Project with the task of integrating and maintaining the code base for the next generation of series models, especially (partial) autonomous driving.
Trajectories prediction and strategy. Its aim is to increase safety and drive more comfortably in the future of autonomous vehicles.
Teleoperated driving closes the gap between today's human drivers and the deployment of fully autonomous vehicles driving on public roads.
Maps reconstruction based on high precision laser scanners, GPS and Inertial Navigation Systems and our efficient SLAM+ algorithm.
Accurate and reliable positioning is one of the key drivers for autonomous driving, enabling innovative on-board functionalities and services.
Migrating autonomous vehicles from a prototype to an industrial product is mainly a safety and reliability challenge. Here we start from sensor data.
Development of on-board technologies, in use for Advanced Driver Assistance Systems, to guarantee continuous product development.
A car used to be the ultimate symbol of freedom and independence but increasingly consumers view ownership as an expense and a burden.
Autonomous driving cannot leave traffic control out of consideration for its quick and pervasive deployment. Some interesting challenges here!
This research project combines the integrated use of vehicle electronics, mobile devices, navigation systems, tablet computers and smartphones.
Proof of concept implementation, to demonstrate the usage of vehicles as a mobile sensors to perform comprehensive and detailed traffic monitoring.
Latencies of a few tens of microseconds and throughput of tens of thousands of transactions per second make high demands on software development.
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