They did most of that back in 2015.[1] This is version 2. It's interesting what's happening as the control theory people get into machine learning. The controls people don't typically run a neural net as a controller. They use the trained net as a tool for building a controller with known continuity properties. The trouble with pure neural net controllers is that they sometimes do something totally bogus for some dat…
>The trouble with pure neural net controllers is that they sometimes do something totally bogus for some data point within the normal input space. That's not OK in control systems. Is that actually true? Everything we do at work with neural nets seems to indicate continuity. We do stuff with mathematical simulations and imagelike processing. Latent space for auto encoders tend to be smoothly varying throughout the ra…
Autonomous DeLorean drives sideways to move forward
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Re: Autonomous DeLorean drives sideways to move forward
#92Earlier quoted context omitted.
>The trouble with pure neural net controllers is that they sometimes do something totally bogus for some data point within the normal input space. That's not OK in control systems. Is that actually true? Everything we do at work with neural nets seems to indicate continuity. We do stuff with mathematical simulations and imagelike processing. Latent space for auto encoders tend to be smoothly varying throughout the ra…
It's not a continuity problem. It's that "bogus" is defined with respect to what it should do, and that criteria requires a working understanding of the environment which isn't present in the model. If you had all possible images of all possible roads in all possible (lighting, weather,..) conditions, etc. then the ideal behaviour is just a function from all inputs to all desired actions. In the absence of this infin…
But translated to the problem at hand, your argument is correct.
Re: Autonomous DeLorean drives sideways to move forward
#93"This leads to the physically insightful result that one can use the rotation rate of the vehicle's velocity vector to track the path, while simultaneously using the yaw acceleration to stabilize sideslip." This sounds like what every racer will tell you: When the car is sliding, you control your direction with the throttle and control the angle of the slide with the steering.
Re: Autonomous DeLorean drives sideways to move forward
#94So is the general idea that by removing the automated controls, which normally limit drift so human drivers don't lose control, they're able to gather data at the extremes of car handling? I'm curious how this would be applied in the real world. It almost seemed to suggest that a self-driving car would operate with those stability controls turned off, allowing it operate evasive maneuvers that would be impossible in…
Drifting is objectively less effective and safe than normal manuevering and braking. Drifting as a sport exists to look cool and stylish. It's like figure skating with cars. (There is one exception- off road racing on loose surfaces requires drifting. But driving that way off road is only useful for speed at the expense of safety and reliability.)
Drifting, as most things, has its place. If you've ever gone karting on a wet track, you know that you can't really place first against competent drivers unless you use drifting to a significant degree.
Same thing with off-road driving, or driving in general that requires rapid direction changes with low surface traction.
Re: Autonomous DeLorean drives sideways to move forward
#95I genuinely hope Tesla get a 2020 Roadster to lap the Nurburgring on autopiliot with nobody inside. If it lives up to promises, it will easily set the all time lap record as the fastest vehicle ever. It will be an interesting time when a $200k production car can whip the pants of a multi-million dollar F1 racecar.
The torque from the electric motors means they do really well in a straight line drag race, but they're fairly pathetic at any race that involves manoeuvring over a longer course.
Re: Autonomous DeLorean drives sideways to move forward
#96Earlier quoted context omitted.
Drifting is objectively less effective and safe than normal manuevering and braking. Drifting as a sport exists to look cool and stylish. It's like figure skating with cars. (There is one exception- off road racing on loose surfaces requires drifting. But driving that way off road is only useful for speed at the expense of safety and reliability.)
Another exception of a sort, and I believe the one this research is meant to address, is when the drift is initiated unintentionally. Say you hit a patch of black ice mid-corner, for example. This kind of work can expand the envelop of the control system to encompass these scenarios.
Can on/off detection response times and recovery strategies be improved for black ice (and hydroplaning)?
If a car hits black ice, should it power itself down or should it max out the CPU looking for the instant traction returns on any wheel and do whatever it takes to try to slow down?
Re: Autonomous DeLorean drives sideways to move forward
#97So is the general idea that by removing the automated controls, which normally limit drift so human drivers don't lose control, they're able to gather data at the extremes of car handling? I'm curious how this would be applied in the real world. It almost seemed to suggest that a self-driving car would operate with those stability controls turned off, allowing it operate evasive maneuvers that would be impossible in…
Drifting is objectively less effective and safe than normal manuevering and braking. Drifting as a sport exists to look cool and stylish. It's like figure skating with cars. (There is one exception- off road racing on loose surfaces requires drifting. But driving that way off road is only useful for speed at the expense of safety and reliability.)
Re: Autonomous DeLorean drives sideways to move forward
#98Re: Autonomous DeLorean drives sideways to move forward
#99Article mentions each tire gets 7,000Nm torque from its electric motor. Is that a typo?
Re: Autonomous DeLorean drives sideways to move forward
#100Earlier quoted context omitted.
yeah but even then the autopilot need to adapt to the different conditions, it can't just throw the hands up when the conditions are hard and let the driver to crash on its own (at least the ideal full autonomous) so you need to have a "friction" (lateral and longitudinal) input to the model, so that the model forecasted car position matches the actual car future, to allow the autopilot to plan the correct avoidance…
You're assuming Autopilot can't currently account for losing traction (this is probably true). But unexpectedly hitting a patch of black ice won't favor one model over the other - in either case you'll use the same methods to slow down. The only difference would be if you also had to avoid an object some distance ahead, and the drift model helped you maneuver around it by applying the throttle. It's extremely difficu…