A driver-distraction-based lane-keeping assistance system
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Summary
This paper addresses the safety challenge of single-vehicle roadway departure (SVRD) accidents, which are frequently caused by driver distraction or drowsiness. The authors propose a lane-keeping assistance system that intervenes only when a driver is positively detected as distracted, aiming to reduce the false positive interventions and driver annoyance associated with conventional lane-keeping systems. While standard systems often trigger warnings during intentional maneuvers like lane changes, this distraction-based approach ensures that haptic interventions via steering torque are applied solely when the vehicle drifts from its lane and the driver’s attention is diverted. The system architecture integrates a video-based driver monitoring system with a lane-keeping module. To estimate visual distraction, the system tracks the driver’s head position and pose using a camera, rather than relying on difficult-to-detect eye gaze vectors. The detection algorithm calculates a distraction level by mapping the driver’s visual focus onto weighted regions of the vehicle interior and road scene. A distraction decision-maker uses adaptive thresholds to determine the driver’s state, accounting for the non-linear nature of distraction where levels rise over time but drop instantaneously upon refocusing. The lane-keeping module then applies an additional torque to the steering shaft to guide the vehicle back into the lane, functioning as an intervention system that augments rather than replaces driver control. Test track investigations indicate significant potential for this system from a driver perspective, provided that the vision sensors for lane and face tracking achieve sufficient reliability. The study highlights that linking intervention to distraction detection effectively mitigates false positives, such as those occurring during intentional lane changes without indicator usage. By requiring both lane departure and a distracted state for intervention, the system maintains a constant hazard profile and improves driver acceptance. The authors conclude that while the technology offers substantial safety benefits by targeting a major cause of SVRD accidents, its practical implementation depends heavily on the robustness of the underlying sensor technologies for accurate real-time tracking.
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | OpenAlex-citations | — | — | 1 | 2026-06-19 |
| archive | success | unpaywall | — | — | 2 | 2026-06-25 |
| extract | success | cached | — | — | 2 | 2026-06-26 |
| clean | success | clean | — | — | 1 | 2026-06-19 |
| chunk | success | chunk | — | — | 1 | 2026-06-19 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-19 |
| promote | success | — | — | — | 1 | 2026-06-19 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-26 |
| tag | success | vector_similarity | — | — | 6 | 2026-06-19 |
| verify | success | — | — | — | 1 | 2026-06-26 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.
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