Thomas Franke

The Role of Interaction Patterns with Hybrid Electric Vehicle Eco-Features for Drivers’ Eco-Driving Performance

Objective: The objective of the present research was to understand drivers’ interaction patterns with hybrid electric vehicles’ (HEV) eco-features (electric propulsion, regenerative braking, neutral mode) and their relationship to fuel efficiency and driver characteristics (technical system knowledge, eco-driving motivation). Background: Eco-driving (driving behaviors performed to achieve higher fuel efficiency) has the potential to reduce CO2 emissions caused by road vehicles. Eco-driving in HEVs is particularly challenging due to the systems’ dynamic energy flows. As a result, drivers are likely to show diverse eco-driving behaviors, depending on factors like knowledge and motivation. The eco-features represent an interface for the control of the systems’ energy flows. Method: A sample of 121 HEV drivers who had constantly logged their fuel consumption prior to the study participated in an online questionnaire. Results: Drivers’ interaction patterns with the eco-features were related to fuel efficiency. A common factor was identified in an exploratory factor analysis, characterizing the intensity of actively dealing with electric energy, which was also related to fuel efficiency. Driver characteristics were not related to this factor, yet they were significant predictors of fuel efficiency. Conclusion: From the perspective of user–energy interaction, the relationship of the aggregated factor to fuel efficiency emphasizes the central role of drivers’ perception of and interaction with energy conversions in determining HEV eco-driving success. Application: To arrive at an in-depth understanding of drivers’ eco-driving behaviors that can guide interface design, authors of future research should be concerned with the psychological processes that underlie drivers’ interaction patterns with eco-features.

A Personal Resource for Technology Interaction: Development and Validation of the Affinity for Technology Interaction (ATI) Scale

ABSTRACT Successful coping with technology is relevant for mastering daily life. Based on related conceptions, we propose affinity for technology interaction (ATI), defined as the tendency to actively engage in intensive technology interaction, as a key personal resource for coping with technology. We present the 9-item ATI scale, an economical unidimensional scale that assesses ATI as an interaction style rooted in the construct need for cognition (NFC). Results of multiple studies (n > 1500) showed that the scale achieves good to excellent reliability, exhibits expected moderate to high correlations with geekism, technology enthusiasm, NFC, self-reported success in technical problem-solving and technical system learning success, and also with usage of technical systems. Further, correlations of ATI with the Big Five personality dimensions were weak at most. Based on the results, the ATI scale appears to be a promising tool for research applications such as the characterization of user diversity in system usability tests and the construction of general models of user-technology interaction.

Electric Vehicles with Range Extenders: Evaluating the Contribution to the Sustainable Development of Metropolitan Regions

AbstractElectric vehicles play a key role in strategic development plans of urban regions in Europe because they are seen as a promising technology to promote environmental quality, livability, and...

Assessing Personality Differences in Human-Technology Interaction: An Overview of Key Self-report Scales to Predict Successful Interaction

For a comprehensive understanding of user diversity, a reliable and valid assessment of stable user characteristics is essential. In the field of human-technology interaction, a plethora of personality-related constructs linked to the experience of and interaction with technical systems has been discussed. A key question for researchers in the field is thus: Which are the key personality concepts and scales for characterizing inter-individual differences in user technology interaction? Based on a literature review and citation analysis, a structured overview of frequently used technology-related personality constructs and corresponding self-report scales is provided. Changes in the popularity and content of scales and concepts that occured over time as well as overlap between constructs and scales are discussed to facilitate scale selection.

System Latency Guidelines Then and Now – Is Zero Latency Really Considered Necessary?

Latency or system response time (i.e., the delay between user input and system response) is a fundamental factor affecting human-computer interaction (HCI). If latency exceeds a critical threshold, user performance and experience get impaired. Therefore, several design guidelines giving recommendations on maximum latencies for an optimal user experience have been developed within the last five centuries. Concentrating on the lower boundary latencies, these guidelines are critically reviewed and contrasted with recent empirical findings. Results of the review reveal that latencies below 100 ms were seldom considered in guidelines so far even though smaller latencies have been shown to be perceivable to the user and impact user performance negatively. Thus, empirical evidence suggests a need for updated guidelines for designing latency in HCI.

The Effect of Displaying Kinetic Energy on Hybrid Electric Vehicle Drivers’ Evaluation of Regenerative Braking

More energy efficient and sustainable systems become increasingly widespread in automotive applications (e.g., hybrid electric vehicles; HEVs). Yet, their real-world energy efficiency strongly depends on driver behaviour and, often, showing optimal eco-driving behaviour is challenging especially if energy dynamics are not sufficiently represented in the driver interface. For example, previous research indicated that HEV drivers try to actively utilize and regain electric energy, without sufficiently considering conversion losses that are part of this process (i.e., energy conversion fallacy). One possible explanation is that HEV drivers do not actively consider kinetic energy while driving, mainly because it is not represented in energy displays. The object of the present research was to examine whether drivers can be supported in a less biased perception of the efficiency of regenerative braking when an indicator of kinetic energy is also represented in the interface. To this end, we designed an online video experiment. Two displays were presented to drivers, a conventional energy flow display in which only electric energy resources were represented and an adapted display in which also kinetic energy resources were represented. Drivers rated the perceived energy efficiency of two types of deceleration scenarios, regenerative braking and neutral mode. The results provide first evidence that adding a representation of kinetic energy resources to displays of energy flows in HEVs can reduce drivers’ energy conversion fallacy.

