Exponential problems it creates or alerts us to.”

Exponential technological growth ”We are energized by the great power of technological impact on us.

We are intimidated by the magnitude of problems it creates or alertsus to.” Herbert Simon, Nobel Prize Winner 1978, Economics (Boutellier andHeinzen, 2014, p.1) In 1965 Gordon Moore, the co-founder of Intel, predicted that in the futureprocessing power would double every 18 months. ‘Moore’s Law’ is stillreferred to today to predict the growth of technology (Loveridge, 1990).Revolutionary technological developments have a large impact on everyaspect of human life. Technologies such as 3G and 4G, smartphones and theWorld Wide Web provide numerous benefits and have simplified our lives.

We now have easy access to information and education, financialtransactions can be completed online, and world trade business is conductedfaster. But the exponential growth of technology is also causing difficulties(Loveridge, 1990). The McKinsey Global Institute’s report ‘Disruptivetechnologies’ of 2013 explores how technological changes transform the waywe live and work, stating: “Business leaders and policy makers need to identify potentiallydisruptive technologies, and carefully consider their potential,before these technologies begin to exert their disruptive powers inthe economy and society.” (Manyika et al.

, 2013, preface) The report analyses technological developments in automation, the internetof things, cloud technology, advanced robotics, energy storage, 3D printingand more. Predicted changes in established norms and technologicaldevelopments will force society to adapt (Manyika et al., 2013). One disciplinehighly influenced by these technological developments is the automotive 16 industry. A selection of the most popular current and future technologicaldevelopments in the automotive industry is presented in Table 1 below. Development Connected cars, Vehicle to vehicle (V2V) communication Real-time internet of things (IoT) connectivity Increasing number of sensors implemented Gesture control systems Voice recognition Electric cars In-car connectivity: Internet connection Integration of social media Integration of mobile devices Augmented reality included into the interface Partially autonomous driving Driver assistance features Fully autonomous driving Current/Future Source Sophistication of in-car technologies Current Manyika et al.

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, 2013 Disruptive Technologies Current andfuture Current Current Currentfuture Current Current Current Future Intland, 2016; Kalogianni,2016; Karlsson, Ahn andChoi, 2017 Manyika et al., 2013 Ropert, 2014 Manyika et al., 2013; TheGuardian view of the carindustry: an electric future,2017 Brauer, 2015;Kalogianni, 2016;Karlsson, Ahn and Choi, 2017 Ropert 2014 Kalogianni, 2016 Karlsson, Ahn and Choi, 2017 • Car sharing Current and Harris, 2017; and • Shared mobility future Manyika et al., 2013 Table 1 Most popular current and future technological developments in the automotiveindustry 1.1 Developments in the Automotive Industry The main focus of automotive research on basic functional requirements from1886-1919, changed from 1920-1930 with the dawn of human factors.Increasing speed, growing numbers of vehicles on roads and increasingtravel times called for a shift in focus towards safety from 1940-1949. Furtherdevelopments in the 1960s included 3-point-seatbelts and research onmental workload and driver fatigue. In the 1970s and 80s emphasis on driver 17 comfort grew.

With an increasing number of functions in the automobile andconcentration on the user experience the focus of research shifted towardsthe driving experience. The development of multimedia interfaces andnavigation systems was followed by lane-keeping, breaking and blind-spot-warning systems in the 2000s, a significant step towards further automationof automobiles (Akamatsu, Green and Bengler, 2013; Miller, 2001; Normarkand Gkouskos, 2012). Today, the connected car has improvedcommunication, connection and networking (Manyika et al., 2013), majorsteps towards autonomous driving (Figure 1). Figure 1 Technological developments in the present and future (Karlsson, Ahn and Choi,2017) In the future self-driving technologies are forecasted to enhance driver safety, reduce traffic congestion etc.

