding of the psychological effects of light but also aids in the practical
application of ambient lighting to influence mood and behavior in various settings.

2.7 Summary
While much research has focused on leisure experience design during commuting,
these studies often assume AVs context [13] [30] [14] or target on passengers [46] [24]
[45] [29] [48]. However, there are still many technical and organizational issues to be
addressed before reaching the fully autonomous driving [12]. In fact, several experts
expressed their belies that the fully autonomous driving will not arrive in 10 years
in the interviews. Therefore, there is a gap between the conceptual solutions and
the real implementation for leisure experience design. Additionally, only few studies
address driver-centric leisure activities. This project aims to bridge these gaps by
focusing on the driver’s experience in partially autonomous context.

Additionally, there have been numerous proposals to rethink the commute and turn
it into a time for enhancing human well-being through various activities such as

20



2. Literature review

stress management, fitness, socialization, gamification and more. Many of these
innovative design innovations falls under the categories, such as Car as a caretaker
[8] [26] [13] [27] [51] [52], Car as a space for stimulation [49] [47] [29] [45] [46] [24]
[48] [30], Car as a space for social relatedness [31] [32]. However, designs for Car
as a space for transition between home and work remains largely unexplored. This
projects will contribute to this area by specifically helping drivers prepare for the
next stage of their day through emotion-based multisensory experiences.

Furthermore, a comprehensive research effort has been conducted to explore strate-
gies for both emotion detection and regulation. Understanding emotions needs a sys-
tem that considers emotion measurement in detail from different resources through
multiple measurement methods [4]. Thus, the design in this project will integrate
the physiological measurements, behavioral measurements, self-reported scales and
other contextual factors in the emotion detection system.

Lastly, there are many studies focused on emotion-based affective driving [138]
[4] [42]. Additionally, numerous studies have explored various emotion regulation
strategies, such as music [99] [97], aroma [105] [104] [106], ambient lights [116] [115]
[121] [109] [111], and haptic senses [51] [16]. However, none have combined multiple
strategies into a single in-vehicle system. This design project will integrate these
strategies to create a comprehensive multisensory experience. Regarding the visual
strategies, while specific lighting colors have been shown to influence emotions [125]
[132] [40], more research is needed to develop precise methods for using a broader
range of colors of lights to induce desired emotional states. This project will gen-
eralize the color effects on emotions on the colorful lights. This remains one the
limitations of this project.

In summary, the contributions will be:

• Driver-Centric Leisure Experience in conditional AVs context: While
much research has focused on leisure experience design during commuting,
these studies often assume an automated driving context or target on passen-
gers. However, few studies address driver-centric leisure activities. The work
fills this gap by focusing on the driver’s experience in conditional AVs context.

• Transition Between Home and Work: Designs under the transition UX
theme have been largely unexplored, and the work contributes to this area
by specifically helping drivers prepare for the next stage of their day through
emotion-based multisensory experiences.

• Multisensory Experience: Although many studies have explored various
affective strategies, none have combined multiple strategies into a single in-
car system. The design integrates these strategies to create a comprehensive
multisensory experience.

21



2. Literature review

22



3
Method

This study adopts the Research through Design (RtD) approach, a methodology that
generates new knowledge by iteratively engaging with the design process to analyze
the present state and propose an enhanced future state through design interventions
[139]. RtD involves a process of deep reflection and iteration, where researchers gain
insights by understanding users, identifying problems, and exploring the context
in which improvements are possible. This methodology is particularly well-suited
for investigating complex, open-ended problems, as it merges design practice with
theoretical reflection to explore innovative concepts, methods, and applications.

In the initial phase of the design study, I conducted expert interviews within the
company to grasp the core essence of Polestar, which helped establish the design
guidelines for the entire project and set the criteria for selecting design concepts in
the subsequent workshops. After developing the design concept Commuting therapy,
I used an AR car simulator to evaluate the results through two assessment tools:
the Product Emotion Measurement (PrEmo) and the User Experience Questionnaire
(UEQ). Finally, I conducted a semi-structured interview to gather further insights.
The chosen evaluation method and the questions for the semi-structured interviews
were structured based on Jordan’s framework of product pleasures.