What Drives Ecodriving? Hybrid Electric Vehicle Drivers’ Goals and Motivations to Perform Energy Efficient Driving Behaviors

Hybrid electric vehicles (HEVs) can significantly contribute to sustainable road transport, yet driver behavior has a marked effect on actual energy efficiency (i.e., the ultimate sustainability effect). The objective of the present research was to examine ecodriving motivation of HEV drivers. To this end, we recruited 39 HEV drivers with above-average fuel efficiencies (suggesting at least some degree of ecodriving motivation) and collected interview data, questionnaire responses, and fuel efficiency data. Specifically, we assessed factors that motivated drivers to drive energy efficiently as well as factors that led to reduced ecodriving behavior. Ecodriving motivation of HEV drivers was found to be particularly driven by the goals of environmental protection, cost reduction, and gamification aspects. Furthermore, relationships between drivers’ most important ecodriving motivation and the level of ecodriving motivation, the achieved fuel efficiency, the level of total HEV driving experience, as well as typical HEV driving distances were examined.

Eco-Driving from the Perspective of Behavioral Economics: Implications for Supporting User-Energy Interaction

Eco-driving can essentially be regarded as driver behavior targeted towards increased energy efficiency. As such, eco-drivers have an impact on fuel efficiency when selecting a vehicle (strategic eco-driving), selecting routes (tactical eco-driving) as well as selecting eco-driving strategies (operational eco-driving). On the operational level, a key task for electric vehicle drivers is to decide how to control and interact with the system-inherent energy flows (i.e., user-energy interaction). With the control of the energy flows, drivers convert energies into each other with the goal of achieving optimal energy efficiency. Consequently, user-energy interaction can be regarded as a regulation of energy resources that is composed of a series of economic decisions. Therefore, we examine economic decision-making as a framework for understanding drivers’ eco-driving decisions on the strategic, tactical and operational level of eco-driving. So far economic decision-making has been most extensively studied with the resource money creating a whole research discipline, namely behavioral economics. A plethora of research has indicated that humans tend to use heuristics and succumb to fallacies when making economic decisions. Therefore, we describe heuristics and biases that have been identified for driver behavior and that are relevant to eco-driving. Based on these, we discuss possible implications of the behavioral economics perspective for user-energy interaction. Opportunities to support drivers’ user-energy interaction on the levels of eco-driving and directions for future research are highlighted.

Human Factors and Ergonomics in the Individual Adoption and Use of Electric Vehicles

Electric vehicles (EVs) can contribute to sustainable individual road transport. That is, they constitute one key element in the broader context of sustainable urban design, which also incorporates important further measures such as promoting public transport, cycling, and walking. However, for EVs to achieve an optimal sustainability effect, several human factors issues need to be addressed. The present chapter gives an overview of ergonomics research in this field with a focus on battery electric vehicles (BEVs). We focus on four core areas: (1) the acceptance of BEVs (e.g. perceived barriers, the effect of practical experience, range acceptance), (2) user interaction with BEV range (e.g. range comfort zone, range stress, or range anxiety), (3) users’ charging behaviour (e.g. interaction styles, green charging), and (4) ecodriving in EV usage (e.g. representation of energy flows, ecodriving control strategies). This overview demonstrates the importance of a comprehensive understanding and support of user-resource interaction in order to realise the sustainability potential of EVs.

User Diversity in the Motivation for Wearable Activity Tracking: A Predictor for Usage Intensity?

Wearable fitness devices (i.e., activity trackers) are increasingly popular for monitoring everyday activity. Research suggests that long-term adherence to activity trackers is relevant for their positive effects on health. Thus, it is essential to understand the factors that foster usage intensity and long-term adherence. Based on first research regarding users’ motives for using activity trackers and self-determination theory, we examined usage motives as predictors for the current and estimated future usage intensity. In addition, we investigated the relation of usage motives and user diversity facets (affinity for technology interaction, geekism, and need for cognition). Results of an online study with N = 58 regular users of activity trackers indicated a substantial variation of users’ intrinsic/extrinsic motivation for using an activity tracker. Further, positive relationships between intrinsic motivation, autonomous regulation and usage intensity were found. Regarding user diversity, affinity for technology interaction and geekism predicted the intrinsic motivation whereas need for cognition did not. Our results imply that, in order to obtain possible beneficial health effects of a more intensive activity tracker usage, users’ intrinsic motivation and autonomy have to be supported.