Influence of Adaptive Human-Machine Interface on Electric-Vehicle Range-Anxiety Mitigation
DOI: 10.3390/mti4010004
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Summary
This paper addresses the challenge of "range anxiety" in electric vehicles (EVs), a psychological barrier to EV adoption where drivers perceive available range as insufficient despite it being adequate. While hardware improvements (battery capacity, charging rates) have diminishing returns due to trade-offs with vehicle weight and cost, the authors argue that human-machine interface (HMI) design offers a viable alternative for mitigation. Within the H2020 ADAS&ME project, the study developed an intelligent HMI designed to provide adaptive coping strategies and automated safety features to reduce driver stress and improve acceptance of EV technology. The study employed a Wizard of Oz (WoZ) experimental design involving 22 inexperienced EV drivers (10 female, 12 male, aged 18–45) who were recruited based on specific criteria, including high driving frequency and familiarity with Advanced Driver Assistance Systems. Participants underwent a one-hour open-road driving task tailored to induce range anxiety. The protocol utilized a fake battery depletion rate of 1% per minute, starting at 60% and ending with an emergency stop at 1%. The HMI provided dynamic feedback, such as tips for regenerative braking at traffic lights, hill climbing advice, and charging station recommendations. A control group of five drivers received only basic navigation and range information without the adaptive coping strategies. Data collection included biophysiological signals, video/audio recording, and Likert scale questionnaires administered before and after the drive to assess emotional states. The primary findings indicate that the intelligent HMI successfully reduced range anxiety by transmitting specific, context-aware energy-saving strategies, such as advising drivers to slow down gradually at red lights to recover energy. The system’s ability to propose accurate coping techniques helped drivers understand how their behavior affected power consumption, thereby increasing their sense of control. Furthermore, the study found that the combination of the HMI and automated driving to a safe spot significantly reduced driver stress during the simulated emergency stop scenario. The adaptive interface allowed the system to proactively manage the driver’s state, transitioning from informational support to directive safety actions as the battery level became critical. The significance of this work lies in demonstrating that human factors and interface design are critical components of EV acceptance, independent of hardware specifications. By integrating intelligent power management, routing analysis, and automated driving assistance, the HMI effectively mitigated the psychological impact of low battery levels. The results suggest that future EVs should incorporate adaptive HMIs that not only display range data but also actively guide driver behavior and automate safety procedures, thereby addressing the root causes of range anxiety and facilitating the broader adoption of electric mobility.
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The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via mdpi_direct on 2026-05-07.
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | — | — | — | 1 | 2026-05-07 |
| archive | success | canonical_url | — | — | 37 | 2026-08-22 |
| extract | success | cached | — | — | 3 | 2026-08-23 |
| clean | success | clean | — | — | 1 | 2026-06-04 |
| chunk | success | chunk | — | — | 1 | 2026-06-04 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-04 |
| enrich | success | — | — | — | 1 | 2026-05-07 |
| promote | success | — | — | — | 1 | 2026-05-07 |
| summarize | success | llm | qwen3.8-27b-gittensor | summ-v5 | 2 | 2026-08-23 |
| tag | success | vector_similarity | — | — | 15 | 2026-06-11 |
Summary generated by qwen3.8-27b-gittensor on 2026-08-23; verification: pending re-verification.
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- Applied Guidance: design guidelines