This chapter introduces the design framework that outlines the overarching guide-
lines for the project. It also presents several detailed steps within the overall Re-
search through Design (RtD) methodology used in the study design.

3.1 Design framework
The design framework used in this study is Jordan’s Four Product Pleasure model
[140]. Specifically, the four pleasures of the product are physio-pleasure, socio-
pleasure, psycho-pleasure, and ideo-pleasure. Physio-pleasure is derived from sen-
sory experiences, including touch, taste, smell, and feelings of sexual or sensual
pleasure. Socio-pleasure arises from the enjoyment of social interactions and the
company of others. Psycho-pleasure is obtained through the successful completion
of tasks, highlighting how a product can facilitate task completion and create a
satisfying experience. Ideo-pleasure relates to the aesthetics of a product and the

23



3. Method

values it embodies. Considering all these four aspects helps me design pleasurable
experiences to enhance the user experience during daily commutes.

I applied Jordan’s Four Product Pleasures model [140] throughout the UX design
process, from assessing current situations, identifying design opportunities, imple-
menting design interventions, to evaluating the outcomes. The integration of the
framework into my design process is outlined as follows:

1. A desired experience: Propose a desired pleasurable leisure experience for
daily commuting.

2. Current situation: Look into the current commuting situation, What plea-
sures are associated with the current commuting experience?

3. Design opportunities: To identify design opportunities for achieving the
desired experience, I can employ three strategies: strengthen existing needs,
introduce new needs, or reduce needs that are negatively impacted by the
current product [57]. Additionally, I can further explore which pleasures can
be enhanced or introduced.

4. Design intervention: Take design interventions to achieve the desired expe-
rience.

5. Evaluation: Evaluate the final design solution by assessing the extent to
which it fulfils the desired product pleasures.

3.2 Study design

3.2.1 Preliminary Expert Interview Study
In the initial phase of my study, I conducted a series of semi-structured interviews to
delve into the essence of Polestar. The questions were structured around key themes
such as brand values, design philosophies, target users, emerging technology trends,
and the future of Polestar. These interviews also aimed to explore participants’
expectations and visions for future leisure experiences with the Polestar brand.

3.2.1.1 Process

I conducted a total of 13 interview sessions, including 12 individual interviews and 1
group interview, each lasting approximately one hour. To ensure comprehensive data
collection, all interviews were recorded audio, and some of the online sessions were
also recorded video. My interview process involved a primary interviewer and an
observer. The main interviewer was responsible for posing the questions, while the
observer focused on noting nonverbal cues, taking detailed notes, and contributing
additional questions towards the end of each session.

24



3. Method

The interview data were promptly transcribed during or immediately after each
session to preserve the accuracy of the participants’ responses. The transcriptions
were then broken down into numerous short notes that capture the significant state-
ments made by the participants. For the analysis, I used affinity diagramming to
systematically categorize and identify common themes in the collected data.

3.2.1.2 Participants

The participants consisted of sixteen employees from various departments within
Polestar. The aim was to gain a comprehensive understanding of Polestar’s design
philosophy from diverse professional perspectives. The objective was to gather in-
sights that would establish a guideline ensuring the project’s alignment with the
Polestar brand and to enhance its possibility for real-world production.

The participants represented a broad spectrum of expertise:

User Experience Design Team: 8 experts
Engineering and Technical Team: 3 experts
Interior Design Team: 3 experts
Innovation Design Team: 2 experts

These interviews were designed to harness the specialized knowledge and viewpoints
from across these different fields, thereby enriching my approach and paving the
way for future project implementation within Polestar. The general questions are
attached in the appendix, but I revised several questions according to different
expertise of the participants I interviewed.

3.2.1.3 Results

The results of this phase were used to find the common consensus of core value and
leisure experiences within Polestar.

In addition to using these findings as guidance for the development of the future
design of leisure experiences, they also provided me with a good understanding of
the essence of Polestar. These perspectives were translated into references that were
utilized in the next study phase, Ideation workshops, to inspire the participants and
help me to narrow down the ideas.

