Nadine Rauh

Understanding the Impact of Electric Vehicle Driving Experience on Range Anxiety

Objective: The objective of the present research was to increase understanding of the phenomenon of range anxiety and to determine the degree to which practical experience with battery electric vehicles (BEVs) reduces different levels of range anxiety. Background: Limited range is a challenge for BEV users. A frequently discussed phenomenon in this context is range anxiety. There is some evidence suggesting that range anxiety might be a problem only for inexperienced BEV drivers and, therefore, might decrease with practical experience. Method: We compared 12 motorists with high BEV driving experience (M = 60,500 km) with 12 motorists who had never driven a BEV before. The test drive was designed to lead to a critical range situation (remaining range < trip length). We examined range appraisal and range stress (i.e., range anxiety) on different levels (cognitive, emotional, and behavioral). Results: Experienced BEV drivers exhibited less negative range appraisal and range anxiety than inexperienced BEV drivers, revealing significant, strong effects for all but one variable. Conclusion: Hence, BEV driving experience (defined as absolute kilometers driven with a BEV) seems to be one important variable that predicts less range anxiety. Application: In order to reduce range anxiety in BEV drivers even when there is a critical range situation, it is important to increase efficiency and effectiveness of the learning process.

Which Factors Can Protect Against Range Stress in Everyday Usage of Battery Electric Vehicles? Toward Enhancing Sustainability of Electric Mobility Systems

Objective: The objective of the present research was to advance understanding of factors that can protect against range anxiety, specifically range stress in everyday usage of battery electric vehicles (BEVs). Background: Range anxiety is a major barrier to the broad adoption of sustainable electric mobility systems. To develop strategies aimed at overcoming range anxiety, a clear understanding of this phenomenon and influencing factors is needed. Method: We examined range anxiety in the form of everyday range stress (ERS) in a field study setting. Seventy-two customers leased a BEV for 3 months. The field study was specifically designed to enable examination of factors that can contribute to lower ERS. In particular, study design and sample recruitment were targeted at generating vehicle usage profiles that would lead to relatively frequent experience of situations requiring active management of range resources and thereby potentially leading to experienced range stress. Results: Less frequent encounter with critical range situations, higher practical experience, subjective range competence, tolerance of low range, and experienced trustworthiness of the range estimation system were related to lower ERS. Moreover, range stress was found to be related to range satisfaction and BEV acceptance. Conclusion: The results underline the importance of the human factors perspective to overcome range anxiety and enhance sustainability of electric mobility systems. Application: Trustworthiness should be employed as a key benchmark variable in the design of range estimation systems, and assistance systems should target increasing drivers’ adaptive capacity (i.e., resilience) to cope with critical range situations.

Individual differences in BEV drivers' range stress during first encounter of a critical range situation

It is commonly held that range anxiety, in the form of experienced range stress, constitutes a usage barrier, particularly during the early period of battery electric vehicle (BEV) usage. To better understand factors that play a role in range stress during this critical period of adaptation to limited-range mobility, we examined individual differences in experienced range stress in the context of a critical range situation. In a field experiment, 74 participants drove a BEV on a 94-km round trip, which was tailored to lead to a critical range situation (i.e., small available range safety buffer). Higher route familiarity, trust in the range estimation system, system knowledge, subjective range competence, and internal control beliefs in dealing with technology were clearly related to lower experienced range stress; emotional stability (i.e., low neuroticism) was partly related to lower range stress. These results can inform strategies aimed at reducing range stress during early BEV usage, as well as contribute to a better understanding of factors that drive user experience in low-resource systems, which is a key topic in the field of green ergonomics.

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.

Influence of User and Task Related Variables on Latency Perception

Nowadays, technical system latencies are nearly unavoidable in Human-Computer-Interaction. However, latencies, if detected by the user, were shown to have a negative influence on experience and satisfaction. Therefore, it is important to examine users’ latency perception thresholds with respect to different influencing factors empirically.

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.

Are 100 ms Fast Enough? Characterizing Latency Perception Thresholds in Mouse-Based Interaction

The claim that 100 ms system latency is fast enough for an optimal interaction with highly interactive computer systems has been challenged by several studies demonstrating that users are able to perceive latencies well below the 100 ms mark. Although a high amount of daily computer interactions is still characterized by mouse-based interaction, to date only few studies about latency perception thresholds have employed a corresponding interaction paradigm. Therefore, we determined latency perception thresholds in a mouse-based computer interaction task. We also tested whether user characteristics, such as experience with latency in computer interaction and interaction styles, might be related to inter-individual differences in latency perception thresholds, as results of previous studies indicate that there is considerable inter-individual variance in latency perception thresholds. Our results show that latency perception thresholds for a simple mouse-based computer interaction lie in the range of 60 ms and that inter-individual differences in latency perception can be related to user characteristics.