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Lateral Evasive Maneuver with Shared Control Algorithm: A Simulator Study.
Sarabia, Joseba; Marcano, Mauricio; Díaz, Sergio; Zubizarreta, Asier; Pérez, Joshué.
Afiliación
  • Sarabia J; TECNALIA, Basque Research and Technology Alliance (BRTA), Astondoa Bidea, Edificio 700, 48160 Derio, Spain.
  • Marcano M; Bilbao School of Engineering, University of the Basque Country UPV/EHU, 48013 Bilbao, Spain.
  • Díaz S; TECNALIA, Basque Research and Technology Alliance (BRTA), Astondoa Bidea, Edificio 700, 48160 Derio, Spain.
  • Zubizarreta A; TECNALIA, Basque Research and Technology Alliance (BRTA), Astondoa Bidea, Edificio 700, 48160 Derio, Spain.
  • Pérez J; Bilbao School of Engineering, University of the Basque Country UPV/EHU, 48013 Bilbao, Spain.
Sensors (Basel) ; 24(2)2024 Jan 16.
Article en En | MEDLINE | ID: mdl-38257655
ABSTRACT
Shared control algorithms have emerged as a promising approach for enabling real-time driver automated system cooperation in automated vehicles. These algorithms allow human drivers to actively participate in the driving process while receiving continuous assistance from the automated system in specific scenarios. However, despite the theoretical benefits being analyzed in various works, further demonstrations of the effectiveness and user acceptance of these approaches in real-world scenarios are required due to the involvement of the human driver in the control loop. Given this perspective, this paper presents and analyzes the results of a simulator-based study conducted to evaluate a shared control algorithm for a critical lateral maneuver. The maneuver involves the automated system helping to avoid an oncoming motorcycle that enters the vehicle's lane. The study's goal is to assess the algorithm's performance, safety, and user acceptance within this specific scenario. For this purpose, objective measures, such as collision avoidance and lane departure prevention, as well as subjective measures related to the driver's sense of safety and comfort are studied. In addition, three levels of assistance (gentle, intermediate, and aggressive) are tested in two driver state conditions (focused and distracted). The findings have important implications for the development and execution of shared control algorithms, paving the way for their incorporation into actual vehicles.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Algoritmos / Agresión Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Sensors (Basel) Año: 2024 Tipo del documento: Article País de afiliación: España

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Algoritmos / Agresión Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Sensors (Basel) Año: 2024 Tipo del documento: Article País de afiliación: España