{"id":616,"date":"2019-01-14T12:01:15","date_gmt":"2019-01-14T12:01:15","guid":{"rendered":"http:\/\/levelfivesupplies.com\/?p=616"},"modified":"2022-12-14T12:06:26","modified_gmt":"2022-12-14T12:06:26","slug":"sensors-used-in-autonomous-vehicles","status":"publish","type":"post","link":"https:\/\/levelfivesupplies.com\/sensors-used-in-autonomous-vehicles\/","title":{"rendered":"Autonomous Cars 101: What Sensors Are Used in Autonomous Vehicles?"},"content":{"rendered":"
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As autonomous vehicles<\/a> become closer to reality, a greater number of startups, universities, car manufacturers<\/a> and technology companies are investing in the development of automated driving – with no sign of slowing down.<\/p>\n<\/div>\n\t\t<\/div> \n\n

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If you’re heading down the road (pardon the pun) to autonomy, it can be hard to know where to start. If you’re just beginning to learn about autonomous technology<\/a>, this introductory roundup is for you.<\/p>\n<\/div>\n\t\t<\/div> \n\n

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Why do autonomous cars need so many sensors?<\/h2>\n<\/div>\n\t\t<\/div> \n\n
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Imagine trying to drive down the road with a completely frosted over windscreen. It would be a matter of seconds before you hit something or ran off the road.  <\/p>\n<\/div>\n\t\t<\/div> \n\n

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Autonomous vehicles are no different. They must be able to ‘see’ their environment in order to know where they can and cannot drive, detect other vehicles on the road, stop for pedestrians, and handle any unexpected circumstances they may encounter.<\/p>\n<\/div>\n\t\t<\/div> \n\n

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Each type of sensor has its own strengths and weaknesses in terms of range, detection capabilities, and reliability. A host of technologies is required to provide the redundancy needed to sense the environment safely. When you bring together two heterogeneous sensors, such as camera<\/a> and radar<\/a>, this is called sensor fusion<\/a><\/strong>.<\/p>\n<\/div>\n\t\t<\/div> \n\n

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Autonomous vehicle sensor categories<\/h2>\n<\/div>\n\t\t<\/div> \n\n
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Automotive sensors fall into two categories: active and passive sensors.<\/p>\n<\/div>\n\t\t<\/div> \n\n

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Active sensors<\/strong> send out energy in the form of a wave and look for objects based upon the information that comes back. One example is radar<\/a>, which emits radio waves that are returned by reflective objects in the path of the beam.<\/p>\n<\/div>\n\t\t<\/div> \n\n

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Passive sensors<\/strong> simply take in information from the environment without emitting a wave, such as a camera. <\/p>\n<\/div>\n\t\t<\/div> \n\n

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Cameras<\/h3>\n<\/div>\n\t\t<\/div> \n\n
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\"Valeo<\/a>
Valeo’s 1MP fisheye ETH<\/a> is an ultra-robust, automotive-grade camera, delivering high-quality images in all environmental conditions<\/figcaption><\/figure>\n<\/div>\n\t\t<\/div> \n\n
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Cameras are already commonplace in modern cars. Since 2018, all new vehicles in the US are required to fit reversing cameras as standard. Any car with a lane departure warning<\/a> system (LDW) will use a front-facing camera to detect painted markings on the road.<\/p>\n<\/div>\n\t\t<\/div> \n\n

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Autonomous vehicles are no different. Almost all development vehicles today feature some sort of visible light camera for detecting road markings – many feature multiple or panoramic cameras for building a 360-degree view of the vehicle’s environment. <\/p>\n<\/div>\n\t\t<\/div> \n\n

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Cameras are very good at detecting and recognizing objects, so the image data they produce can be fed to AI-based algorithms for object classification.<\/p>\n<\/div>\n\t\t<\/div> \n\n

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Some companies, such as Intel Mobileye, rely on cameras for almost all of their sensing. However, they are not without their drawbacks. Just like your own eyes, visible light cameras have limited capabilities in conditions of low visibility. Additionally, using multiple cameras generates a lot of video data to process, which requires substantial computing hardware.<\/p>\n<\/div>\n\t\t<\/div> \n\n

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Beyond visible light cameras, there are also infrared<\/a> cameras, which offer superior performance in darkness and additional sensing capabilities.<\/p>\n<\/div>\n\t\t<\/div> \n\n

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Radar<\/h3>\n<\/div>\n\t\t<\/div> \n\n
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