BEGIN:VCALENDAR PRODID:-//Microsoft Corporation//Outlook 14.0 MIMEDIR//EN VERSION:2.0 METHOD:PUBLISH X-MS-OLK-FORCEINSPECTOROPEN:TRUE BEGIN:VEVENT CLASS:PUBLIC CREATED:20170324T075416Z DESCRIPTION:http://autonomous-driving-berlin.com/en/\nThis were the main To pics 2017\nThe Tech:AD Business & Technology Sessions\n* Level 3 & 4 – C hallenges for virtual & real life testing\,\nvalidation & simulation\n* Wi ll software be the future differentiator of automated cars? In\naddition\, what does it needs? Scalable\, platform-independent software\narchitectur es for ADAS and automated driving - Is the V Model still\nvalid or do we n eed to restructure the development process?\n* Fail-operational automated driving architectures – What are the\nchallenges in development and test ing? In addition in which extent will\nthe number of test cases increase w ith a higher level automation?\n* How does automated driving impact the us er experience?\nAutonomous driving from an end-user and usability perspect ive\n* Automated parking - Architecture/integration\, modular functional\n development & strategic implications\n* Deep Driving - Artificial intellig ence\, Deep Learning & Deep\nDriving in Automotive - What are state of the art algorithms for\ncomputer vision and machine learning including those most important for\nthe automotive industry?\n* What are the newest concep ts\, challenges\, use cases & game\nchangers to the new AUTOSAR Adaptive P latform for Connected and\nAutonomous Vehicles?\n* Safety and Risk Issues for Self Driving Cars - Consider the\nrequirements of cyber security in a variety of system layouts e.g.\nintegrated network and centralised process or\, to establish what layout\noffers the most secure architecture\n* Ergo nomic Design of the Vehicle Motion in an Automated Driving\nCar - What is a concept for the design of an automated driving system\nthat uses the dri ver's motion perception to feed back the automation\nsystem's state and in tention & which design & interaction concept do we\nneed in which level of automation according to SAE?\n* Embracing the ecosystem of Automated Mobi lity on demand -\nExplore how Automated Mobility on Demand (AMoD) will fil l societal gaps\nfor first mile and last mile public transportation\, rede fining the field\nof mobility\n* Artificial Intelligence for Autonomous Sy stems: Hype vs. Reality\nThe Tech.AD Technical Sessions\n* What is a highl y scalable architecture and function path from\nAssisted to Automated Driv ing?\n* New SPAD sensor technology - from Architectures to Applications\n* Relaying on LIDAR Sensor Technology to Master Complex Traffic\nScenarios - Assessing future opportunities and challenges with LiDAR\nadoption for v ehicle perception\n* What is the potential role of the tire technology for safe\nautonomous driving? How can the tire sensor enhance automated drivi ng?\n* On-The-Road Beta Testing and verification for autonomous driving\n – What are the challenges? In addition\, how can recent advances in\nmod eling\, verification\, and implementation technologies simultaneously\nred uce and accelerate the required testing and verification effort?\n* What a re the requirements future complexity driven by Level 3 &\n4 automation?\n * Architecture needs for automated driving - How do you envisage\nthe arc hitecture that will need to be implemented to deliver automated\ndriving ( Level 3 and above)?\n* Vehicle Automation and the importance of Radar Sens ors - Why is\nenvironmental perception and understanding of the backbone o f driverless\ncars important?\n* Novel LiDAR sensing technology: A new app roach to detection and\nranging- Implementation of high-performance LiDAR flash and LiDAR\nscanning micro-mirrors for autonomous driving application s\n* From Fail-Safe components to operational safe systems for\nAutomated Driving - How is operational safety looking beyond ISO 26262?\n* How is Sy stem-Theoretic Safety & Security Analysis with STPA-Sec\nworking & which a re the safety architecture solutions needed to be\ndiscussed?\n* Cognitive Cars & Vehicles – Challenges for imaging\, perception\nsytems and AI\n* Expectations on AI - Detection and recognition of multiple\nobjects\, imp roved perception\, reduced power consumption\, improved object\nclassifica tion\, recognition and prediction of actions\, and reduction of\ndevelopme nt time of ADAS systems.\n* Deep learning architecture in embedded systems \n DTEND;VALUE=DATE:20180307 DTSTAMP:20131118T145455Z DTSTART;VALUE=DATE:20180305 LAST-MODIFIED:20170324T075416Z LOCATION:Berlin\, Germany PRIORITY:5 SEQUENCE:0 SUMMARY;LANGUAGE=de:Automotive Tech.AD Berlin 2018 TRANSP:TRANSPARENT UID:040000008200E00074C5B7101A82E00800000000D0B36C2F76E4CE01000000000000000 01000000009AD90BDF61FB040A36CA5D8F32EFB47 X-ALT-DESC;FMTTYPE=text/html:\n\n< /xml>

