Safety Engineers involved in Autonomous Vehicle industry need to do their Due Diligence
Recently I started a LinkedIn thread with a “safety engineer” from GM, a company using the safety driving approach, who defended Tesla’s “Autopilot”. They stated the drivers who died bore responsibility because they are supposed to be in control at all times. When I stated the safety driving approach should largely not exist, therefore the position the safety drivers are put in should not exist, as well as the supporting argument I will make below, they ignored every one of those points and doubled down on their original statement. As “safety engineers” these folks have a very high bar set for them. That means it is incumbent on these folks to do their professional, technical, ethical and moral due diligence on these issues, especially given at least 6 people have died as human Guinea pigs (two more, including one more this week, maybe beaded to the list when AP use is confirmed) and thousands more will come as the safety driving and machine learning take on accident scenarios. While I realize these folks have significant Maslow’s Triangle issues to contend with regarding their jobs and voicing an opinion counter to their company’s official positions, and the massive industry echo chamber (food, shelter, clothing, ego etc) to deal with, I believe that as “safety engineers” they must do their homework, get in the weeds and take the path that science, ethics and morality dictates. At the very least they should defend their POV and clearly specify where each one pf my points is incorrect and why. And when they become aware of the issues, how to resolve them and that they are on the wrong side, they have the same responsibilities to change their organizations minds or resign. If they do not do this, they will be giving tacit approval to a process that injures and kills people for no reason. Providing false confidence and enabling more harm to come to people. Which at some point will involve the first pointless death of a child or family.
With regard to the approach the industry is using to develop and test their autonomous technology. It is a myth that public shadow and safety driving can create a legitimate autonomous vehicle and that the lives the process takes are necessary and for the greater good. That it is impossible to drive the trillion miles or spend $300B to stumble and restumble on all the scenarios necessary to complete the effort. In addition, the process harms people for no reason. The first issue is handover. The process cannot be made safe for most complex scenarios because the time to regain proper situational awareness and do the right thing, especially in time critical scenarios. cannot be provided. Another dangerous area is learning accident scenarios. AV makers will have to run thousands of accident scenarios thousands of times to accomplish this. That will cause thousands of injuries and deaths. The final issue is Deep Learning which is often fooled by patterns and shadows. The solution is to replace the majority of that Public shadow Driving and Deep Learning (along with inferior gaming-based simulation) with simulation based on DoD technology and Dynamic Sensing and Avoidance.
This is the article that explains the majority of my position.
Proposal for Successfully Creating an Autonomous Ground or Air Vehicle
Please find more information below
Simulation can create a Complete Digital Twin of the Real World if DoD/Aerospace Technology is used
Why are Autonomous Vehicle makers using Deep Learning over Dynamic Sense and Avoid with Dynamic Collision Avoidance? Seems very inefficient and needlessly dangerous?
Using the Real World is better than Proper Simulation for AV Development — NONSENSE
SAE Autonomous Vehicle Engineering Magazine — End Public Shadow/Safety Driving
Relevant Biography
Former system engineer, engineering and program manager for Lockheed Martin. Including aircraft simulation, the software engineering manager for all of NORAD and the Aegis Weapon System.
Key Autonomous Vehicle Industry Participation
- Lead — SAE On-Road Autonomous Driving (ORAD) Simulation Task Force
- Member SAE ORAD Verification and Validation Task Force
- SME — DIN/SAE International Alliance for Mobility Testing & Standardization group to create sensor simulation specs
- Stakeholder for UL4600 — Creating AV Safety Guidelines
- Member of the IEEE Artificial Intelligence & Autonomous Systems Policy Committee
- Presented the IEEE Barus Ethics Award for Post 9/11 DoD/DHS Efforts
My company is Dactle — We are building an aerospace/DoD/FAA level D, full L4/5 simulation-based development and testing system with an end-state scenario matrix to address all of these issues. We can supply all of the scenarios, the scenario matrix tool, the data, the integrated simulation or any part of this system. A true all model type digital twin. If someone would like to see a demo or discuss this further please let me know.
