IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning

Open code of my published paper: Health-considered energy management strategy for fuel cell hybrid electric vehicle based on improved soft actor critic algorithm adopted with Beta policy

Open code of my published paper: Ecological Driving Framework of Hybrid Electric Vehicle Based on Heterogeneous Multi-Agent Deep Reinforcement Learning

[ECC 2022] Codebase for the paper titled "Learning Eco-Driving Strategies at Signalized Intersections".

This repository contains codes and datasets in correspondence to my bachelor thesis for computer science at Vrije Universiteit Amsterdam.

This is an app that demonstrates using of the Telematics SDK and walks you through the integration. The SDK tracks user location and driving behavior such as speeding, cornering, braking, distracted driving, and other parameters.

Open code of my published paper: Eco-Driving Framework for Hybrid Electric Vehicles in Multi-Lane Scenarios by Using Deep Reinforcement Learning Methods

Greenwave project website.