Sven Jeroschewski

Open Source Software Engineer

Talk Title

Vehicle Abstraction with Open Source Technologies

Room

Nest

Date

04.07.2024

Time

16:20 > 40 min

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Many use cases within Android Automotive rely on data originating from the various deeply embedded systems spread across the vehicle. Accessing this data can be very complex due to different data semantics and structures or various communication protocols. From the perspective of an Android application developer, this data is thus often essentially „hidden“ in the deeply embedded layers of the vehicle. A solution to this challenge, which also enables more portability of the applications, is to introduce an abstraction layer with clear APIs and a widespread data model. 

Eclipse KUKSA is an open-source project that enables read and write access to Vehicle Signals using a simple and secure API. KUKSA utilizes the Vehicle Signal Specification (VSS) as the data model, which provides an abstract view of a vehicle, making it an ideal base for SDV systems. VSS is the result of the open collaboration between different OEMs and suppliers like BMW or Bosch and is available as open-source. For instance, the Automotive Grade Linux (AGL) project has integrated KUKSA and VSS into its releases. During this talk, we give an overview of what KUKSA can do and where it fits into the Android Automotive ecosystem. We further touch on the most recent developments, like our Kotlin SDK for integrating Android applications with Kuksa-enabled systems, and give an outlook of the midterm roadmap.

Speaker Bio

Sven Erik Jeroschewski is a Software Engineer with Bosch Digital. In collaboration with ETAS, he applies and extends open-source technologies in a technically sound and compliant manner to domains such as automotive or industry. In that process, he actively works within the automotive open-source ecosystem and acts as a committer for Eclipse Kuksa. Sven studied Computer Engineering at the TU Berlin and the University of Oklahoma, focusing on networked embedded systems and connected driving.

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