[Paper]  IEEE IV 2021, IEEE ITSC 2021, JSAE 2021

1. Model in the Loop Testing and Validation of Embedded Autonomous Driving Algorithms, IEEE IV21: A testing framework combining high fidelity models of vehicle, traffic and physics-based sensors. We in particular prioritize embedded development, focusing on high performance algorithms and low latency communication. Advantage is an efficient development process when transforming from virtual to physical testing.

1. Enhancing Comfort in Autonomous Driving Development, JSAE Annual Spring Congress 2021: A summary of our progress works to improve AV comfort, including: imitation learning, inverse reinforcement learning, driving style classification and learning via co-teaching, comfort-based scenario generation, full vehicle testing and validation platform.

2. Safe Imitation Learning on Real-Life Highway Data, IEEE ITSC 2021: A safe learning approach for autonomous vehicle driving, with attention on specific and real-life human driving data (from Netherlands to Belgium).

If you are interested, please check .pdf files in my RG here: https://lnkd.in/dMvT8rA

These works are collaboration of various colleagues from Siemens DI and ABU Mentor Graphics: Anoosh Anjaneya Hegde, Flavia Sofia Acerbo, Ludovico Ruga, Theo Geluk, Mohsen Alirezaei, Dennis Bruggner, Dhiraj Gulati, Herman Van der Auweraer and others…