https://handong1587.github.io/deep_learning/2015/10/09/dl-and-autonomous-driving.html

Deep Learning and Autonomous Driving

Published: 09 Oct 2015 Category: deep_learning

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1. Courses

2. Papers

   1. DeepDriving

   2. BRAIN4CARS: Cabin Sensing for Safe and Personalized Driving

3. Projects

4. Blogs

Courses

(Toronto) CSC2541: Visual Perception for Autonomous Driving, Winter 2016

• homepage: http://www.cs.toronto.edu/~urtasun/courses/CSC2541/CSC2541_Winter16.html

(MIT) 6.S094: Deep Learning for Self-Driving Cars

• homepage: http://selfdrivingcars.mit.edu/

• github: https://github.com/lexfridman/deepcars

• youtube: https://www.youtube.com/playlist?list=PLrAXtmErZgOeiKm4sgNOknGvNjby9efdf

• mirror: https://pan.baidu.com/s/1boLRFaB

How to Land An Autonomous Vehicle Job: Coursework

• blog: https://medium.com/self-driving-cars/how-to-land-an-autonomous-vehicle-job-coursework-e7acc2bfe740#.7vfjx3i1j

Papers

An Empirical Evaluation of Deep Learning on Highway Driving

• arxiv: http://arxiv.org/abs/1504.01716

• github: https://github.com/brodyh/caffe

DeepDriving

DeepDriving: Learning Affordance for Direct Perception in Autonomous Driving

• project page: http://deepdriving.cs.princeton.edu/

• paper: http://deepdriving.cs.princeton.edu/paper.pdf

• code: http://deepdriving.cs.princeton.edu/DeepDriving.zip

End to End Learning for Self-Driving Cars

• intro: NVIDIA DevBox and Torch 7, 30 FPS

• arxiv: http://arxiv.org/abs/1604.07316

• blog: https://devblogs.nvidia.com/parallelforall/deep-learning-self-driving-cars/

• demo: https://www.youtube.com/watch?v=NJU9ULQUwng&feature=youtu.be

• github: https://github.com/SullyChen/Nvidia-Autopilot-TensorFlow

End-to-End Deep Learning for Self-Driving Cars

• blog: https://devblogs.nvidia.com/parallelforall/deep-learning-self-driving-cars/

Can we unify monocular detectors for autonomous driving by using the pixel-wise semantic segmentation of CNNs?

• arxiv: http://arxiv.org/abs/1607.00971

BRAIN4CARS: Cabin Sensing for Safe and Personalized Driving

Brain4Cars: Sensory-Fusion Recurrent Neural Models for Driver Activity Anticipation

Brain4Cars: Car That Knows Before You Do via Sensory-Fusion Deep Learning Architecture

• arxiv: http://arxiv.org/abs/1601.00740

Car that Knows Before You Do: Anticipating Maneuvers via Learning Temporal Driving Models

• arxiv: http://arxiv.org/abs/1504.02789

• github: https://github.com/asheshjain399/ICCV2015_Brain4Cars

Recurrent Neural Networks for Driver Activity Anticipation via Sensory-Fusion Architecture

• project page: http://www.brain4cars.com/

• arxiv: http://arxiv.org/abs/1509.05016

• github: https://github.com/asheshjain399/RNNexp

Long-term Planning by Short-term Prediction

• arxiv: http://arxiv.org/abs/1602.01580

Learning a Driving Simulator

• intro: by hacker Geohot

• project page: http://research.comma.ai/

• arxiv: http://arxiv.org/abs/1608.01230

• paper: https://github.com/commaai/research/blob/master/paper/commalds.pdf

• github: https://github.com/commaai/research

Comma.ai open-sources the data it used for its first successful driverless trips

• blog: https://techcrunch.com/2016/08/03/comma-ai-open-sources-the-data-it-used-for-its-first-successful-driverless-trips/

Autonomous driving challenge: To Infer the property of a dynamic object based on its motion pattern using recurrent neural network

• arxiv: http://arxiv.org/abs/1609.00361

Safe, Multi-Agent, Reinforcement Learning for Autonomous Driving

• arxiv: https://arxiv.org/abs/1610.03295

Learning from Maps: Visual Common Sense for Autonomous Driving

• arxiv: https://arxiv.org/abs/1611.08583

SAD-GAN: Synthetic Autonomous Driving using Generative Adversarial Networks

• intro: Accepted at the Deep Learning for Action and Interaction Workshop, 30th Conference on Neural Information Processing Systems (NIPS 2016)

• arxiv: https://arxiv.org/abs/1611.08788

MultiNet: Real-time Joint Semantic Reasoning for Autonomous Driving

• intro: first place on Kitti Road Segmentation. joint classification, detection and semantic segmentation via a unified architecture, less than 100 ms to perform all tasks

• arxiv: https://arxiv.org/abs/1612.07695

• github: https://github.com/MarvinTeichmann/MultiNet

Projects

Caffe-Autopilot: Car autopilot software that uses C++, BVLC Caffe, OpenCV, and SFML