http://autonomous-driving-berlin.com/en/

This were the main Topics 2017

Th e Tech:AD Business &\; Technology Sessions

  • Level 3 &\; 4 – Challenges for virtual &\; real life testing\, validation &\; simulation
  • Will software be the future differentiator of automated cars? In addition\, what does it needs? Scalable\, platform-in dependent software architectu res for ADAS and automated driving - Is the V Model still v alid or do we need to res tructure the developme nt process?
  • Fail-operational automated driving architectures – What are the challenges in development and testing? In addition in which ext ent will the number of test cases increase with a higher level automation?
  • How does automated driving impact the user experience? Autonomous driving from an end-user and usability perspective
  • Automated parking - Architecture/integration\, modular functiona l development &\; s trategic implications
  • Deep Driving - Artificial intelligence\, Deep Learning &\; Deep Driving in Automotive - What are state of the art algorithms for computer vision and machine learning including th ose most important for the automotive industry?< /li>
  • What are the newest con cepts\, challenges\, u se cases &\; game changers to the new AUTOSAR Adaptive < span class=SpellE>Platform for Connected and Autonomous Vehicles?
  • Safety and Risk Issues for Self Driving Cars - Consider the requirements of cyber security in a variety of system layouts e.g. integrated network and centralised processor\, to establish what layout offers the most secure architecture
  • Ergonomic Design of the Vehicle Motion in an Automated Drivin g Car - What is a concept for the design of an automated driving system that uses the driver's motion perception to feed back the automation syste m's state and < span class=SpellE>intention &\; which design &\; interaction con cept do we need in which level of automation according to SAE?
  • Embracing the ecosystem of Aut omated Mobility on demand - Explore how Auto mated Mobility on Demand (AMoD) will fill societal gaps for first< /span> mile and last < span class=SpellE>mile public transportation\, redefining the field of mobility
  • Artificial Intelligence for Autonomous Systems: Hype vs. R eality

 

The Tech.AD Technical Sessions

  • What i s a highly scalable architecture and function path from Assisted to Automated Drivin g?
  • New SPAD sensor technology - from Architectures to Applications
  • Relaying on LI DAR Sensor Technology to Master Complex Traffic Scenarios - Assessing future opportunities < span class=SpellE>and challenges with LiDAR adoption for vehicle perception
  • What is the po tential role of the tire technology for safe autonomous driving? How can the tire senso r enhance automated driving?
  • On-The-Road Beta Testing and verification for autonomous drivingWhat are the < span class=SpellE>challenges? In addition \, how can recent advances in modeling\, verification\, and implementation technologies simultaneously reduce and accelerate the requir ed testing and verification effort?
  • What are < span class=SpellE>the requirements future complexity driven by Level 3 &\; 4 automation?
  • Architect ure needs for < span class=SpellE>automated driving  - How do you envisage the architecture that will need to be implemented to deliver automated driving (Level 3 and above)?
  • Vehicle Automation and the importance of Radar Sensors - Why is environmental perception and understanding of the backb one of driverless cars important?
  • Novel LiDAR sensing technology: A new approach to detection and ranging- Implementation of high-perf ormance LiDAR flash and LiDAR scanning micro-mirrors for autonomous d riving applications
  • From Fail-Safe components to operational safe systems for Automated Driving - How is operational sa fety looking beyond ISO 26262?
  • How is System-Theoretic Safety &\; Security Analysis with ST PA-Sec working &\; which are the safety architecture solutions needed to be discussed?
  • Cognitive Cars &\; VehiclesChallenges for imaging\, perception sytems and AI
  • Expectations on AI - Detection and recognition of multiple objects\, improved perception\, reduced power consumption\, improved < span class=SpellE>object classification\, recognition and prediction of actions\, and re duction of   development time of ADAS systems.
  • Deep learning ar chitecture in embedded systems
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