Outside of individual autonomous vehicles, there is a need for a broader view of collaborative engineering and operations. The autonomous vehicle (AV) will rely on city and other AV sensing feedback to provide safer, efficient route guidance and automated driving. Systems Engineering (SE) can help AV development and operations by considering a broader context, including the vehicles' operational environment. At the same time, model-based systems engineering (MBSE) supports increasing product and systems complexity driven by more sensors, actuators, and computing electronics. Lastly, accurate digital twins improve virtual and physical correlations to deliver improved and faster solutions for AV development and validations.
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Enable a system of systems framework needed for AV development and operations
An architectural framework for situational awareness, e.g., obstacle detection and avoidance, is needed so AVs can assist each other. This requires coordination beyond a vehicle in a traffic ecosystem requires a blueprint for safety cooperation. Building trust within the operational environment requires an appreciation of system of systems thinking, starting with systems engineering practices applied to the AV during development and the environment in which it operates, even more so as that environment changes. Siemens Autonomous Vehicle Development solutions set broadens SE capabilities to enable a system of systems framework needed for AV development and operations.
Bridge gaps between engineering disciplines with an integrated MBSE approach
From fleet coordination to traffic management, transportation management systems need to connect with today's vehicles to bridge the gap between today's advanced driver-assisted systems and tomorrow's fully autonomous vehicles. This requires an integrated MBSE approach to cover these broader domains and their viewpoints (i.e., contexts) beyond a single vehicle in AV development. System of systems practices are needed to organize multi-disciplinary information, pre-validate complex system assumptions before detailed designs, and include new groups outside of historical vehicle engineering and manufacturing. Siemens integrated MBSE solutions are designed to help their customers bridge gaps between engineering disciplines, improving collaboration and even spanning organizations.
Deliver improved and faster solutions for AV development with Siemens Digital Twins
Vehicle development, verification and validation, and lifecycle support are changing due to the exponential growth of vehicle-related electronics and software. AV development requires considering complex operational scenarios, which can only be done by applying model-based systems engineering principles supported by architectural frameworks to ensure consistency. AV adaptation to its operational environment needs accurate digital twins of their real-world operational environment systems. By leveraging real-world measurements to correlate virtual model-based scenarios using digital twins, assessing complex operational anomalies will make AVs upgrades more reliable and thus earn customer and society trust.
Download this white paper to read why CIMdata forecasts that companies connecting data with learning digital twins will realize significant benefits during AV development and operations—building trust with cities and passengers.