I'm not sure if the vision system is smart enough to be used for collision detection. The radar and ultrasonics are used to detect vehicles, but I believe the camera is just used to help follow the lines painted on the road.
Could it be that this trailer was out of spec? Could that be why 1. there is little damage to the truck, 2. The body is mostly intact but the roof is gone, and 3. the car did not detect the obstacle?
[0] http://www.sparebumper.com/index.php?act=viewProd&productId=...
(look at the NHTSA crash test videos on youtube)
It might be that cameras introduce enough noise and artifacts into the mix that its not worth integrating them at this point.
I don't understand why the truck wasn't detected. Not exactly a small target.
In a different domain, nuclear power plant design, the Three Mile Island plant had a solenoid activated valve for letting high pressure out of the reactor vessel. The problem was that although the plant operators said set the valve to close, the valve was stuck open. It turns out that the control panel light signifying that the valve was closed simply displayed the signal sent to the solenoid, not that the valve had actually closed. No secondary valve, no meter to determine flow.
There had been a operator's manual change for TMI and other plants of the same design, but the proper hardware change was never made. Hence TMI.
But I worry about the kind of thinking as in TMI and also in Tesla.
In the case of Tesla, they have to engineer so that the cars knows about obstacles before crashing into them. The fact that Tesla did not think through this pretty obvious scenario is frightening and suggests a fault in their overall process in engineering. I just feel that Tesla cannot be trusted in terms of engineering unless they have some very smart group check their design.
I doubt BMW would have made such a mistake.
For all of his self-promotion and as head of a car company and a rocket company, Elon Musk has never worked as an engineer for a large firm where he'd be mentored in engineering.
For example, the CEO of GM is an engineer (EE) who was mentored in engineering. https://en.wikipedia.org/wiki/Mary_Barra
And the same for IBM: (EE & CS) https://en.wikipedia.org/wiki/Ginni_Rometty
That looks a tad like fear mongering.
Please be specific. What is the fear mongering? It is a statement from someone educated as an engineer and trained as an engineer.
Engineering, whether it is designing buildings, cars, airplanes, is thinking through the scenarios and testing for them. This seems to be a situation where they were ruling out overhead signs, but because of trucks clearance of these signs would be well over 10 feet and they could check for anything under 10 feet or 8 feet and should have.
And, as I said before, if they didn't think this through, what else that we can't see are they not thinking through?
It's not like they haven't thought this through. Tesla has been clear that this is a Driver Assistance, not a full autonomous car. There are multiple warnings, including every time you enable auto pilot that makes it clear you must pay attention.
This accident while tragic from current reports looks like the driver was not paying attention to the road. The best way that we're going to get to fully autonomous cars is to collecting real world data and I think auto pilot has been a reasonable approach in that direction.
If by that you mean you're a software engineer, I do think it's fair to distinguish between getting an EE/CS degree vs say a BA in CS plus programming experience.
(I write this as someone in the latter group.)
The meta point I'm trying to share is that if you're trying to convince a technical audience(which HN certainly is) berating people by saying "I know better because I have this slip of paper" is the quickest way to get someone to dig in and dismiss your idea.
Engineers are natural skeptics, arguing from the technical side will always be the stronger position.
Basically you're saying that some level of collateral damage is acceptable, and because there's a warning, it's the driver's fault.
To be clear: if someone not paying attention causes a crash, it is their fault. This does not, however, absolve Tesla (or any other manufacturer) from the responsibility for releasing an insufficiently-tested and potentially dangerous system into an environment where anyone who has a passing familiarity with human nature knows it will not be used responsibly.
Tesla calls it 'beta' software, and went so far as to describe the deceased driver as a tester in its press release after the crash. Again, anyone who understands human nature can see that this is a cynical attempt to manipulate the public's opinion. It may, however, come back to bite them, when people start asking WTF they were thinking when they put beta software on the road in the hands of ordinary drivers.
