Popular GitHub Repositories for Truck Platooning

Euro Truck Simulator 2 autonomous driving solution

Self-Driving Truck in Euro Truck Simulator 2, trained via Reinforcement Learning

This project aims to count every vehicle (motorcycle, bus, car, cycle, truck, train) detected in the input video using YOLOv3 object-detection algorithm.

Control system design for platoon of autonomous vehicles

Autonomous Driving project for Euro Truck Simulator 2 Running on Real World

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 followers will follow each other using Goal to Goal controller.

A Platooning demonstrator consisting of a convoy of 1/10 scale RC cars. Deep Learning and Computer Vision concepts utilized and system implemented on the Jetson Nano.

Code for my Master's thesis, game theory for adversarial autonomous vehicle platooning scenarios

Autonomous Driving for Euro Truck Simulator 2

Heterogeneous GNN-based multi-agent reinforcement learning for coordinated platooning and traffic signal control using Ray RLlib and SUMO

This repository is to release A simulation platform for truck platooning evaluation in an interactive traffic environment

Bachelor's Thesis about self driving trucks done at Chalmers University of Technology in 2017

Using Blender and Python to generate synthetic data for training an 8-class YOLOv5 detector in a highway driving scenario (Sedan, SUV, Van, Truck, Bus, Warning Sign, Speed Limit Sign, Speed Cam Sign).

The dataset consists of data collected from heavy Scania trucks in everyday usage. The system in focus is the Air Pressure system (APS) which generates pressurised air that is utilized in various functions in a truck, such as braking and gear changes. The dataset’s positive class consists of component failures for a specific component of the APS system. The negative class consists of trucks with failures for components not related to the APS. So, I created a model where It can able to detect whether the APS is going to fail or Not.

In this project, the system in focus is the Air Pressure system (APS) which generates pressurized air that are utilized in various functions in a truck, such as braking and gear changes. The datasets positive class corresponds to component failures for a specific component of the APS system.

Predicting Food Truck Locations Using Snowpark ML and XGBoost

Self Driving truck using ROS Kinetic , Supervised Deep Learning, OpenCv and SLAM

Modern machine learning project development - This end-to-end project implementation provides the real-time delay updates to logistic companies. It uses MLflow for model tracking and management, Hopsworks Feature Store for storing and managing the dataset, and Streamlit for building an interactive web application to predict truck delays.

Simulation model for tractor-trailer system (both tank trailer and contrainer trailer) in carla platform. The vechicle including 1 truck and 2 trailers can both reflect LiDAR ray casted by Carla's self defined sensors. The repo also contains the calibration board for camera and lidar.

An automated supply chain incident processing system that analyzes financial impacts of truck breakdowns, makes optimal routing decisions, and coordinates external execution through AI agents and workflow orchestration.