The essence of Polestar encompasses key topics such as design philosophy, design
implementation, brand positioning, and target users. Experts described Polestar
as a sophisticated, luxurious, high-performance, and sporty brand. The UX de-
sign manager emphasized that Polestar aims to develop simple products powered
by complex technologies, making advanced features intuitive for users. He high-
lighted that Polestar prioritizes seamless user experiences over flashy or gimmicky
functionalities. The focus is on integrating sophisticated technology in a way that
feels natural and effortless for the user, ensuring that every interaction is smooth

25



3. Method

and straightforward.

Most experts emphasized that Polestar is a design-driven company, prioritizing de-
sign in its decision-making processes. They expressed confidence in Polestar’s UX
system, frequently using terms such as "simple," "minimalistic," and "Scandinavian"
to describe its design language. The digital design style is characterized by phrases
such as "reduced interface," "big and bold buttons," "scroll forbidden," "cutting cor-
ners," and "simple but intuitive," with an emphasis on distinctiveness. An expert
stated that Polestar’s products are often compared to Apple products, focusing on
minimalism, technology-centric features, and excellent user experiences. The com-
pany maintains strict control over aesthetics and errors, allowing only two font sizes
and five colors in the UX system, without permitting user variations in color.

Many experts noted that Polestar’s target user group overlaps with that of Ap-
ple products, consisting of technology enthusiasts eager to explore new innovations.
For example, these users buy Vision Pro not necessarily to solve problems, but to
experience cutting-edge technology. Other experts also envisioned tech-driven car
enthusiasts, likely cool young individuals with a strong interest in technology. Given
the price point of Polestar cars, the target age group has been adjusted to 30-40
years, aligning with the affordability of Polestar products. This demographic is often
characterized as "middle-aged individuals with a strong interest in technology and
refined taste" and "affluent individuals who value well-crafted products with excep-
tional quality and performance." Polestar aims to serve these discerning customers
who appreciate the seamless integration of advanced technologies into their vehicles.

When implementing designs in Polestar vehicles, two key factors are prioritized:
market needs and investment control. Market demand is the driving force behind
design, which is essential to align new features with consumer preferences, though
predicting these needs can be challenging. Additionally, the effective management of
financial resources ensures that investments in design and technology deliver value.
A notable example is the "Breath" project, a digital app developed for in-car deep
breathing exercises, which averaged two minutes of user engagement. This app was
integrated into Polestar cars and downloaded by over 1000 users, showcasing how
market needs and controlled investment can drive successful project implementation.

Experts in the automotive industry are dedicated to staying ahead of cutting-edge
technological trends, ensuring they provide the most innovative and refreshing in-
sights. Key themes frequently mentioned by these experts include:

1. Artificial Intelligence: Artificial intelligence has made significant strides
across various fields and has become so prevalent that every expert I inter-
viewed acknowledges its impact and anticipates its crucial role in enhancing
user experience in the automotive industry. AI enables more precise contextual
usage and tailored personal experiences in cars. However, there was debate
among experts about whether AI functionalities, which are already feasible
on mobile phones and computers, are necessary in automotive environments.

26



3. Method

If AI is integrated into vehicles, the challenge lies in distinguishing its appli-
cations in a car from those on other devices. The goal is to ensure that AI
provides unique, valuable benefits specific to the driving experience.

2. Autonomous driving: Autonomous driving is a pivotal topic in the realm of
technology, with widespread belief that, despite the common assertion that it’s
just around the corner, it still has a considerable journey ahead. Experts agree
that complete autonomy is unlikely to be realized within the next 20 years.
Currently, Polestar’s autonomous driving capabilities fall between Level 3 and
Level 4, which must be factored into the design of in-car leisure experiences.

3. Human-machine interface: The interaction between humans and machines
has evolved beyond traditional digital or physical screens to include a variety of
advanced technologies. These include gesture recognition, voice recognition,
head or eye tracking, proximity-based wake-up systems and so much more.
The accuracy of these input and recognition methods is continually improv-
ing, with reaction times becoming increasingly swift. Designers are focused
on seamlessly integrating these interactive technologies to optimize their effec-
tiveness and minimize distractions across different scenarios, particularly for
drivers. This approach aims to reduce cognitive load and enhance overall user
experience.

