Prepere the apendix to the paper: Computational Offloading for autonomous...

Prepere the apendix to the paper: Computational Offloading for autonomous systems: Real-World Experiments and Modeling

README.md

 # Autonomous Driving
 
-## Paper Computational Offloading for autonomous systems: Real-World Experiments and Modeling
+## Paper: Computational Offloading for autonomous systems: Real-World Experiments and Modeling
 Main branch to indruce the codes and datasets is Paper. And codes for measurment are in the folder /measurement_autonomous_driving/src/measurement. RRT* and Road sign recognition is implemented in main branch for both local and MEC server processing. 
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 Dataset for YOLOv3: https://campuscvut-my.sharepoint.com/:f:/r/personal/danekja5_cvut_cz/Documents/PaperApendix?csf=1&web=1&e=ebepJz folder: own_data 
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 Dataset for cosutme neural network: https://benchmark.ini.rub.de/gtsrb_news.html
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 Dataset for test road sign recognitio: https://campuscvut-my.sharepoint.com/:f:/r/personal/danekja5_cvut_cz/Documents/PaperApendix?csf=1&web=1&e=ebepJz folder: dataset_test_paper
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 Dataset for path planning: Branch paper in /measurement_autonomous_driving/src/measurement
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 Trained weights for YOLOv3 and costume neural networ: https://campuscvut-my.sharepoint.com/:f:/r/personal/danekja5_cvut_cz/Documents/PaperApendix?csf=1&web=1&e=ebepJz folders: 832ownbest.pth and traffic_classifier.keras
 Components of AV are detailed [here](documentation/components_of_AV.pdf).