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dataset and code for 2016 paper "Learning a Driving Simulator"

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Contributors list

the people's comma

the paper

Learning a Driving Simulator

the driving dataset

7 and a quarter hours of largely highway driving. Enough to train what we had in Bloomberg.


We present two Machine Learning Experiments to show possible ways to use this dataset:

Training a steering angle predictor

Training a generative image model

Downloading the dataset


or get it at comma dataset

45 GB compressed, 80 GB uncompressed

dog/2016-01-30--11-24-51 (7.7G)
dog/2016-01-30--13-46-00 (8.5G)
dog/2016-01-31--19-19-25 (3.0G)
dog/2016-02-02--10-16-58 (8.1G)
dog/2016-02-08--14-56-28 (3.9G)
dog/2016-02-11--21-32-47 (13G)
dog/2016-03-29--10-50-20 (12G)
emily/2016-04-21--14-48-08 (4.4G)
emily/2016-05-12--22-20-00 (7.5G)
frodo/2016-06-02--21-39-29 (6.5G)
frodo/2016-06-08--11-46-01 (2.7G)

Dataset referenced on this page is copyrighted by and published under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License. This means that you must attribute the work in the manner specified by the authors, you may not use this work for commercial purposes and if you alter, transform, or build upon this work, you may distribute the resulting work only under the same license.

Dataset structure

The dataset consists of 10 videos clips of variable size recorded at 20 Hz with a camera mounted on the windshield of an Acura ILX 2016. In parallel to the videos we also recorded some measurements such as car's speed, acceleration, steering angle, GPS coordinates, gyroscope angles. See the full

list here. These measurements are transformed into a uniform 100 Hz time base.

The dataset folder structure is the following:

+-- dataset
|   +-- camera
|   |   +-- 2016-04-21--14-48-08
|   |   ...
|   +-- log
|   |   +-- 2016-04-21--14-48-08
|   |   ...

All the files come in hdf5 format and are named with the time they were recorded. The camera dataset has shape

number_frames x 3 x 160 x 320
type. One of the
hdf5-datasets is called
and addresses the alignment between camera frames and the other measurements.




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Show us amazing stuff on this dataset


Riccardo Biasini, George Hotz, Sam Khalandovsky, Eder Santana, and Niel van der Westhuizen

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