(Thrun, 2010). The number of sensors implemented in the automobile is constantly increasing (Manyika et al., 2013). Infotainment systems are offering more entertainment options (Regan, 2004) and connected automobiles do not only offer wireless internet access, but also connection to a broad network of automobiles and enable V2V communication. Gesture control systems are developing; augmented reality is included into the automobile interface (Ropert, 2014). The amount of 18 software and technology built into automobile interfaces and applications fornavigation, music, internet, communication and connection to social networkschallenge the driver by providing a large volume of information.

Drivers arepreoccupied with electronic devices, potentially degrading performance,impacting road safety. Attention sharing in a hazardous environment, such asthe driving environment, presents a significant safety issue (Regan, 2004). Self-driving automobiles could transform the driving environment from apotentially stressful environment requiring high concentration andresponsibly, to an environment for relaxation and social interaction (RandReport, 2014). While increasing automation is predicted to enhance safetyand decrease the environmental impact of automobiles, concerns regardingself-driving vehicles arise, such as fears of privacy issues and hacking of on-board computer systems (Ropert, 2014). The greatest obstacle in the way ofdeveloping technologies for the automotive environment is humanacceptance (Thrun, 2010). With increasing automation and growingsophistication of in-car technologies customer behaviour and needs willchange (Gao et al., 2016) and a more emotional relationship between driversand their automobiles will be created (Michael, 2001; Hagel et al., 2017).

When comparing the developments in the automotive industry to Maslow’sPyramid of Human Needs multiple comparisons are obvious. In his book ‘ATheory of Human Motivation’, Maslow explains human motivation through hispyramid visualising the hierarchy human needs. Even though the model wascreated in 1943, it is prescient in its content and often referred to in modernresearch. In Maslow’s Pyramid of Human Needs the appearance of one needrests on the satisfaction of the prior need (Maslow, 1943). This approach hasbeen used as an analogy in multiple disciplines, such as marketing or design(Heppard, 2015; Baches, 2016) and has some strong similarities to thedevelopments in the automotive industry and research (Figure 2). 19 Figure 2 Analogy between Maslow’s Pyramid of Human Needs and historical developments in the automotive industry (based onAkamatsu, Green and Bengler, 2013; Hagel et al., 2017; Miller, 2001; Normark and Gkouskos, 2012) 20 Figure 2 Analogy between Maslow’s Pyramid of Human Needs and historical developments in the automotive industry (based on Akamatsu,Green and Bengler, 2013; Hagel et al., 2017; Miller, 2001; Normark and Gkouskos, 2012) While the first four stages of physiological needs, safety, love/belonging andesteem can be seen in parallel to the past developments in the automotiveindustry of transportation, safety and human factors, comfort and experience,the peak of the pyramid is based on predictions and recent and futuredevelopments.

In order for future automotive design to adapt to thementioned challenges the traditional automotive design process needs toadapt (Giuliano, Germak and Giacomin, 2017). A shift towards humanemotion and a more human-centred approach to automotive design isrequired. To accomplish this the significance of the role of emotion in thedriving environment must be gauged. 1.2 The Importance and Role of Emotion The automotive environment is highly emotional (Sheller, 2004),encompassing the driving experience, corresponding feelings and emotionalstates (Carrabine and Longhurst, 2002), the social relationship between theautomobile and driver (Hagman, 2010), the emotional values an automobileobjectifies (Urry, 2004) and the identification of drivers with their vehicles(Edensor, 2004). The emotional components of the driving experiencebecome apparent through expressions like “thrill of driving”, “passion of thecollector” (Sheller, 2004, p.5) and often directly involve expressions with ahigh emotional value (Miller, 2001; Sheller, 2004).

