Control system design for platoon of autonomous vehicles

The code for the project Distributed Nonlinear Model Predictive Control (DNMPC) for vehicle platooning

This project includes many aspect and all of them are done by ROS/Gazebo environment and the programming language used is Python.Starting by launching 3 Ackerman vehicles in one Gazebo environment and providing a path planning of lane changing of the leader car, the leader will move according to this path using Fuzzy Logic Control, and the 2 fol…

code for paper: [1] M. Hu, X. Wang, Y. Bian, D. Cao, and H. Wang, “Disturbance Observer-Based Cooperative Control of Vehicle Platoons Subject to Mismatched Disturbance,” IEEE Transactions on Intelligent Vehicles, vol. 8, no. 4, pp. 2748–2758, Apr. 2023.

This project is all about the quest of building a platooning capable robot.

CoOP: V2V-based Cooperative Overtaking for Platoons on Freeways

A small extension of Carla for the validation of vehicle platoon controllers.

MIP model for optimizing charging and platooning schedule of electric freight vehicles.

Projects done during T4AV: Lane Detection, Adaptive Cruise Control and Platooning

Line follower, platooning, sensor fusion with DroidControlSystem and etc.

Robot platooning, sensor fusion of odometry and inertial unit and more ...

The scope of the project is to optimize traffic flow in urban intersections by adopting the platooning system.

Implement platooning for Carrera Digital 132. The car is controlled by an Arduino Nano.

Simulation web app aimed at visualizing and providing graphs for a platooning system with interactive conditions.

ROS-Package containing an API for Car2Car Communication. This repository also contains a Platooning demo that makes use of the API

The goal of this project is to bring most of Event-B and refinement calculus into Python

Dinamically creates platoons on the emergence of a road blocking (signs, accidents, blockage)

A framework for the optimization of simulation parameters.

This repository analyzes driving data recorded with model race cars in a platooning scenario using the STARS framework.

A repo containing the implementation of a Reinforcement Learning approach to optimize vehicle platooning dynamics using Q-learning algorithms. This project aims to reproduce in a small and simplified scale the results achieved by a reference paper.