Data-Learning Game Output Regulation Approach for Human-Machine Cooperative Driving Toward Varied Drivers and Vehicles

For personalized human-machine cooperative (HMC) control, traditional model-driven approaches, which rely on predefined driver-vehicle-road (DVR) models, often struggle to adapt to individual driver differences. To address this, a data-learning shared control strategy based on game output regulation...

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Veröffentlicht in:	IEEE transactions on intelligent transportation systems 2024-12, Vol.25 (12), p.20190-20202
Hauptverfasser:	Guo, Hongyan, Shi, Wanqing, Guo, Jingzheng, Liu, Jun, Cao, Dongpu, Chen, Hong
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Adaptation models adaptive dynamic programming Dynamic programming game output regulation Game theory Human-machine cooperative driving Human-machine systems personalized drivers Regulation Roads Vehicle dynamics Vehicles
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