Semantics addressingemotions, feelings or desires are used in marketing strategies of majorautomobile companies such as BMW with the headline “Joy is BMW”(Blanckenberg, 2009) or Peugeot using “Motion and Emotion” (PeugeotMotion & Emotion, 2010). The emotional significance of the pleasure ofdriving for instance can be explained by the “kinaesthetic experience” (Katz,2001, p.144), which defines driving as an embodied and sensuousexperience and emphasises the feelings created through the experience of”movement and being moved together” (Sheller, 2004, p.68). The relationship between drivers and automobiles might be the most 21 emotional human-machine-interaction (Michael, 2001; Miller 2001). Theautomobile is personified as a companion or even as wife or lover (Sheller,2004). This relationship is reinforced by major automobile companies,offering applications emphasising the connection between driver andautomobile such as watches or mobile applications, which create a 24-hourbond between human and machine (e.

g. BMW smart watch). Moreover, theautomobile is strongly connected to significant human values, such asfreedom and independence (Sheller, 2004). The ownership of an automobilecreates the feeling of power and freedom; the automobile is often referred toas a status symbol eliciting feelings such as pride and power (Urry, 2004).Moreover, ownership is strongly connected to the identification of a driver withhis/her vehicle (Hagman, 2010). The purchase choice is strongly influencedby the values and characteristics the buyer can identify with (Hagman, 2010).The decision to purchase an automobile is an emotional one, as theidentification with the vehicle includes self-reflection and self-realisation(Carrabine and Longhurst, 2002).

A strong identification again leads to astronger connection between human and automobile (Sheller, 2004). “Car design influences the lives of millions of people throughout theworld. Whether the car serves as merely a practical means oftransport or as an extension of one’s personality, its design andbrand will always attract comment.” (Newbury, 2002, p.

11) Research (Hsu, Lu and Ho, 2013; Warell, 2008) into the visual appeal ofautomobiles, such as the study by Cornet and Krieger (2005), identified thefour most important influences on the purchase of an automobile as “exteriorstyling”, “interior styling”, “trendy” and “makes me feel attractive” (Cornet andKrieger, 2005, p.1). Factors such as expression, emotional response andbrand impression are significant to the automotive industry (Cornet andKrieger, 2005). Further studies covered the influence of the exterior styling(Desmet, 2002), the social roles (Pelly, 1996) and other emotional aspects inthe automotive industry. 22 Negative emotions can have a major impact on driving performance, andcause accidents or road deaths (Dement, 1997; Wells-Parker et al., 2002).These emotional states include aggressiveness and anger (Wells-Parker etal.

, 2002), fatigue and drowsiness (Lyznicki et al., 1998), stress (Matthews etal., 1998), confusion (Ball and Rebok, 1994), nervousness (Li and Ji, 2005)and sadness (Dula and Geller, 2003). Aggressiveness and anger can causeaggressive driving behaviour (Wells-Parker et al., 2002).

Fatigue anddrowsiness can influence concentration, judgement, perception and reactiontime, potentially causing accidents (Dement, 1997). Another commonproblem is driver stress, often leading to a significant decrease in drivingperformance (Hoch et al., 2005; Uchiyama et al., 2002). Driver confusion cancause increased reaction time, or decreased decision-making ability(Jonsson et al., 2005). Confusion is prevalent amongst elderly drivers, butwith the increasing sophistication of digital technologies it is expected tobecome a greater issue in the future.

Nervousness and sadness cannegatively influence the driving performance and lead to human error andaccidents (Li and Ji, 2005). Human error is still the largest cause for accidentsand road deaths (National Highway Traffic Safety Administration, 2008).While the influence of negative emotions on driving has been studied in thepast, in-depth investigations of multiple emotional states during driving arelimited.

This research takes the view that a systematic investigation ofmultiple emotional states is necessary to respond to the aforementionedchallenges in automotive design. Autonomous vehicles offer many potential benefits for the future, includingreduced CO2 emission and fuel consumption (Bullis, 2011), increased safetyand reduced fatalities (Manyika et al., 2013) and decreased congestion(Dumaine, 2012).

