CN112840284A - 基于数据流的自动驾驶方法、装置、电子设备及存储介质 - Google Patents
基于数据流的自动驾驶方法、装置、电子设备及存储介质 Download PDFInfo
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Abstract
一种基于数据流的自动驾驶方法、装置、电子设备及存储介质,所述方法包括:获取自动驾驶模型的神经网络图以及参数,所述参数为预先训练的参数(201);根据所述自动驾驶模型的神经网络图以及参数,在数据流架构上配置得到所述自动驾驶模型对应的数据流自动驾驶模型(202);获取用于自动驾驶的图像信息(203);将所述图像信息输入到所述数据流自动驾驶模型中进行处理,得到图像处理结果(204);将所述图像处理结果发送到驾驶决策模块中,形成驾驶决策(205)。所述方法可以加速自动驾驶中对图像的识别与检测速度,从而提高自动驾驶的实时性,另外,数据流自动驾驶模型对硬件要求不高,从而可以降低自动驾驶的成本以及功耗。
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PCT国内申请,说明书已公开。
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- PCT国内申请,权利要求书已公开。
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Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN106126481A (zh) * | 2016-06-29 | 2016-11-16 | 华为技术有限公司 | 一种计算引擎和电子设备 |
CN107392189A (zh) * | 2017-09-05 | 2017-11-24 | 百度在线网络技术(北京)有限公司 | 用于确定无人车的驾驶行为的方法和装置 |
CN108012156A (zh) * | 2017-11-17 | 2018-05-08 | 深圳市华尊科技股份有限公司 | 一种视频处理方法及控制平台 |
CN108520296A (zh) * | 2018-03-20 | 2018-09-11 | 福州瑞芯微电子股份有限公司 | 一种基于深度学习芯片动态cache分配的方法和装置 |
CN109583462A (zh) * | 2017-09-28 | 2019-04-05 | 幻视互动(北京)科技有限公司 | 基于深度神经网络的数据流处理方法、装置及*** |
CN109901574A (zh) * | 2019-01-28 | 2019-06-18 | 华为技术有限公司 | 自动驾驶方法及装置 |
CN110046704A (zh) * | 2019-04-09 | 2019-07-23 | 深圳鲲云信息科技有限公司 | 基于数据流的深度网络加速方法、装置、设备及存储介质 |
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Publication number | Priority date | Publication date | Assignee | Title |
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US10007269B1 (en) * | 2017-06-23 | 2018-06-26 | Uber Technologies, Inc. | Collision-avoidance system for autonomous-capable vehicle |
CN108021395B (zh) * | 2017-12-27 | 2022-04-29 | 北京金山安全软件有限公司 | 一种面向神经网络的数据并行处理方法及*** |
CN108803604A (zh) * | 2018-06-06 | 2018-11-13 | 深圳市易成自动驾驶技术有限公司 | 车辆自动驾驶方法、装置以及计算机可读存储介质 |
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- 2019-08-13 WO PCT/CN2019/100382 patent/WO2021026768A1/zh active Application Filing
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Patent Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
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CN106126481A (zh) * | 2016-06-29 | 2016-11-16 | 华为技术有限公司 | 一种计算引擎和电子设备 |
CN107392189A (zh) * | 2017-09-05 | 2017-11-24 | 百度在线网络技术(北京)有限公司 | 用于确定无人车的驾驶行为的方法和装置 |
CN109583462A (zh) * | 2017-09-28 | 2019-04-05 | 幻视互动(北京)科技有限公司 | 基于深度神经网络的数据流处理方法、装置及*** |
CN108012156A (zh) * | 2017-11-17 | 2018-05-08 | 深圳市华尊科技股份有限公司 | 一种视频处理方法及控制平台 |
CN108520296A (zh) * | 2018-03-20 | 2018-09-11 | 福州瑞芯微电子股份有限公司 | 一种基于深度学习芯片动态cache分配的方法和装置 |
CN109901574A (zh) * | 2019-01-28 | 2019-06-18 | 华为技术有限公司 | 自动驾驶方法及装置 |
CN110046704A (zh) * | 2019-04-09 | 2019-07-23 | 深圳鲲云信息科技有限公司 | 基于数据流的深度网络加速方法、装置、设备及存储介质 |
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