Wang, Zheng ; Suga, Satoshi ; Nacpil, Edric John Cruz ; Yang, Bo ; Nakano, Kimihiko (2022)
Effect of Fixed and sEMG-Based Adaptive Shared Steering Control on Distracted Driver Behavior.
In: Sensors, 2022, 21 (22)
doi: 10.26083/tuprints-00020076
Artikel, Zweitveröffentlichung, Verlagsversion
Kurzbeschreibung (Abstract)
Driver distraction is a well-known cause for traffic collisions worldwide. Studies have indicated that shared steering control, which actively provides haptic guidance torque on the steering wheel, effectively improves the performance of distracted drivers. Recently, adaptive shared steering control based on the forearm muscle activity of the driver has been developed, although its effect on distracted driver behavior remains unclear. To this end, a high-fidelity driving simulator experiment was conducted involving 18 participants performing double lane change tasks. The experimental conditions comprised two driver states: attentive and distracted. Under each condition, evaluations were performed on three types of haptic guidance: none (manual), fixed authority, and adaptive authority based on feedback from the forearm surface electromyography of the driver. Evaluation results indicated that, for both attentive and distracted drivers, haptic guidance with adaptive authority yielded lower driver workload and reduced lane departure risk than manual driving and fixed authority. Moreover, there was a tendency for distracted drivers to reduce grip strength on the steering wheel to follow the haptic guidance with fixed authority, resulting in a relatively shorter double lane change duration.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2022 |
| Autor(en): | Wang, Zheng ; Suga, Satoshi ; Nacpil, Edric John Cruz ; Yang, Bo ; Nakano, Kimihiko |
| Art des Eintrags: | Zweitveröffentlichung |
| Titel: | Effect of Fixed and sEMG-Based Adaptive Shared Steering Control on Distracted Driver Behavior |
| Sprache: | Englisch |
| Publikationsjahr: | 2022 |
| Publikationsdatum der Erstveröffentlichung: | 2022 |
| Verlag: | MDPI |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Sensors |
| Jahrgang/Volume einer Zeitschrift: | 21 |
| (Heft-)Nummer: | 22 |
| Kollation: | 14 Seiten |
| DOI: | 10.26083/tuprints-00020076 |
| URL / URN: | https://tuprints.ulb.tu-darmstadt.de/20076 |
| Zugehörige Links: | |
| Herkunft: | Zweitveröffentlichung DeepGreen |
| Kurzbeschreibung (Abstract): | Driver distraction is a well-known cause for traffic collisions worldwide. Studies have indicated that shared steering control, which actively provides haptic guidance torque on the steering wheel, effectively improves the performance of distracted drivers. Recently, adaptive shared steering control based on the forearm muscle activity of the driver has been developed, although its effect on distracted driver behavior remains unclear. To this end, a high-fidelity driving simulator experiment was conducted involving 18 participants performing double lane change tasks. The experimental conditions comprised two driver states: attentive and distracted. Under each condition, evaluations were performed on three types of haptic guidance: none (manual), fixed authority, and adaptive authority based on feedback from the forearm surface electromyography of the driver. Evaluation results indicated that, for both attentive and distracted drivers, haptic guidance with adaptive authority yielded lower driver workload and reduced lane departure risk than manual driving and fixed authority. Moreover, there was a tendency for distracted drivers to reduce grip strength on the steering wheel to follow the haptic guidance with fixed authority, resulting in a relatively shorter double lane change duration. |
| Freie Schlagworte: | driver–automation shared control, haptic guidance steering, adaptive automation design, surface electromyography, driver distraction |
| Status: | Verlagsversion |
| URN: | urn:nbn:de:tuda-tuprints-200766 |
| Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 600 Technik, Medizin, angewandte Wissenschaften > 600 Technik 600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften und Maschinenbau |
| Fachbereich(e)/-gebiet(e): | 18 Fachbereich Elektrotechnik und Informationstechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Automatisierungstechnik und Mechatronik |
| Hinterlegungsdatum: | 29 Apr 2022 09:04 |
| Letzte Änderung: | 02 Mai 2022 10:03 |
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| Zugehörige Links: | |
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| Suche nach Titel in: | TUfind oder in Google |
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