liyan2015/SUMO-RL-MobiCharger
OpenAI-gym-like Reinforcement Learning environment for Dispatching of Mobile Chargers with SUMO. Compatible with Gym and popular RL libraries such as stable-baselines3.
This project helps traffic engineers and urban planners simulate and optimize the dispatching of mobile charging vehicles for electric cars in city networks. It takes in real-world traffic scenarios and EV charging requests to produce optimized routes and actions for mobile chargers, aiming to efficiently recharge electric vehicles on the go. The end-users are researchers or practitioners focused on urban mobility and sustainable transportation solutions.
No commits in the last 6 months.
Use this if you need to simulate and develop strategies for dynamically dispatching mobile chargers to electric vehicles within a city-scale road network using the SUMO traffic simulator.
Not ideal if you are looking for a pre-built, ready-to-deploy solution for real-time mobile charger dispatching without any development or simulation work.
Stars
15
Forks
—
Language
Python
License
MIT
Category
Last pushed
Mar 16, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/liyan2015/SUMO-RL-MobiCharger"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
DLR-RM/stable-baselines3
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
google-deepmind/dm_control
Google DeepMind's software stack for physics-based simulation and Reinforcement Learning...
Denys88/rl_games
RL implementations
pytorch/rl
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
yandexdataschool/Practical_RL
A course in reinforcement learning in the wild