BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:Israel BEGIN:DAYLIGHT DTSTART:20220325T030000 TZOFFSETFROM:+0200 TZOFFSETTO:+0300 RRULE:FREQ=YEARLY;BYDAY=-1FR;BYMONTH=3 TZNAME:IDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20211031T010000 TZOFFSETFROM:+0300 TZOFFSETTO:+0200 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10 TZNAME:IST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20220101T195443Z UID:F7BE5347-07E1-4D8B-8CD6-0FD3F82D1311 DTSTART;TZID=Israel:20211110T100000 DTEND;TZID=Israel:20211110T160000 DESCRIPTION:Automotive Radar perception thoughts towards AV\n\nTakeaways:\n \n- Everybody speaks about vision and lidar systems\, but Radar is an indi spensable key technology for highly automated and autonomous ADAs\n- HW-SW Co-Design is essential to come to the next level\n- High Performance rada r versus smart radar networks – some thoughts\n- Radar perception can be nefit performance\, if machine learning is applied to it\n- Massive AI is entering the Radar-Perception arena.\n\nAbstract:\n\nOver decades automoti ve driver assistance systems have developed from simple park assistance an d ACC to highly complex L3 functions. Among other issues\, that has been d riven by the dramatic development of radar sensor technology and radar bas ed perception. Radar can “see”\, where other sensors can´t. Due to th eir performance to be packaged nearly invisible\, modern cars can still ap pear as design artwork icons\, like the present EQ-S. With the development towards higher automatization the total perception system has to provide much more comprehensive and precise information to the path planning and b ehavior stages in order to allow proper operation. Based on our experience with the “Bertha Drive” as quasi autonomous vehicle\, we got inside w hat is needed in the future. One outcome of our L4/L5 research projects wa s\, the sensor technology in cooperation with perception algo-concepts hav e to develop along other lines as compared to simple L2 systems. The key n ote will line out from a radar point of view what has been achieved so far and what will be needed in the future for L3 to L5 driving.\n\nDr.-Ing. J uergen Dickmann is head of Radar sensors and radar-based perception for hi ghly automated/autonomous driving\, Mercedes-Benz AG. In this role he is r esponsible for the 6th generation at Mercedes-Benz AG and future radar sol utions towards autonomous driving. In the automotive field\, he introduced for the first time AI concepts for Radar and exploited Radar usage beyond ranging and detection for comprehensive environment perception. Before th at\, he managed the technology transfer process of all perception sensing (Radar\, Laser\, Video\, localization etc.) technologies from research int o series for former passenger car platforms. He conducted radar research a nd pre-developments for radar-based Pre-Crash and driver assistant systems for all company platforms (Passenger cars\, Busses\, Van\, Truck) inside DAIMLER Chrysler AG\, where he introduced Lidar technology in Chrysler car s. In 1986 he started his career at AEG Research Center\, where he did res earch on III/V-semiconductor processing techniques\, mm-Wave device and MM IC-design (up to 120GHz). He achieved several records in high frequency de vices and MMICs with III/V semiconductors. He got the academic award “Pr eis der VDE/ITG” in 1993. The research achievements of him and his group can be found in https://www.researchgate.net/profile/Juergen_Dickmann. He holds various patents.\n\nSpeaker(s): Juergen Dickmann\, \n\nAgenda: \n10 :00-11:00 Meeting BGU Autonomous Driving Race Team\n\n11:00- 12:00 BGU Aut onomous Platforms (BGU ECE research labs)\n\n12:00-13:00 Automotive Radar perception thoughts towards AV ECE BGU Seminar\n\n13:00-15:00 Autonomous v ehicle Cyber security with BGU accelerator team\n\nVirtual: https://events .vtools.ieee.org/m/298697 LOCATION:Virtual: https://events.vtools.ieee.org/m/298697 ORGANIZER:bilik@bgu.ac.il SEQUENCE:1 SUMMARY:Automotive Radar perception thoughts towards AV URL;VALUE=URI:https://events.vtools.ieee.org/m/298697 X-ALT-DESC:Description: <br /><p>Automotive Radar perception thoughts towar ds AV</p>\n<p>Takeaways:</p>\n<ul>\n<li>Everybody speaks about vision and lidar systems\, but Radar is an indispensable key technology for highly au tomated and autonomous ADAs</li>\n<li>HW-SW Co-Design is essential to come to the next level</li>\n<li>High Performance radar versus smart radar net works &ndash\; some thoughts</li>\n<li>Radar perception can benefit perfor mance\, if machine learning is applied to it</li>\n<li>Massive AI is enter ing the Radar-Perception arena.</li>\n</ul>\n<p>&nbsp\;</p>\n<p>Abstract:< /p>\n<p>Over decades automotive driver assistance systems have developed f rom simple park assistance and ACC to highly complex L3 functions. Among o ther issues\, that has been driven by the dramatic development of radar se nsor technology and radar based perception. Radar can &ldquo\;see&rdquo\;\ , where other sensors can&acute\;t. Due to their performance to be package d nearly invisible\, modern cars can still appear as design artwork icons\ , like the present EQ-S. With the development towards higher automatizatio n the total perception system has to provide much more comprehensive and p recise information to the path planning and behavior stages in order to al low proper operation. Based on our experience with the &ldquo\;Bertha Driv e&rdquo\; as quasi autonomous vehicle\, we got inside what is needed in th e future. One outcome of our L4/L5 research projects was\, the sensor tech nology in cooperation with perception algo-concepts have to develop along other lines as compared to simple L2 systems. The key note will line out f rom a radar point of view what has been achieved so far and what will be n eeded in the future for L3 to L5 driving.</p>\n<p>&nbsp\;</p>\n<p>Dr.-Ing. Juergen Dickmann is head of Radar sensors and radar-based perception for highly automated/autonomous driving\, Mercedes-Benz AG. In this role he is responsible for the 6th generation at Mercedes-Benz AG and future radar s olutions towards autonomous driving. In the automotive field\, he introduc ed for the first time AI concepts for Radar and exploited Radar usage beyo nd ranging and detection for comprehensive environment perception. Before that\, he managed the technology transfer process of all perception sensin g (Radar\, Laser\, Video\, localization etc.) technologies from research i nto series for former passenger car platforms. He conducted radar research and pre-developments for radar-based Pre-Crash and driver assistant syste ms for all company platforms (Passenger cars\, Busses\, Van\, Truck) insid e DAIMLER Chrysler AG\, where he introduced Lidar technology in Chrysler c ars. In 1986 he started his career at AEG Research Center\, where he did r esearch on III/V-semiconductor processing techniques\, mm-Wave device and MMIC-design (up to 120GHz). He achieved several records in high frequency devices and MMICs with III/V semiconductors. He got the academic award &ld quo\;Preis der VDE/ITG&rdquo\; in 1993. The research achievements of him a nd his group can be found in <a href="https://www.researchgate.net/profile /Juergen_Dickmann">https://www.researchgate.net/profile/Juergen_Dickmann</ a>. He holds various patents.</p>\n<p>&nbsp\;</p><br /><br />Agenda: <br / ><p>10:00-11:00 Meeting BGU Autonomous Driving Race Team</p>\n<p>11:00- 12 :00 BGU Autonomous Platforms (BGU ECE research labs)</p>\n<p>12:00-13:00 A utomotive Radar perception thoughts towards AV ECE BGU Seminar</p>\n<p>13: 00-15:00 Autonomous vehicle Cyber security with BGU accelerator team</p> END:VEVENT END:VCALENDAR