Complex driving operations are realized by powerful electronic control units (ECUs). These ECUs process huge quantities of data and, on this basis, compute the correct driving strategy. To ensure that complicated driving strategies can be developed in an efficient way, the development of software functions is shifted to the lab. Wherever possible, virtualization replaces experimentation based on real hardware. However, this approach requires that models are properly validated based on real environment data. This in turn demands the use of reliable, flexible tools for efficient data acquisition as well as the ability to access such data via the cloud. A modular, scalable approach provides developers the access to measurement data at every phase of vehicle development and enables the integration of high-performance, in-vehicle data acquisition solutions. Seamless integration of data acquisition solutions from the prototype phase to the post-SOP phase helps deliver fast and cost-efficient development processes. Comprehensive data acquisition from the lab phase through to the production vehicle provides function developers with the ability to validate the highly complex functions of automated driving in such a way that automated systems will one day be able to replace human driving.
Session:
Data Science & AI
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| 13:40 - 14:10