lexfridman/deeptraffic
DeepTraffic is a deep reinforcement learning competition, part of the MIT Deep Learning series.
DeepTraffic is a competition where you design and test a neural network to control autonomous vehicles on a simulated highway. You input your proposed network code, and the system simulates traffic flow, allowing you to visualize how your vehicle (or multiple vehicles) navigates dense traffic. This is for anyone interested in exploring how AI can optimize traffic flow and improve autonomous vehicle navigation.
1,793 stars. No commits in the last 6 months.
Use this if you want to experiment with designing AI algorithms for autonomous vehicles to improve traffic efficiency in a gamified environment.
Not ideal if you're looking for a tool to implement real-world self-driving car software or analyze existing traffic infrastructure.
Stars
1,793
Forks
280
Language
JavaScript
License
MIT
Category
Last pushed
Aug 01, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/lexfridman/deeptraffic"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Compare
Higher-rated alternatives
ArztSamuel/Applying_EANNs
A 2D Unity simulation in which cars learn to navigate themselves through different courses. The...
idreesshaikh/Autonomous-Driving-in-Carla-using-Deep-Reinforcement-Learning
Deep Reinforcement Learning (PPO) in Autonomous Driving (Carla) [from scratch]
kevinhughes27/TensorKart
self-driving MarioKart with TensorFlow
KimangKhenng/Traffic-SImulation-and-Visualization
Traffic Intersection Simulation Using C++ and Qt
ikergarcia1996/Self-Driving-Car-in-Video-Games
A deep neural network that learns to drive in video games