Unfortunately I do not have any real life data labelled or not. I just thought this is a hot domain in which Numenta could find an interested partner.
It just came to me while watching what Comma.ai is doing: they sell a lane-tracking device running their open-sourced software. It is just a phone sized computer with two cameras, inertial sensors, gps, and an interface to car’s computer. They support a few dozen car models, ones with drive-by-wire capability and radar collision sensor.
Through their already sold devices they collected a lot of driving data which they use to improve/train the software/ AI model.
The data is collected in both autonomous and human driver mode.
What they also attempt, is to develop a full autonomous driving AI and previously collected data will be very useful for that.
What George Hotz mentioned is even they have collected millions of miles, the actual training set is much smaller, and I can only assume they-re using some statistics to cherry pick this smaller training set.
Other companies attempting to make autonomous vechicles probably are applying the same strategy.
@rhyolight from all I’ve read I understand the anomaly detector is unsupervised, I assume the labeled data you mention is only to estimate its capabilities?
@sheiser1 yes, that’s the kind of stuff I had in mind. There-s a certain “rythm” when a driver does a normal lane change and a different one when it reacts to an unexpected event… and probably skips the turn signal.
I do not have any data myself, I wonder if a phone just recording video (placed as a dashcam) together with accel/gyro over a few weeks commuting would show some relevant information.
If anomaly detector on accelerator/gyro/gps picks some moments in time, one can check the video record at that moment to see if it was an useful insight or not.
Of course easier would be to convince a developer like comma.ai to provide a few hundred miles sample of their data for a test.
@MaxLee - yeah that is a great simulator. I like there are many parts bundled together and has a really good tutorial series. I think it could be a good training arena/environment for an embodied agent. Yeah the shape and “muscles” of a car. Not necessary to achieve autonomous driving but to have agents evolve/train/play together in a simulated world and see how they interact with each other.
Who knows, animal-type cognition might be the solution for autonomous driving.