• github: https://github.com/SullyChen/Caffe-Autopilot

Self Driving Car Demo

• intro; A project that trains a virtual car to how to move an object around a screen (drive itself) without running into obstacles using a type of reinforcement learning called Q-Learning

• github: https://github.com/llSourcell/Self-Driving-Car-Demo/

Autoware: Open-source software for urban autonomous driving

• github: https://github.com/CPFL/Autoware

Open Sourcing 223GB of Driving Data

• homepage: https://udacity.com/self-driving-car

• blog: https://medium.com/udacity/open-sourcing-223gb-of-mountain-view-driving-data-f6b5593fbfa5#.q8nk5bfpp

• github: https://github.com/udacity/self-driving-car

Machine Learning for RC Cars

• github: https://github.com/kendricktan/suiron

Self Driving (Toy) Ferrari

• github: https://github.com/RyanZotti/Self-Driving-Car

Lane Finding Project for Self-Driving Car ND

• github: https://github.com/udacity/CarND-LaneLines-P1

Instructions on how to get your development environment ready for Udacity Self Driving Car (SDC) Challenges

• github: https://github.com/gtarobotics/self-driving-car

DeepDrive: self-driving car AI

• intro: Caffe Model / Dataset / Tips and Tricks

• homepage: http://deepdrive.io/

DeepDrive setup: Run a self-driving car simulator from the comfort of your own PC

• github: https://github.com/crizCraig/deepdrive

DeepTesla: End-to-End Learning from Human and Autopilot Driving

http://selfdrivingcars.mit.edu/deeptesla/

Blogs

Self-driving cars: How far away are we REALLY from autonomous cars?(7 Aug 2015)

http://www.alphr.com/cars/1001329/self-driving-cars-how-far-away-are-we-really-from-autonomous-cars

Practice makes perfect: Driverless cars will learn from their mistakes(9 Oct 2015)

http://www.alphr.com/cars/1001713/practice-makes-perfect-driverless-cars-will-learn-from-their-mistakes

Eyes on the Road: How Autonomous Cars Understand What They’re Seeing

• blog: http://blogs.nvidia.com/blog/2016/01/05/eyes-on-the-road-how-autonomous-cars-understand-what-theyre-seeing/

Human-in-the-loop deep learning will help drive autonomous cars

Human-in-the-loop deep learning will help drive autonomous cars

Using reinforcement learning in Python to teach a virtual car to avoid obstacles

• part 1: https://medium.com/@harvitronix/using-reinforcement-learning-in-python-to-teach-a-virtual-car-to-avoid-obstacles-6e782cc7d4c6#.rneyuerga

• part 2: https://medium.com/@harvitronix/reinforcement-learning-in-python-to-teach-a-virtual-car-to-avoid-obstacles-part-2-93e614fcd238#.1pt1lli4c

• part 3: https://medium.com/@harvitronix/reinforcement-learning-in-python-to-teach-an-rc-car-to-avoid-obstacles-part-3-a1d063ac962f#.jwzm2v1r4

• github: https://github.com/harvitronix/reinforcement-learning-car

Autonomous RC car using Raspberry Pi and Neural Networks

• blog: http://www.multunus.com/blog/2016/07/autonomous-rc-car-using-raspberry-pi-and-neural-networks/

• github: https://github.com/multunus/autonomous-rc-car

The Road Ahead: Autonomous Vehicles Startup Ecosystem

https://medium.com/the-mission/the-road-ahead-autonomous-vehicles-startup-ecosystem-3c91d546673d#.gft1xyh9l

Deep Driving – A revolutionary AI technique is about to transform the self-driving car

https://www.technologyreview.com/s/602600/deep-driving/

**Visualizations for regressing wheel steering angles in self driving cars with Keras **

• blog: http://jacobcv.blogspot.jp/2016/10/visualizations-for-regressing-wheel.html

• github: https://github.com/jacobgil/keras-steering-angle-visualizations

Recruitment Information:

Our company is actively recruiting General Intelligence autonomous driving research talents in Shanghai, inviting engineers and technical experts in the following areas to explore and apply autonomous driving in the domestic frontier:

~ Driving Hardware Engineer

~ Driving Software Development Engineer

~ Decision Planning Algorithm Engineer

~ Deep Learning, Computer Vision, Sensors and other fields…

We are eager to find technical experts in this field, and we also welcome graduate students with certain experience to intern and gain experience!

We expect you to have strong learning ability: hands-on ability, and a dream for autonomous driving and artificial intelligence.

– As long as you have a certain foundation in deep learning, and have a strong interest in autonomous driving, we welcome you

– Of course, familiarity with Linux, Raspberry Pi, Python, TensorFlow, simulator simulation, etc. is required

– Familiarity with autonomous driving hardware sensors, etc.

– Familiarity with Udacity or the Commaai community is better

Familiarity with commaai is a must for the interview!https://github.com/commaai

Previous achievements or projects are more than welcome.

Work location: Shanghai Zhangjiang Hi-Tech Park; Full-time, part-time, and internship opportunities are available; General Intelligence provides a stage for you to showcase and challenge! If interested, please send your resume to WeChat zdx3578 for communication;