Simon Fürst | BMW Group

Principal Expert Autonomous Driving Technologies

Simon Fürst studied Aerospace Engineering at the Technical University of Munich. From 1993 till 2001 he was a research assistant at the department of System Dynamics and Flight Mechanics at the University of the Federal Armed Forces in Munich. His research area was on onboard autonomous, vision-based systems for navigation and landing of airplanes and helicopters as well as for autonomous vehicles.

From 2001 till 2002 he worked for IABG in Ottobrunn as a project leader and consultant for the qualification of the high-risk avionics software in the tiger helicopter and the Eurofighter Typhoon.

Since 2003 he is with BMW. From 2005 till 2009 he was an expert and project leader in ISO creating the automotive safety standard ISO 26262. From 2006-2017 he was in AUTOSAR in many major roles of this 200+ companies non-commercial industry standardization organization. During that period has was two times spokesperson of AUTOSAR. In parallel he was General Manager at BMW being responsible for the series roll-out of the AUTOSAR standard into all BMW vehicles. Since April 2017 he was General Manager in the division of Autonomous Driving and Driver Assistance. There he was responsible for machine learning, reasoning and knowledge representation and line manager for agile development teams. In October 2019 he was appointed as principal expert for automated driving technologies.

13:30 - 14:10

Thursday, November 19

Software Architectures for Automated Driving


Currently numerous OEMs are working on SAE level 3 “Highway Pilot Systems” to be released in the next vehicle generations. This new customer functionality will become the high-end feature of ADAS that extend existing SAE level 1 to 2 features. A scalable approach for system, ECU, sensor and software architecture is required so that features of higher SAE levels can be added on top while re-using already existing features. This requires on the one hand side an extendable sensor setup with additional sensors complementing the entry-level sensor setup. On the other hand, scalable SoC architectures must be used to enable re-use of software assets from entry level SoCs up to high-end SoCs. But this scalable approach places high demands on a scalable software architecture as well as on safety. Additionally, data driven development places new demands on the software architecture for L3 systems. It is understood that such software systems will be continuously enhanced by data gained from testing while in the development phase and from more data collected by the customer fleet. This requires seamless toolchains with very high automation and efficient regression testing to deliver software updates whenever needed.