Modeling driver-vehicle interaction in automated driving Modellierung der Fahrer-Fahrzeug-Interaktion beim automatisierten Fahren
DOI: 10.1007/s10010-021-00576-6
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Summary
This paper addresses the critical challenge of modeling driver-vehicle interaction (DVI) in automated driving, where the collaboration between human drivers and automated systems significantly impacts road safety, comfort, and acceptance. The authors argue that successful interaction requires a precise interpretation of influencing factors, including driver state, system state, and environmental conditions. To address this, the study proposes a comprehensive framework that integrates a feedback control loop for regulating driver state with a detailed driver model representing the decision-making process during task transitions. The methodology involves two main components: a theoretical model and an experimental validation. The proposed DVI structure utilizes a feedback controller that receives inputs regarding the driver’s current state, the target state, automation level, and situation criticality. This controller generates appropriate stimuli (visual, auditory, or haptic) to regulate the driver’s state toward a target that ensures safe performance. The accompanying driver model is based on cognitive architectures, specifically adapting the Adaptive Control of Thought-Rational (ACT-R) model for cognitive processes and the PAD (Pleasure, Arousal, Dominance) model for emotional states. The model posits that decision-making involves parallel cognitive and emotional processes, followed by motor reactions. To validate this model, the researchers conducted a driving simulator experiment with 38 participants. The experiment investigated whether both emotional and cognitive states become active during the decision-making process and determined the temporal sequence of these processes during a mode change from automated to manual driving. The results from the simulator experiment were analyzed to map the participants' responses to the proposed driver model. The findings confirmed that the activity levels of both emotional and cognitive states increase during the takeover situation, supporting the hypothesis that these processes are active in parallel. Furthermore, the data indicated that the increase in activation levels occurs before the onset of the physical response, consistent with the model’s prediction that decision-making precedes motor action. The results were consistent with the suggested driver model regarding the driver’s cognitive and emotional states during the transition of driving tasks. The significance of this work lies in its contribution to a general, personalized framework for DVI that accounts for individual driver differences and real-time situational criticality. By demonstrating that emotional and cognitive states are integral to the decision-making process during automation handovers, the study provides evidence for designing interaction systems that monitor and regulate these states. This approach aims to improve driver performance and safety by ensuring the driver is adequately prepared and attentive before assuming control, thereby addressing issues such as loss of situational awareness and overreliance on automation.
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-06-07 |
| archive | success | canonical_url | — | — | 1 | 2026-06-09 |
| extract | success | cached | — | — | 2 | 2026-06-09 |
| clean | success | clean | — | — | 1 | 2026-06-07 |
| chunk | success | chunk | — | — | 1 | 2026-06-07 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-07 |
| promote | success | — | — | — | 1 | 2026-06-07 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-09 |
| tag | success | vector_similarity | — | — | 8 | 2026-06-11 |
| verify | success | — | — | — | 1 | 2026-06-09 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-09; verification: verified.
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- Theoretical Contribution: computational model, conceptual framework, theory or model