AI platform for autonomous cars reconfigures on the fly

December 04, 2019 //By Christoph Hammerschmidt
AI platform for autonomous cars reconfigures on the fly
Together with partners, the Fraunhofer Institute for Integrated Circuits IIS is developing a compute platform that uses artificial intelligence to precisely capture the vehicle environment. The project is intended to make an essential contribution to the development of urgently needed technology components that make autonomous driving safe and reliable. The challenge: The platform needs to be able to react on the fly on the failure of a sensor.

In autonomous driving, data from laser, camera and radar sensors in the car must be reliably and quickly combined and processed. Through this sensor data fusion and intelligent object recognition, the vehicle always has a precise image of the real traffic conditions, can locate itself in this environment and make the right decision in any driving situation on the basis of this information. The data to be processed for the environment recording is so complex that artificial intelligence methods are required to ensure a high level of traffic safety.

Fraunhofer IIS and its partners in the KI-FLEX project are developing a high-performance hardware platform and the associated software framework for this purpose. The algorithms used for sensor signal processing and sensor data fusion are largely based on neural networks and allow the vehicle position and environment to be recorded quickly and accurately.

The significance and usability of individual sensors varies depending on the traffic situation, weather and lighting conditions. In order to do justice to this, the platform is designed as software-programmable and reconfigurable hardware. This means that the algorithms used for sensor evaluation can be exchanged during the journey if conditions change. This allows the car to react flexibly to impairments or even the failure of individual sensors. In addition, the project team will develop suitable methods and tools to ensure the functional safety of the AI algorithms used and their interaction even during reconfiguration while driving. For the efficient execution of all algorithms and reconfigurations, the computing resources of the hardware platform are dynamically allocated according to the load.

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