Elevating cluster software development with QNX Hypervisor on AWS

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Digital cockpit systems are the primary “vehicle to user” interface of a Software-Defined Vehicle (SDV) which include digital instrument clusters that have sophisticated graphics needs as well as safety-critical requirements. For instance, vehicle state information, such as vehicle malfunction warnings, gear position, and advanced driver assistance state are among the features that must be available to drivers at all times to help ensure road safety. According to a report from Boston Consulting Group (BCG), “The emergence of SDVs will create over $650 billion in value for the auto industry by 2030, making up 15% to 20% of automotive value.” This highlights the massive opportunity for automakers who will have to cultivate SDV capabilities to manage technical complexity via cross tier development, connection to regional and global supply bases, and efficiently integrate platforms.

To help unlock this opportunity and expedite the development of digital instrument cluster software, automotive Original Equipment Manufacturers (OEMs) and their suppliers should be able to build and test software without the dependence on physical hardware systems. Heavy dependency on specialized hardware target systems, that are often expensive and scarce, has been a hurdle for OEMs and has kept them from launching new vehicle features rapidly. BlackBerry QNX Hypervisor helps solve this challenge by reducing an OEM’s dependence on hardware and enables OEMs in launching cloud targets with binary parity. The QNX Hypervisor is a foundational component designed to help establish stability and integrity of mixed criticality systems and safety functions. In this blog post, we delve into how the QNX Hypervisor technology, together with Amazon Web Services (AWS), can help enhance the development and testing of such a consolidated digital instrument cluster domain software. We will discuss how decoupling software development from dedicated hardware targets can increase software development efficiency.