Driverless Vehicle Makers are Switching to Trucks to make things Easier — It’s Nowhere Near Enough
After Starsky Robotics went bankrupt Waymo and Aurora announced they are now working on autonomous long-haul trucks. The thought being the use case is easier so they will get to L4 faster. Yes, slightly on the first part. Nowhere close on the second.
The problem is the whole development and testing approach not the public road use cases.
Highway driving, like most “geofencing” does not eliminate enough scenarios or objects to mitigate the massive time, money and safety issues with the use of public shadow and safety driving and use of gaming-based simulation. Particularly if you rely on a significant amount of deep learning. For example — most of the pattern confusion issues around signs, degraded signs, clothing etc would still exist. While unlikely a person wearing any article of clothing with any pattern that could confuse the system should still be handled. And from a “safety driver” POV the average speeds involved make having a catastrophic accident more likely.
The solution is to switch most of the development and testing to proper simulation. One that can create a legitimate digital twin.
More in my articles here
The Autonomous Vehicle Industry can be Saved by doing the Opposite of what is being done now to create this technology
Proposal for Successfully Creating an Autonomous Ground or Air Vehicle
Simulation can create a Complete Digital Twin of the Real World if DoD/Aerospace Technology is used
- https://medium.com/@imispgh/simulation-can-create-a-complete-digital-twin-of-the-real world-if-dod-aerospace-technology-is-used-c79a64551647
Simulation Photorealism is almost Irrelevant for Autonomous Vehicle Development and Testing
Autonomous Vehicles Need to Have Accidents to Develop this Technology
Using the Real World is better than Proper Simulation for AV Development — NONSENSE
- https://medium.com/@imispgh/using-the-real world-is-better-than-proper-simulation-for-autonomous-vehicle-development-nonsense-90cde4ccc0ce
Why are Autonomous Vehicle makers using Deep Learning over Dynamic Sense and Avoid with Dynamic Collision Avoidance? Seems very inefficient and needlessly dangerous?
The Hype of Geofencing for Autonomous Vehicles
Remote Control for Autonomous Vehicles — A far worse idea than the use of Public “Safety” Driving
My name is Michael DeKort — I am a former system engineer, engineering and program manager for Lockheed Martin. I worked in aircraft simulation, the software engineering manager for all of NORAD, the Aegis Weapon System, and on C4ISR for DHS.
Key Industry Participation
- Founder SAE On-Road Autonomous Driving Simulation Task Force
- Member SAE ORAD Verification and Validation Task Force
- Stakeholder for UL4600 — Creating AV Safety Guidelines
- Member of the IEEE Artificial Intelligence & Autonomous Systems Policy Committee (AI&ASPC)
- Presented the IEEE Barus Ethics Award for Post 9/11 Efforts
My company is Dactle
We are building an aerospace/DoD/FAA level D, full L4/5 simulation-based testing and AI system with an end-state scenario matrix to address several of the critical issues in the AV/OEM industry I mentioned in my articles below. This includes replacing 99.9% of public shadow and safety driving. As well as dealing with significant real-time, model fidelity and loading/scaling issues caused by using gaming engines and other architectures. (Issues Unity will confirm. We are now working together. We are also working with UAV companies). If not remedied these issues will lead to false confidence and performance differences between what the Plan believes will happen and what actually happens. If someone would like to see a demo or discuss this further please let me know.