Autonomous driving could lead to social benefits;occupants could decide freely how to use their time in the vehicle. Predictions 1.3 The Importance of Emotion for AutonomousVehicles 23 present the idea of the future automobile as a living room, workplace or thenew ‘third place’ (e.g.

Mercedes concept self-driving automobile introducedat CES 2015 Las Vegas). Automotive technology is progressing strongly towards higher automation(Manyika et al., 2013), with self-parking systems, steering assistance andautomatic breaking systems. Toyota, General Motors, Mercedes, BMW, Audiand Volvo are testing autonomous systems (Manyika et al., 2013).

Severalpredictions see autonomous automobiles on the streets by 2025-2030 (Gott,2014; Jacques, 2014; Stanley and Gyimesi, 2015). “That would translate into approximately 10 to 20 percent of the1.2 billion private automobiles projected to be on the road in 2025having the ability to self-drive in at least half of all traffic situations.”(Manyika et al., 2013, p.81) The largest issue facing autonomous vehicles is therefore not the technology,but regulatory frameworks and most importantly public support and humanacceptance (Manyika et al.

, 2013; Thrun 2010). Without human acceptance,there is no foundation for connected, self-driving automobiles. Thrun statesthat: “We need to overcome the old belief that only people can drive cars,and embrace new modes of transportation that utilize the twenty-firstcentury technology.” (Thrun, 2010 p 106) Schoettle and Sivak conducted research into the acceptance of self-drivingvehicles and 43.

5% of the participants stated that they always want to be infull control of their vehicle, only 15.6% had a positive point of view towardsautonomous automobiles and more than 60% of participants expressedconcerns about riding an autonomous automobile (Schoettle and Sivak,2014). With the automobile taking over tasks that the driver once used toperform, issues of acceptance, trust and pride can arise (Koo et al., 2015,p.2). To prevent this from happening Koo et al.

emphasise the “need for 24 designers to observe this phenomenon from the perspective of the humandriver” (Koo et al., 2015, p.2). Recent surveys investigating the public opinionof partially autonomous and self-driving vehicles reinforce the need for furtherresearch and adaptations (Business Wire, 2014; Cisco, 2013; Schoettle andSivak 2014; Silberg et al.

, 2013). The role of emotion research becomeshighly significant when taking into account upcoming changes in theautomotive environment due to automation. Koo et al. state the concern that”cars are starting to make decisions on our behalf” (Koo et al., 2015, p.1).

When looking at the stages of vehicle automation (Figure 3) it becomesapparent that we are currently in the progress of entering a stage of highlyautomated vehicles, facing full automation in 2025. Figure 3 Arch of vehicle automation (Horrell, 2014) For highly automated vehicles where the driver still has an active role andcontrol is shared between the automobile and the driver, the role of human-automobile interaction is highly significant. While the role of the driver in afully manual automobile, as well as in a fully self-driving automobile isobvious, the biggest challenges arise with partially autonomous cars(Norman, 1990). With automobile and driver cooperating, interaction needsto happen on an affective level to create a successful control loop.

To keepthe human informed, the automobile must understand and respond to humanbehaviour and emotions (Shaikh and Krishnan, 2013). Therefore, a high levelof understanding of drivers is required. In the fully automated stage, the role of the driver will change into a passengerrole, with the automobile taking over all tasks which used to be human- 25 controlled. For the passengers to trust their self-driving automobile anaffective passenger-car communication is required. The automobile mustunderstand human needs and respond to behaviour and emotion; emotionalfactors and affective states are therefore crucial for acceptance, safety andcomfort of future automotive design (Eyben et al.

, 2010). Furthermore, newcommunication models between automobiles and pedestrians have to becreated in order to ensure the pedestrian’s safety and comfort. Theautomobile will need to be able to predict the pedestrian’s behaviour (Meeder,Bosina and Weidmann, 2017).