4. Health monitoring and management system: The Polestar 4 is equipped
with a driver monitoring camera that tracks the driver’s attention and fatigue
levels. This camera is mounted above the dashboard, aimed directly at the
driver’s face, and provides real-time monitoring of the driver’s eye activity
and blinking frequency. By analyzing these data points, the car system can
determine whether the driver is focused on the road or showing signs of fatigue.
Additionally, the Polestar 4 features a handwheel monitor sensor designed to
detect if the driver’s hands are positioned correctly on the steering wheel. This
function is optional and can be activated at the driver’s discretion to reduce
user resistance.

5. Virtual Reality and Augmented Reality: Virtual Reality (VR) and Aug-
mented Reality (AR) technologies have significantly transformed how infor-
mation is presented, offering users immersive experiences in various domains.
For instance, Meta’s Oculus Quest (Meta, 2023) provides a fully immersive
VR experience for gaming and virtual meetings, while Microsoft’s HoloLens
(Microsoft, 2023) utilizes AR to overlay digital information onto the physi-
cal world, enhancing tasks such as remote assistance and interactive training.
Experts highlight that Polestar is actively developing AR glass, though its
specific functionalities and use cases are still under exploration. Integrating
AR and VR into the design of in-car leisure experiences is crucial, driven by
both technological trends and Polestar’s substantial investment in these tech-
nologies, which offers a solid foundation for growth. For example, envision an
AR navigation system akin to the one developed by WayRay (WayRay, 2023),

27



3. Method

which projects directions directly onto the windshield, or a VR entertainment
system inspired by HTC Vive (HTC, 2023), providing immersive content dur-
ing autonomous driving. These innovations have the potential to significantly
enhance the user experience within the vehicle.

When discussing the leisure experience in cars, experts highlighted numerous inno-
vative features that go beyond traditional offerings such as video streaming, gaming,
and karaoke. For example, Tesla offers a fireplace mode, where users can enjoy a
virtual fireplace displayed on the center screen with the soothing sounds of crackling
wood. Another notable feature was from the now-defunct brand Hiphi, which pro-
vided a charging port on the car roof for camping devices. Polestar 4 has introduced
an animal mode, allowing users to leave their pets in the car with the climate con-
trol running in auto mode. Many experts agreed that providing unique features not
available on mobile phones would significantly enhance the in-car leisure experience.
Common themes mentioned in this context include wellness and well-being, empha-
sizing the importance of creating a relaxing and enjoyable environment within the
vehicle.

1. Entertainment: Some experts anticipate the development of more immersive
and sophisticated entertainment systems for music, gaming, and videos in
cars. For instance, they envision features like theatre mode for a cinematic
experience, connectivity between cars for multiplayer gaming, communication,
and even driving competitions. These advancements aim to transform the in-
car experience, making it more engaging and interactive, and providing unique
entertainment options that go beyond what is available on mobile devices.

2. Driving experience: Polestar started as a driver-centric brand and continues
to emphasize the driving experience. Many users view driving as a source of joy
and stimulation. For instance, Mercedes has introduced a feature that allows
drivers to improvise songs using the steering wheel while driving (Mercedes-
Benz, 2023). This illustrates the potential for further innovations to enhance
the driving experience. By integrating advanced technologies and creative
functionalities, Polestar can continue to elevate the joy of driving, making it
more engaging and enjoyable for users.

3. Mindfulness: Some experts have noted that our daily lives are inundated
with information, creating a constant influx of data to process. As a result,
many drivers seek moments of mindfulness while on the road, desiring a break
from the technological world. They appreciate features that offer mindfulness
relaxation or meditation, which can benefit their mental health. Integrating
these calming and restorative experiences into the driving environment can
help drivers detach from the constant stream of information and find tranquil-
ity, enhancing their overall well-being.

4. Wellness and well-being: Some experts have observed that our daily lives
are already saturated with information, leading many drivers to seek moments

28



3. Method

of mindfulness while driving. They desire opportunities to detach from the
technological world and enjoy relaxation techniques that benefit their mental
health, such as mindfulness exercises or meditation. These features can provide
valuable moments of tranquillity in the constant flow of information. However,
the UX manager noted that in his years of experience with health monitoring,
the typical solutions — such as mindfulness exercises, ambient lighting, or
calming music—often need to be chosen with caution. These elements must
be carefully integrated to ensure they enhance the driving experience without
becoming distractions or detracting from overall safety.

