Data underlying the project: Cooperation of Autonomous Vehicles in Mixed Traffic (SCoop)

This data includes technical notes and results from my work at TU Delft.<br>I have attached a zipped folder "projects" which includes all the different projects/publications I worked on:<br>COLREGs-aware Trajectory Optimization for Autonomous Surface VesselsModel Predictive Trajectory Optimization for Autonomous Vessels Considering Traffic RulesActive Thruster Fault Diagnosis for an Overactuated Autonomous Surface VesselSet-Membership Estimation for Fault Diagnosis of Nonlinear Systems<br>For each project/publication, the folder includes the content of the work (text, notes, figures, plots, etc.). These publications align with the goal of our project (SCoop): The goal of the SCoop project is to design a cooperation framework to allow autonomous vehicles to safely navigate in mixed traffic even in the presence of faults. The results are generated from simulation experiments using ROS (Robot Operating System) and were collected in .rosbag files (to be further processed and generate plots).<br>The code that generated the data is available on Github: https://github.com/ttsolakis

本数据集包含我在代尔夫特理工大学（TU Delft）开展研究工作期间生成的技术笔记与实验成果。
我已附入名为"projects"的压缩文件夹，其中收纳了我参与的全部项目与出版物相关内容：
1. 适配《国际海上避碰规则》（COLREGs）的自主水面艇轨迹优化
2. 考虑交通规则的自主船舶模型预测轨迹优化
3. 超驱动自主水面艇的主动推进器故障诊断
4. 非线性系统故障诊断的集合成员估计

针对每个项目或出版物，该文件夹均包含对应研究的完整内容，涵盖文本、笔记、图表、绘图等资料。上述研究均契合我们的SCoop项目目标：SCoop项目旨在构建一套协作框架，使得自主车辆即便在存在故障的场景下，也能在混合交通环境中安全航行。

本数据集的实验结果均基于机器人操作系统（ROS, Robot Operating System）开展的仿真实验生成，并以.rosbag文件格式存储，可用于后续处理与绘图生成。
生成本数据集的代码已托管至GitHub平台，地址为：https://github.com/ttsolakis