An interactive haptic force feedback interface for semi-automatic control in highly-automated vehicles

KAMEZAKI, Mitsuhiro; MANAWADU, Udara E.; KAWANO, Takahiro; ISHIKAWA, Masaaki; SUGANO, Shigeki · 2018 · DOAJ

DOI: 10.1299/transjsme.18-00008

archive: archived pipeline: cataloged verified

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Summary

This study addresses the limitations of current autonomous driving systems (ADS), which often restrict driver interaction to simple destination inputs, thereby reducing control flexibility and complicating takeovers during system failures. The authors propose a semi-automatic control method that allows drivers to input discrete vehicle maneuvers—such as lane changes, overtaking, and speed adjustments—rather than continuous steering or pedal inputs. To implement this, they developed a Haptic Force Feedback Interface (HIF), a joystick-type device providing bidirectional interaction through kinesthetic (force) and tactile (vibration) feedback. This interface enables the ADS to accept or reject driver inputs based on safety and traffic rules, while also conveying environmental states to the driver. The HIF was designed with a 3D-printed ergonomic grip, DC motors for force feedback (up to 50N repulsive force), and vibration motors. It supports lateral controls (turning, lane changing, overtaking), longitudinal controls (acceleration/deceleration), and parking commands. Visual feedback was supplemented via augmented reality (AR) indicators in a driving simulator. The study compared the HIF against a previously developed hand-gesture interface (GIF), manual driving (steering wheel/pedals), and fully autonomous driving (touchscreen destination input). Experiments involved 20 participants navigating a 2km course with varied traffic scenarios. Metrics included input error rates, input time, and subjective workload using the NASA-TLX scale. Results demonstrated that the HIF significantly outperformed the GIF in reliability and speed. The HIF had an input error rate of 0.84%, compared to 24.8% for the GIF, and an average input time of 1.00 seconds versus 1.39 seconds for the GIF. Participants preferred the HIF due to its immediate physical feedback, which clarified input acceptance or rejection, and its ergonomic design, which reduced arm fatigue associated with the gesture-based GIF. Semi-automatic driving with the HIF resulted in lower subjective workload than manual driving but higher than fully autonomous driving. Drivers particularly favored the HIF in dynamic urban environments requiring rapid maneuvers, such as overtaking, where the interface’s responsiveness and clear input zones were advantageous. The study concludes that semi-automatic control via haptic force feedback offers a balanced approach, combining the flexibility of manual driving with the reduced cognitive load of automation. The HIF’s ability to provide reliable, bidirectional interaction enhances driver trust and situational awareness, making it a superior interface for semi-autonomous vehicles compared to gesture-based or purely visual alternatives. This approach supports a more natural driver-vehicle interaction, potentially improving safety and user experience in highly automated driving contexts.

Key finding

The haptic force feedback interface significantly reduced input time and error rates compared to a hand-gesture interface and was preferred by drivers for its immediate, bidirectional feedback capabilities.

Methodology

simulator

Sample size: 20

Provenance

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 topic_sweep_doaj on 2026-06-01.

StageOutcomeToolModelPromptAttemptsCompleted
discover success 1 2026-06-01
archive success canonical_url 1 2026-06-06
extract success cached 3 2026-06-10
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 2026-06-01
promote success 1 2026-06-04
summarize success llm qwen3.6-27b-prismaquant summ-v5 2 2026-06-10
tag success vector_similarity 15 2026-06-11
verify success 2 2026-06-10

Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

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