When discussing the future of Polestar cars, most experts agree that vehicles will
continue to serve primarily as tools for transportation. The future selling point of
cars is anticipated to be their role as a private space, which is essentially a flexi-
ble, mobile extension of one’s home. Experts predict that, even in a decade, users
will still need to connect their phones to their cars to access music and other func-
tionalities. After exploring intricate features and decorative gimmicks, car interiors
and functionalities should refocus on what genuinely matters to drivers. Stream-
lined, intuitive designs that prioritize practicality and user experience are expected
to become central to future automotive developments.

Additionally, there are challenges in advancing UX design due to the need to ac-
commodate different platforms across various generations of cars. For example,
the Polestar 4 is built on Geely’s SEA platform, which is tailored for the Chinese
market, while other models are based on Volvo’s SPA2 platform. This discrepancy
requires designers to ensure a consistent user experience across diverse platforms,
presenting a significant challenge. Maintaining uniformity in UX design while cater-
ing to platform-specific requirements is crucial for delivering a cohesive and seamless
experience for all users.

3.2.2 Ideation workshops
One form of innovative methods is creative sessions, such as design workshops, where
participants (users) are invited to generate ideas and communicate their thoughts
[141]. I organised two workshops, both within and outside the company to get
diversified creative thoughts. Subsequently, I identified several fields that are most
promising in the automotive leisure experience based on previous research.

1. Car as a space for transition: The state of experiencing calmness and
reduced stress, often achieved through restful activities that soothe the mind
and body.

2. Car as a space for stimulation: The feeling of heightened energy and
enthusiasm, typically resulting from engaging in stimulating or thrilling activ-
ities.

3. Car as a space for social relatednee: The sense of connection and belong-

29



3. Method

ing with others, derived from meaningful interactions and shared experiences.

4. Other: Anything participants can conceive, ensuring their thoughts are un-
restricted and encouraged to explore freely.

The mutual methodology I used in different ideation workshops is brain writing.
Brain writing is a collaborative ideation technique in which participants silently
write down their ideas on a specific theme and then pass them on to others to build
upon. However, unlike the traditional brain-writing technique, which minimizes
verbal communication, I allowed participants to explain their ideas verbally to build
a mutual understanding.

Building on previous research, I directed my design towards creating a multi-sensorial
experience within intelligent cockpits. In my first workshop, I facilitated sensory
exploration by encouraging participants to engage with various sensations, particu-
larly emphasizing tactile and olfactory experiences. The second workshop adopted
a broader context beyond automotive applications, encouraging diverse and unex-
pected ideas. Moreover, the second workshop built upon insights and outcomes
derived from the initial session.

3.2.2.1 On-site workshop

The on-site workshop took place in a dedicated room adjacent to the car show
hall at the Polestar HQ. This location allowed participants to seamlessly transition
between the workshop discussion environment and the real-world car scenario, fa-
cilitating a more immersive experience. I sent out invitations and prepared various
refreshments, including drinks, snacks (candy and chocolate), as well as necessary
materials such as sticky notes, whiteboards, and pens. Additionally, I focused on
engaging different sensations, particularly tactile and olfactory experiences. To facil-
itate this, I provided various scents and Arduino components (Soma bits) to enhance
sensory exploration.

Figure 3.1: Workshop preparation

30



3. Method

There were our participants took part in the session: three from the User Experience
Design team and one from the User Experience Attributes team. All participants
are avid drivers with a strong passion for technology and a deep understanding of
cutting-edge advancements.

I began the workshop with a 15-minute lightning talk, presenting PPT slides to
inform participants about the project’s background, objectives, latest technological
advancements, academic research, and methodologies. During this session, I also
outlined the day’s agenda, goals, task briefs, and workshop rules, emphasizing a
non-judgmental and egalitarian environment where generating a quantity of ideas
took precedence over immediate quality.

