Gamification-supported Exploration and Practicing for Automotive User Interfaces and Vehicle Functions

Diewald, Stefan; Möller, Andreas; Stockinger, Tobias; Roalter, Luis; Koelle, Marion; Lindemann, Patrick; Kranz, Matthias

doi:10.1007/978-3-319-10208-5_32

Cited by 8 publications

(3 citation statements)

References 23 publications

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“…Small-scale studies that employ games, empower an understanding of complex social-technological systems performances, managing personal mobility, and individual behavior change in the automotive domain. Due to their capability for stirring sustainable motivation and strong commitment [108,109], games also promote sustainable urban mobility [110,111]. Moreover, Delphi (11/2002) is used as a constructor of future experts' scenarios, basing its predictions on differences and similarities in experts' knowledge collected via surveys [112][113][114][115][116].…”

Section: Landscape Overview Of Indiviual Groups Of Methods and Their mentioning

confidence: 99%

The Landscape of Envisioning and Speculative Design Methods for Sustainable Mobility Futures

2020

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Urban mobility is facing an increased long-term uncertainty and complexity generated by accelerated technological development. These challenges require radical advancement in planning processes and methods, which could enable breaking out of path dependencies and unlocking alternative, sustainable futures. In order to provide a landscape overview of foresight-focused methods used in the domain of urban mobility, we conduct a systematic literature review. An analytical framework for review is based on planning knowledge taxonomy, including dialectic between knowing how/what and knowing to what end and doing. Such framework formulation is aiming to assess methodological capacity for widening system boundary and holism (object-focus) as well as integration and imagination (process-focus). Results show that the overall trend of methodological development is emphasizing development in object or process-focus domain, but rarely both. In addition to this assessment, we conclude that methodological development should further reflect the moral and democratic dimension concerning public deliberation. Such development should aim to create spaces for shared discussion, reflection, and formation of alternative futures, while allowing spaces for agonistic contestation and conflicting opinions through radical, experimental, and experiential approaches.

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Section: Landscape Overview Of Indiviual Groups Of Methods and Their mentioning

confidence: 99%

The Landscape of Envisioning and Speculative Design Methods for Sustainable Mobility Futures

2020

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“…Previous studies showed that serious games and gamified learning methods have been particularly and successfully applied in different business fields [ 11 , 16 ] and in sectors where technologies and mobile applications are used, such as automotive manufacturing [ 18 ], occupational health settings including medicine, surgery and rehabilitation [ 19 , 20 ], sports (e.g., baseball, [ 21 ]) and in hazardous working sectors such as firefighting [ 22 ], construction [ 1 ] and mining [ 23 ].…”

Section: Introductionmentioning

confidence: 99%

Innovating Occupational Safety Training: A Scoping Review on Digital Games and Possible Applications in Agriculture

Vigoroso

Caffaro

Cremasco

et al. 2021

IJERPH

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Digital games have been successfully applied in different working sectors as an occupational safety training method, but with a very limited application in agriculture. In agriculture and other productive sectors, unintentional injuries tend to occur with similar dynamics. A literature review was carried out to understand how occupational risks are addressed during game-based safety training in different productive sectors and how this can be transferred to agriculture. Literature about “serious game” and “gamification” as safety training methods was searched in WEB OF SCIENCE, SCOPUS, PUBMED and PsycINFO databases. In the forty-two publications retained, the computer was identified as the most adopted game support, whereas “points”, “levels”, “challenges” and “discovery” were the preferred game mechanics. Moreover, an association can be detected between the game mechanics and the elements developed in the game. Finally, during the game assessment, much positive feedback was collected and the games proved to be able to increase the operators’ skills and safety knowledge. In light of the results, insights are provided to develop an effective, satisfying and engaging safety game training for workers employed in agriculture. Games can be best used to learn and they are certain to improve over the next few years.

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“…Different car manufacturers developed several Gamification mechanisms and embedded them in their models. Diewald et al [21] provided a comprehensive review of such applications. From Volkswagen's BlueMotion Roulette to Ford's SmartGauge with EcoGuide, passing through the Kia's ECOdynamics and Fiat's eco:Drive.…”

Section: Background and Related Workmentioning

confidence: 99%

On combining Big Data and machine learning to support eco-driving behaviours

et al. 2019

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The automotive industry is currently facing a moment of radical change. According to the 2018 edition of the future automotive industry structure (FAST) study, 1 conducted by Oliver Wyman and the German Automotive Association, there are seven main factors that will drive this sector over the next decade (until 2030), thanks to the exploitation of digitization, artificial intelligence (AI), and machine learning (ML). These identified factors are: (i) connected vehicles, (ii) autonomous vehicles, (iii) electric mobility, (iv) digital industry, (v) new distribution channel pay-per-use, (vi) changes in customer structure, and (vii) new concepts for Human-Machine Interface. In this emerging context, the Internet of Things paradigm can be exploited, taking advantage of interconnected sensors, which are more and more accurate, smaller, and powerful [1]. Accordingly, vehicles are increasingly being equipped with a variety of sensors, provided with integrated connectivity, that can monitor different components and situations, such as the engine, the driving style or the environmental conditions. Indeed, these sensors lead to the generation of large volumes of data about the vehicle,

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Gamification-supported Exploration and Practicing for Automotive User Interfaces and Vehicle Functions

Cited by 8 publications

References 23 publications

The Landscape of Envisioning and Speculative Design Methods for Sustainable Mobility Futures

The Landscape of Envisioning and Speculative Design Methods for Sustainable Mobility Futures

Innovating Occupational Safety Training: A Scoping Review on Digital Games and Possible Applications in Agriculture

On combining Big Data and machine learning to support eco-driving behaviours

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