{"id":2738,"date":"2018-08-10T21:19:43","date_gmt":"2018-08-10T21:19:43","guid":{"rendered":"https:\/\/athis-consulting.com\/news\/?p=2738"},"modified":"2018-10-02T10:28:51","modified_gmt":"2018-10-02T10:28:51","slug":"image-sensors-the-eyes-for-autonomous-vehicles","status":"publish","type":"post","link":"https:\/\/athis-technologies.com\/news\/innovation\/automotive\/2018\/image-sensors-the-eyes-for-autonomous-vehicles\/","title":{"rendered":"Image Sensors: The Eyes For Autonomous Vehicles"},"content":{"rendered":"

Radhika Arora, Sr. Manager at ON Semiconductor\u2014Image Sensor Group (ISG), led a talk that fell into the Disruptive Technology category titled, \u201cImage Sensors\u2014Eyes for Autonomous Vehicles.\u201d<\/p>\n

\"\"<\/p>\n

According to the IEEE WIE ILC description, the presentation \u201cinvestigates the challenges and opportunities pertaining to imaging that may arise as a result of emerging autonomous vehicle (AV) technologies.\u201d AV technology will bring fundamental change, create disruption, and have far-reaching impacts. Where do image sensors fall into the equation to make the AV segment successful?<\/p>\n

\"\"<\/p>\n

Arora began by saying over the last five years, the talk of autonomous tech has evolved. Initial chatter started as science fiction, but now self-driving cars have shifted\u00a0to an inevitability.<\/p>\n

\u201cIn California, 54 companies have been grated permits to test autonomous technologies on the streets. These companies are redefining modern mobility,\u201d says Arora.<\/p>\n

Voyage was chosen as one of the examples, which has a\u00a0self-driving taxi service<\/a>\u00a0at The Villages, Florida. Waymo followed, which has a public trial of self-driving vehicles under its\u00a0Early Rider program<\/a>\u00a0in Arizona. Ford and Domino rounded out the examples, with their\u00a0human-free delivery service<\/a>.<\/p>\n

With all these trials, what is the potential impact of autonomous driving? \u201cAV technology will have an estimated seven trillion dollar impact on the global economy,\u201d Arora says.<\/p>\n

According to Arora, autonomous cars must perform better than a human. It needs to have a 360 view without any blind spots. To achieve this, Arora points out three essential sensors: image, lidar, and radar.<\/p>\n

The talk honed in on image\u00a0sensors, which are advantageous since they can distinguish color. This proves useful analyzing traffic lights and lane markings. According to Arora, image sensors are attractive to the self-driving market because of its low cost. However, image sensors have trouble in bad weather and low-light conditions.<\/p>\n

The trends of autonomous vehicle cameras were outlined as the following: More Cameras, Wider Field of View, More Pixels, More Advanced. \u201cThe bottom line is, the more pixels you have the smaller the object you can detect at a further distance,\u201d Arora adds.<\/p>\n

The talk ended with cybersecurity of an image sensor. \u201cHacking image sensors basically means you\u2019re blinding the car. A denial of service can make the car go blind,\u201d says Arora.<\/p>\n

She outlined the following attacks during the presentation:<\/p>\n

    \n
  1. Denial of Service:<\/strong>\u00a0Loss of video, no signal, black\/white screen.<\/li>\n
  2. Tampering:<\/strong>\u00a0Changing video data to add\/remove\/modify objects in view.<\/li>\n
  3. Repudiation:\u00a0<\/strong>Cause receiver to reject or discard data.<\/li>\n
  4. Eavesdropping\/Privacy:\u00a0<\/strong>Capturing video content for malicious purposes (tracking, etc.).<\/li>\n
  5. Spoofing:<\/strong>\u00a0Fool receiver into accepting data from an untrusted source.<\/li>\n<\/ol>\n

    Although promising, there is a broad spectrum of issues from safety to environmental conditions that self-driving car sensors\u00a0need to address before we permanently take our hands off the steering wheel.<\/p>\n

     <\/p>\n","protected":false},"excerpt":{"rendered":"

    Radhika Arora, Sr. Manager at ON Semiconductor\u2014Image Sensor Group (ISG), led a talk that fell into the Disruptive Technology category titled, \u201cImage Sensors\u2014Eyes for Autonomous Vehicles.\u201d According to the IEEE WIE ILC description, the presentation \u201cinvestigates the challenges and opportunities pertaining to imaging that may arise as a result of emerging autonomous vehicle (AV) technologies.\u201d […]<\/p>\n","protected":false},"author":5,"featured_media":3083,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"amp_status":"","_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"Image Sensors: The Eyes For Autonomous Vehicles at IEEE Women in Engineering \r\n#sensors #AI #Womenintech","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","enabled":false}}},"categories":[208,15],"tags":[256,261,126,218],"jetpack_publicize_connections":[],"yoast_head":"\nImage Sensors: The Eyes For Autonomous Vehicles - 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