Multiple warnings would seem to me to be insufficient to reduce the hazard presented by the Autopilot functionality; indeed, there are any number of videos of Tesla drivers using the vehicle contra to the warnings. As one specific example, consider that the Tesla Autopilot cautions the driver to maintain hands on the wheel[0], yet does not enforce this requirement[1] despite having the capability to do so[2]. There's also a problem with Musk viz. marketing: he's the very public face of the company, and he is frequently overly optimistic in describing the car's capabilities by blurring the line between current and future capabilities, e.g., implying that holding the wheel isn't critical with a wink-wink, nudge-nudge[3].
Tesla's PLM certainly has some sort of mechanism to continuously examine the risk analysis for the car, yet the Autopilot functionality doesn't seem to have been significantly updated to incorporate the changing risk profile. To add on all of this, why does Autopilot allow one to speed? Why can one enable Autopilot on a road such as the exemplar if it is contrary to the instructions and the car is capable of knowing the difference? What does the risk analysis say on the topic of the feature name "Autopilot" being misunderstood by the public? &c. &c.
I do wonder about the engineering processes at Tesla. I admittedly don't work in automotive, but I do work in a regulated industry, and Tesla's apparent engineering process makes me very uneasy. Risk analyses that I have done took into account that the user may not have read the instructions for use, and I struggle to understand how Tesla could not do the same.
[0] "Drivers must keep their hands on the steering wheel." https://www.tesla.com/presskit/autopilot
[1] "We drove for 10 miles without the message appearing." http://www.teslarati.com/what-happens-ignore-tesla-autopilot...
[2] It's not clear that they have a capacitance sensor as on properly-equipped Mercedes, but Teslas allegedly can detect minute torques applied to the steering wheel as happens when the wheel is held. I recall reading this about the Teslas, but can't find a citation at the moment.
[3] “It works almost to the point where you can take your hands off,” Musk laughs, “but we won’t say that. Almost.” http://www.wired.com/2015/10/tesla-self-driving-over-air-upd... also, "But by April, he told a conference that Autopilot was "almost twice as good as a person," even in its first version." and from the same, "Musk himself has retweeted news reports showing drivers using Autopilot with no hands on the wheel." http://www.autonews.com/article/20160705/OEM06/160709956/tes...
1. Can the fact that the driver is not required to maintain physical control of steering implements cause the computer algorithms to be considered legally culpable (and, by extension, Tesla) for failing to act as a driver is legally required to under Florida law?
2. Does the statements of Elon Musk et al imply that the car is fit to act as a driver in its legal responsibilities under the rules of the road (independent of any legal ability for a driver to discharge those responsibilities to the car), so that failing to, say, be able to detect an obstruction in traffic constitutes a defect such that it's violating the implicit warrant of merchantability?
That looks a tad like denial, especially in the light of your follow-up.
There are sound arguments to be made here. There's no need to make it personal.
If anything uncontrolled intersections and high speed difference merges (200ft radius 270* on ramp I'm looking at you) more efficient to handle with driverless cars, provided they're capable of identifying the road (easy) all the non-static participants (hard).
I'm thinking that a very good visual AI would be necessary to make distinctions like this; radar won't even see a wire, I don't think, and to lidar, it would look a lot like the grass. A touch-sensitive coating on the car would probably be a good idea too, so that the car can tell when if it is starting to scratch its paint on what it thought was an insignificant obstacle, like a branch.
Simply not looking at obstacles in one area because of the difficulty of rejecting false positives is a terrible idea, and demonstrates that that AI is not ready to drive.
"Radar tunes out what looks like an overhead road sign to avoid false braking events"
When I was developing Grand Challenge software, I used to have an Eaton VORAD looking out my window at home, tracking vehicles going through an intersection. It could see cars, but usually not bicycles. Range and range rate were good; azimuth info was flaky. Stationary objects didn't register because it was a Doppler radar. Output from the device was a list of targets and positions, encapsulated in Serial Line Interface Protocol.
The big problem with these radars is not seeing the road itself as an obstacle. When you're moving, everything has a Doppler radar return. Usually, the road is hit at such an oblique angle that it doesn't reflect much. But there are exceptions. The worst case is a grating-floor bridge.
LIDAR isn't a panacea. The charcoal-black upholstery used on many office chairs is so non-reflective in IR that a SICK LMS can't see it at point-blank range.
[1] http://www.fujitsu-ten.com/business/technicaljournal/pdf/38-...