ロボティクス・メカトロニクス講演会講演概要集
Online ISSN : 2424-3124
セッションID: 2A2-K01
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Bayesian Active Learningの車両動的性能設計への応用
*田島 尚史新谷 浩平尾越 敦貴山本 望琴岩田 基史星原 光太郎
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Drivability is a key aspect of vehicle dynamic performance and comprehensive evaluation is necessary for ensuring drivability quality as such complicated driver operation and vehicle behavior. Furthermore, vehicle control program would be complex for safe and secure vehicle dynamic performance. This paper proposes a novel automated drivability screening system. The proposed system is composed of automated evaluation sub-system and automated exploring sub-system. The automated evaluation sub-system is drivability evaluation by using driver model and PT-VRS equipment to mimic expert driver. The automated exploring sub-system is used to explore feasible region of design space described by control parameters and simulation conditions. To show effectiveness of the proposed system, an example is demonstrated by comparison to expert driver.

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