- 专利标题: Efficiency improvement for machine learning of vehicle control using traffic state estimation
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申请号: US16503204申请日: 2019-07-03
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公开(公告)号: US11279361B2公开(公告)日: 2022-03-22
- 发明人: Ippei Nishitani , Hao Yang , Rui Guo , Shalini Keshavamurthy , Kentaro Oguchi
- 申请人: TOYOTA MOTOR ENGINEERING & MANUFACTURING NORTH AMERICA, INC.
- 申请人地址: US KY Erlanger
- 专利权人: TOYOTA MOTOR ENGINEERING & MANUFACTURING NORTH AMERICA, INC.
- 当前专利权人: TOYOTA MOTOR ENGINEERING & MANUFACTURING NORTH AMERICA, INC.
- 当前专利权人地址: US KY Erlanger
- 代理机构: Seyfarth Shaw LLP
- 主分类号: H04W4/40
- IPC分类号: H04W4/40 ; B60W30/18 ; G05D1/00
摘要:
A method of improving efficiency of a vehicle behavior controller using a traffic state estimation network is described. The method includes feeding an input of a feature extraction network of the vehicle behavior controller with a sequence of images. The sequence of images include a highway section and corresponding traffic data. The method also includes disentangling an estimated behavior of a controlled ego vehicle. by the traffic state estimation network. The traffic state estimate network disentangles the estimated of the controlled ego vehicle from extracted traffic state features of the input provided by the feature extraction network. The method further includes selecting an action to adjust an autonomous behavior of the controlled ego vehicle according to the estimated behavior of the controlled ego vehicle.
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