While multiple researchers are investigating the requirements stemming fromcurrent and future stages of automation and the necessity to respond toneeds of drivers, passengers and pedestrians (Eyben et al., 2010; Meeder,Bosina and Weidmann, 2017; Shaikh and Krishnan, 2013) further researchon methods of emotion investigation during driving is required. To meet human requirements for coping with current and future automobiletechnology, it is important to understand the multi-layered emotional role ofthe automobile (Sheller, 2004). To achieve this, studies of human behaviourand emotional states in the driving context are required. We need to be ableto predict the channels of user behaviour and emotion while driving.

AsNorman states “we must design our technologies for the way people actuallybehave, not the way we would like them to behave” (Norman, 2007, p.12).Furthermore, a shift of the main focus of the automobile industry from humanperformance to human behaviour is required for future design to addressissues such as the greater sophistication of technologies and the increasingcomplexity of the automotive habitat. To respond to these challenges a betterunderstanding of human behaviour, needs, desires and emotions isnecessary (Giuliano, Germak and Giacomin, 2017). 1.4 Current Technology for Estimating Human Emotionand Current Uses of the Collected Information 26 While most research approaches focus on negative emotions and theirconsequences (Deffenbacher et al.

, 2002; Parkinson, 2001), the focus isgradually shifting towards the investigation of multiple emotional states in theautomotive environment. One approach to a better understanding of humanemotion which has recently been applied in automotive research is affectivecomputing, the study of systems or devices which can recognise, interpret orprocess human emotion (Picard, 2003). Different physiological measurementtools (e.g.

Galvanic Skin Response, Respiration Rate), behavioural sensors(e.g. Facial-Expression Analysis, Speech Analysis) or self-report tools (e.g.Car Logs, Self-Assessment Manikin) have been applied to driving research(Healey, 2000; Hoch et al., 2005; Jones and Jonsson, 2005).

Moreover,numerous modern human–centred design approaches combining variousmethods have been applied to automotive research and design, to investigatethe drivers’ and passengers’ behaviour, emotion and needs and improve thedriving experience (Gkatzidou, Giacomin and Skrypchuk, 2016; Giuliano,Germak and Giacomin, 2017). Current research and appropriate methods for the investigation of emotionsduring driving are not only limited but also not comparable due to majordifferences in applied methodologies, investigations of emotion andmeasurement tools. Furthermore, research methodologies and results areoften highly influenced by their limitations (Chapter 3.

2 EmotionMeasurement in Automobile Research). Therefore, further researchsystematically investigating emotional responses within the automotivehabitat is required. This research uses identification of the limitations andshortcomings of previous efforts to direct the line of investigation. Throughthe development of specific queries that must be answered, an improvedframework for the study of human emotion in the automotive environmentmay be developed. 27 1.5 Research Questions This research takes the view that there is a need for the automotive industryto shift the focus towards the driver’s behaviour, emotions and needs. A betterunderstanding of the driver’s emotional response to changes in the drivingenvironment is required, especially considering current and futuretechnological developments.

The aim of this research is to investigate themeasurability, natures and causes of emotional responses during simulatedand on-road driving. Furthermore, the ability to causally assign individualemotional responses to specific sources of the emotion will be explored.Additionally, this thesis will investigate the assigned causes for emotionalevents in the driving environment and the influence of different road typesand situations on those. Finally, a dataset of emotional responses and theircauses in different driving settings will be created. A comparison featuring astatistical analysis of the collected results will be conducted to investigate howdifferent driving settings influence drivers’ emotions.

Therefore, the mainresearch questions of this thesis and are: How can human emotional responses be measured in an automotiveenvironment? Can emotional responses be triggered and measured in a simulateddriving environment? What are the major challenges? What are the typical natures, frequencies and causes of emotional eventsin a natural real driving environment? What are the typical natures, frequencies and causes of emotional eventsin a partially controlled real driving environment? How can the typical natures, frequencies and causes of emotional eventsbetween two on-road studies in different settings be compared? 


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