Following this, I started an icebreaker exercise designed to stimulate the senses
through the Soma experience, lasting 40 minutes. Firstly, I guided participants to
do a body scanning to figure out what sensation was stood out at the moment, and
used body map to visualise the feelings. This was done to activate the body senses in
order to invite participants to pay more attention to their body senses while ideating
in the car context. Then, I asked participants to move to the show hall, where they
could sit inside the Polestar 2 to practice breathwork, acupressure, feldenkrais, and
meditation as guided exercises. After that, they went back to the original room to
explore the soma bits for different sensory responses. In the following, they redrew
the bodymap. In the end, I organised a brief discussion where participants shared
their body maps and favourite exercises.

The main part of the workshop focused on the commute scenario, situations that
could take place in the context of transition between home and work, especially stop-
and-go traffic jams. The task was to come up with new ideas for leisure experience
that could enhance the commuting experience in general or in a specific situation.
Thus, they were introduced to the project scenario:

" It’s Tuesday evening, and Eric is heading home from work, a journey that typically
takes him about an hour. However, today the traffic is unusually heavy, and he finds
himself in a stop-and-go situation for what seems like forever. What can I do to
make the mundane commuting experience more pleasant?"

The methodology I used for the workshop is called brainwriting. Brainwriting is
a collaborative ideation method where participants write down their ideas rather
than verbally sharing them, fostering creativity and inclusive participation in team
settings. Brainwriting was structured in several directions that I found to be the
most promising in the academic field, which are relaxation, social aspects, and
exitement. However, I did not want to limit the thoughts of my participants, so
I added one more category, which is called "Others". In order to help participants
understand different categories more profoundly, I printed and hanged the pictures
and definitions of different categories from Desmets’ 13 fundamental physchological
needs on the wall.

31



3. Method

There were two rounds of brainstorming. In the first round, participants were asked
to think about an in-car leisure experience that transforms the boring, negative
experience to an enjoyable, positive experience. based on the story and the pain
points. They were able to write, draw, or even act out (Body storm) with the
artifacts to ideate at least 3 ideas within 6 minutes. At the end of each session, they
took turns explaining the idea and started brainstorming in another category. They
were encouraged to build on the ideas of other participants.

In the second round of brainstorming, participants were asked to come up with a
final idea in 5 minutes, consider merging, integrating or building on their past ideas
and the ideas of others they liked. In the end, they were asked to explain the ideas
in turn.

The brainstorming workshop yielded significant insights that will shape the upcom-
ing online workshop and the future direction of this project. The primary objective
was to harness collective creativity and identify innovative solutions to enhance
leisure user experience in Polestar vehicles.

Several design directions emerged during the session:

1. Car as a space for transition: To enhance relaxation and comfort, the
participants suggested features such as reclining or massage seats and mood
lighting, creating a "Yoga Mode" for the vehicle.

2. Car as a space for stimulation: Participants proposed various ways to
increase excitement during the drive. Hands-on activities could include en-
gaging in physical or digital construction projects, such as woodworking or
programming Mindstorms kits, ranging from simple to complex tasks. Digital
interaction opportunities for music creation and programming were suggested,
catering to tech enthusiasts. Additionally, driver-centric features focusing on
fun, stimulation, and speed were highlighted to enhance the driving experience
for automotive technology enthusiasts.

3. Car as a space for socialization: In exploring socialization within the
vehicle, participants proposed various innovative approaches to enhance in-
teractions among occupants, between vehicles, and with people outside the
car.

(a) Co-Experience Among Occupants: To enrich the shared experience
within the vehicle, participants suggested facilitating intellectual engage-
ment through stimulating conversations and interactive questions. Col-
laborative digital or physical projects and karaoke sessions were proposed
to encourage teamwork and fun. Additionally, integrating window dis-
plays to engage with landmarks and provide context could enhance the
overall experience for all occupants.

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3. Method

(b) Connection Between Cars: For interactions between vehicles, the fo-
cus was on facilitating casual communication during traffic jams. Ideas
included implementing features that allow vehicles to share emotions or
offer advice through vehicle labels, thereby improving understanding of
road conditions and fostering connections among drivers. This could also
help in enhancing communication among commuters and improving over-
all traffic flow.

(c) Connection with People Outside the Car: To strengthen connec-
tions with people outside the vehicle, participants suggested enhancing
family and friends interactions. This could involve features for playing
games with children, connecting with nearby friends for social events,
or planning activities together. Options