Popular GitHub Repositories for Electric Vehicles

User can set up destination for any agent to navigate on Google Map and learn the best route for the agent based on its current condition and the traffic. Our result is 10% less energy consumption than the route provided by Google map

Chargym simulates the operation of an electric vehicle charging station (EVCS) considering random EV arrivals and departures within a day. This is a generalised environment for charging/discharging EVs under various disturbances (weather conditions, pricing models, stochastic arrival-departure EV times and stochastic Battery State of Charge (BOC) at arrival). This is an open source OpenAI Gym environment for the implementation of Reinforcement Learning (RL), Rule-based approaches (RB) and Intelligent Control (IC).

The official implementation of "Electric Vehicle Routing for Emergency Power Supply with Deep Reinforcement Learning" (AAMAS 2024, extended abstract).

Automate and evaluate software test scenarios for electric vehicle software using the LLMs.

The EV Smart Charging Bot is a Telegram-based assistant that helps EV owners find the most cost-effective and eco-friendly charging times by analyzing real-time electricity prices and emissions. It leverages machine learning and natural language processing for personalized, intelligent recommendations.

Scene understanding is a vital aspect of safe and effective autonomous driving. And with the increase of high-quality datasets in recent years, the models have sufficient data to train on. However, the underlying models are important factors in determining the overall effect