The autonomous driving software applications are increasingly in demand. Robot taxis, autonomous buses, last mile transportation, delivery robots, and many more domain specific applications share a common core software stack. Developing or even adapting existing autonomous software to a certain domain is a huge task even if the change is very simple. One small change can break the system or even change the system's expected behavior. Extensive testing is essential to guarantee that the system works as expected. Evaluating a software stack as complex as autonomous driving systems is challenging. Different modules require different ways of evaluation. The danger of testing safety critical situations. Time and resources needed for evaluating every change in the system.
The goal of this workshop is to try to cover the problem of autonomous driving software stack assessment, especially the use of scenario based evaluation methods.
Professor, Institute of Innovation for Future Society, Graduate School of Informatics, Presidential Advisor, Nagoya University
Professor, Faculty of Electrical Engineering, HSA_ired, Augsburg University of applied sciences.
Welcome, and plenary speeches from Professor Takeda and Professor Carsten
Introduction, Scenario Based Evaluation for Autonomous Driving Software Systems. Hatem Darweesh
How can smart infrastructure contribute to the future of automated driving. Mathias Pechinger
Open-Source Testing Framework for Path Planning and Control Algorithms in Autonomous Driving. Armin Straller
Tutorials, Running Standard Scenarios with CARLA Simulator. Hatem Darweesh
Real-to-Synthetic: Generate Simulator-Ready Scenes from Real-world Data. Tian Yafu
Q&A
Master Student, Master candidate, Faculty of Electrical Engineering, Augsburg University of Applied Sciences
PhD candidate, Faculty of Electrical Engineering, Augsburg University of Applied Sciences
Behavior Signal Processing Laboratory, Graduate School of Informatics, Nagoya University, Japan.
