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udacity
self-driving-car
Jupyter Notebook2016–2020
udacity / self-driving-car · Archived

self-driving-car

The Udacity open source self-driving car project

4Distinct people
6Mentions
0Explicit recommenders
6.3KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

The Udacity open source self-driving car project

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year6 dated mentions

Observed mentions: 2016-10-06 02:01:34 UTC to 2020-02-12 13:29:07 UTC.

0122016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments20162017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments20182019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2020

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC211
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC101
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC000
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC101
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC202

What Hacker News says

6 sources
They claim it was ("The dataset was annotated entirely by humans using Autti" via https://github.com/udacity/self-driving-car/tree/master/anno...). But after looking at the data I'm almost certain there was some "tool assist" going on. There were dozens of frames in a row with phantom bounding boxes in the exact same location which made it look in some way automated (maybe user error combined with a "copy bounding boxes from the previous frame" feature?)
In A popular self-driving car dataset is missing labels for hundreds of pedestrians
This is pretty damn impressive - I'll definitely have to give it a deeper look later. On seeing the name, I had hoped it had come out of Udacity and their Self-Driving Car Engineer Nanodegree program; I was a "beta-tester" for that course (read: in the first cohort of the new nanodegree), and the self-driving vehicle that was being developed as a part of that course had the same name. As far as I know, the simulator and code and other stuff we used is all available on github: https://github.com/udacity/self-driving-car https://github.com/udacity/self-driving-car-sim Not as advanced, of course, but still another open-source avenue with a similar purpose. As I recall, it wasn't very difficult to work with, and even with a GTX 750 TI/SC GPU I was able to both render, train, and run models and still have 3D acceleration using CUDA on my Ubunt
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u install. Of course, that maxed out the GPU and put the fans on high, but it still worked fairly well at a decent resolution and level of detail settings. Just to show you don't need an expensive GPU to play around with this stuff...
In Carla – Open-source simulator for autonomous driving research
> That's total bullshit. Udacity has their own self-driving vehicle. They built it for their Self-Driving Vehicle Car Engineer Nanodegree program; I just started term 3 yesterday, and apparently they're going ahead with the plan for student to run code on it. https://medium.com/udacity/term-3-in-depth-on-udacitys-self-... Apparently, they have a test track, and will have a safety driver on-board. For that part of the term (dubbed "Integration"), we'll be broken into teams of 10-20 students, and (somehow) have to coordinate on building the software pieces to run on the vehicle. This will all be done using a custom simulator designed to replicate the test track (similar to what has already been used). Once something is working, the group will then merge the pieces (nodes and modules for ROS and something called AutoWare) all together in a s
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hared github repo. That'll be shipped over to Udacity for testing on "track days", and results sent back to the team for analysis. I'm not sure how well this whole thing is going to work; it's very much an experiment that I believe is unique for a MOOC and hasn't been tried before (develop software as a group project of international students, to drive a real self-driving vehicle on a test track in Mountain View, CA - yep, that seems reasonable). I guess we'll see when we get there. The vehicle is named "Carla", and (overall) it is open-sourced. Here are some links to learn more about it: https://www.udacity.com/self-driving-car https://github.com/udacity/self-driving-car http://www.ros.org/ http://www.tier4.jp/ https://github.com/CPFL/Autoware The vehicle itself is apparently some standard vehicle converted by a third-party company (for the life of me, I can't recall the make or model of the vehicle, nor the company that did the conversion!); if you wanted to DIY this yourself at full scale, you'd basically want a vehicle that uses a mostly drive-by-wire control system for the brakes, accelerator, and steering. If that isn't available, then something that uses electro-hydraulic power braking and steering (or electric power-steering) would be the next best thing. I'd shy away from trying to do this with a standard vehicle; building the actuators you would need to control everything is not a trivial thing to do (and especially to do so safely and reliably). Honestly, if you really wanted to do this, and you didn't want to kill yourself, others, or damage property (as much?) - start out smaller with an RC car or similar. There are plenty of examples on how to do this on the internet, but my favorite go-to example is this one: http://blog.davidsingleton.org/nnrccar/ That one occupies a "soft spot" in me because David Singleton was one of the original students in the Stanford-sponsored ML Class of 2011, taught by Andrew Ng. I was a part of that class; it taught us enough to build such a vehicle, and David was inspired to do so and follow thru with it. What used to cost hundreds-of-thousands of dollars (if not millions) back in the 1980s: https://ftp.utcluj.ro/pub///docs/imaging/Autonomous_driving/... ...could in 2011 be done for much, much less. Final note: I don't have any association with any of this other than being a student in the Udacity course and interested in learning about this technology.
In Comma.ai launches an $88 universal car interface called Panda

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