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Automated driving has been expected for decades. The first systems, which at least partially automate the vehicle, have been installed in higher priced vehicles for several years. In the near future, however, many more competencies are to be transferred to the systems and the vehicle will thus be fully automated. Such systems receive their data from various sensor systems such as Light Detection And Ranging (LiDAR). Therefore, it is essential that this information is transmitted correctly and reliably to the environmental perception system. In order to ensure this, redundancy of sensors is a key factor in addition to diversity. For example, multiple, independently controlled MEMS-based LiDAR systems can be operated synchronously. This requires the selection of a Master system which can be reliably followed by all Slave systems. In this publication, an architecture for MEMS-based Micro-Scanning LiDAR systems is proposed to determine the appropriate system as Master. The architecture has been implemented in an FPGA prototyping platform to demonstrate its feasibility and evaluate its performance.
|Title of host publication||32nd IEEE Intelligent Vehicles Symposium, IV 2021|
|Number of pages||7|
|Publication status||Published - 11 Jul 2021|
|Event||32nd IEEE Intelligent Vehicles Symposium: IV21 - Virtuell, Austria|
Duration: 11 Jul 2021 → 17 Jul 2021
|Name||IEEE Intelligent Vehicles Symposium, Proceedings|
|Conference||32nd IEEE Intelligent Vehicles Symposium|
|Period||11/07/21 → 17/07/21|
ASJC Scopus subject areas
- Computer Science Applications
- Automotive Engineering
- Modelling and Simulation
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- 1 Talk at conference or symposium