Inem - Institute for sustainable energy technology ans mobility Marcel Voßhans, B.Eng., M.Sc.

• Technical Project Leader AMEISE
• Team Projekt RAFT

• Perceptional Algorithms
• Infrastructural Integration AD
• Roboter Operating System (ROS)
• Sensory (LiDAR, Camera)
• Autonomous Driving & Simulation
• Artificial Intelligence
• Automotive: Functional Safety

Education

2015- 2018

Electrical Engineering and Information Technology, B. Eng. (Hochschule Hannover)

2018- 2020

Applied Computer Science: Autonomous Systems, M.Sc. (Hochschule Esslingen)

Experiences

2019

Daimler AG (Electrical Power Steering Development, SbW)

2018

Conntinental Teves AG (Testing Rig Automation & Development)

2017

Semester abroad in Sweden, Växjö

2016

Summer School in China as a Tutor, Hangzhou

2015- 2017

Assistant: Center for teaching and consulting, E-Learning concepts (Hochschule Hannover)

Tutor: Faculty of Electrical Engineering, Math + Physics (Hs Hannover)

• M. Voßhans, P. Holzner, R. Wörner, T. Faul, and T. Heisig, “Fahrzeugklassifizierung mittels Stereokamerasystem unter Einsatz von Deep Learning,” in Neue Dimensionen der Mobilität, H. Proff, Ed., Wiesbaden: Springer Fachmedien Wiesbaden, 2020, pp. 489–504.
• Voßhans, Marcel, Hu, Di, Tan, Mingkun, Heisig, Tobias, Schneider, Simon, Hedderich, David, … Wörner, Ralf. (2020). Requirements for battery electric and automated passenger transport with focus on environment detection from vehicle and infrastructure perspectives. Presented at the EVS33, Zenodo. http://doi.org/10.5281/zenodo.4026798
• Vosshans M. et al. (2021) Reliability of Conventional Infrastructure in Context of Automated Driving illustrated by the SLAM Problem. In: Bargende M., Reuss HC., Wagner A. (eds) 21. Internationales Stuttgarter Symposium. Proceedings. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-33466-6_16

ORCID: 0000-0001-8882-3527