• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>ATZ Electronics Worldwide >Teaching Cars to Hear
【24h】

Teaching Cars to Hear

机译：教学汽车听

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Visual sensors can only detect objects in their direct line of sight. MEMS microphones are not subject to this limitation. Infineon and Reality AI recommend these components - together with machine learning methods - as a useful addition for future driver assistance systems. For example, they can help ADAS perceive emergency vehicles with warning signals earlier. Even today, autonomous shuttle buses are already on the road on some fixed routes in public transport. The first robo-taxis are expected to be in use in Germany from 2022. Self-driving cars also aim to provide a cost-effective transportation solution for seniors who can no longer drive themselves but live in residential neighborhoods that can only be reached by car. On the way to a fully autonomous vehicle, Advanced Driver Assistance Systems (ADAS), which already relieve the driver of some tasks, are standard in many modern vehicles. Some suppliers are already focusing on Level 3 of automated driving, which includes hands-off and eyes-off paradigms, but still requires the driver to intervene in certain hazardous situations. Sensor technology is a key component of platforms for automated driving: Only if the vehicle correctly captures all important data from the environment it can draw the right conclusions and react accordingly. Existing automotive environment sensing solutions typically use cameras or active sensors such as lidar, radar, or ultrasonic sonar. These approaches can be costly and are subject to significant limitations because targets must be in a clear line of sight to the sensor. Furthermore, the target must be specifically illuminated by light or another energy source; dust, weather and obstacles will affect the sensors.
机译：在他们的视觉传感器只能检测对象直接的视线。受此限制。人工智能推荐这些组件——一起机器学习方法——作为一个有用的补充为未来的驾驶员辅助系统。的例子中,他们可以帮助ADAS感知进入紧急状态车辆与早期预警信号。今天,自治摆渡车已经在在公共场合的道路在一些固定的航线交通工具。在使用中从2022年在德国。也提供一个具有成本效益的目标老年人不能运输解决方案不再自己开车,但生活在住宅社区只能达成的车。全自动汽车,先进驾驶员辅助系统(ADAS)了缓解一些任务的司机,是标准的许多现代的汽车。关注三级自动驾驶,包括不干涉和目光从范例,但是仍然需要司机在特定的干预危险的情况。组件自动驾驶的平台:只有在车辆正确捕获所有从环境中重要的数据可以画正确的结论,做出相应的反应。现有汽车环境传感解决方案通常使用相机或活跃传感器等激光雷达、雷达或超声波声纳。方法可以是昂贵的和受很大的局限性必须因为目标传感器在一个清晰的视线。此外,目标必须明确照射的光或另一种能量来源;灰尘,会影响天气和障碍传感器。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号