Industry in Turmoil – One of the most profound changes the auto industry is grappling with is the emergence of connected and autonomous cars, says Joe Barkai. Automakers have been keeping a steady pace of technology innovation and manufacturing excellence for over a century. Since the breakthrough of the highly efficient assembly line, auto manufacturers were in the forefront of engineering innovation, designing and building cars that were successively better, safer and cleaner. For many decades, the industry has been at the centre of the US economic development, and, to many, an industrial and social icon.

But over the past decade or so, the iconic and seemingly stable industry has been in turmoil. It has been undergoing massive changes caused by the cumulative effect of rapid technology innovation, disruptive business models, aggressive new competitors, and an emerging supply chain ecosystem whose full impact is not fully comprehended yet. One of the most profound changes the auto industry is grappling with is the emergence of connected and autonomous cars. Most industry visionaries and practitioners portray a bold vision of a future in which cars, occupants, and cloud-based information and control systems communicate and exchange information in the omnipresent Internet of Things cloud. Cars are becoming part of the Internet, or, in today’s parlance, they are yet additional, if unconventional, “things” in the Internet of Things (IoT).

Connected to your mobile device, a digital infrastructure, and a wealth of streamed cloud-based content and services, your car isn’t a just car anymore. It is an information centre; it’s your wallet; it’s your office on wheels. Cars are no longer self-contained independent systems designed to insulate and shelter you from your surroundings; quite the opposite. Cars in the future will be constituents of a broad network and a conduit of a continuous torrent of information and services delivered by a fast-growing vibrant ecosystem.


More than any technology revolution underway today, the connected car, and, eventually, autonomous driverless cars, pose unprecedented challenges for automotive designers and engineers.

Of course, embedded software in car isn’t new and has been used in cars for several decades. The first production car to incorporate embedded software was the 1977 General Motors Oldsmobile Toronado, that employed an electronic control unit (ECU) to control spark timing, and starting continuous innovation to fuel economy and reduce emissions.

Developing simple control software in the earlier days of software-controlled automotive systems wasn’t a very onerous task, and informal methods and basic software skills were quite adequate. As appetite for more complex software-controlled systems increased, designers managed to get by using a rudimentary software engineering environment built around open- source configuration management and bug tracking tools, and augmented by the unavoidable plethora of spreadsheets and lengthy informal email conversations.

Nowadays, software-driven functionality is expanding quickly from controlling mechanical subsystems to serving a central role in defining customer experience and driving product differentiation. Key functions and user experience features are implemented in software, enabling unique, finely-tuned features to satisfy different consumer segments and diverse tastes.

The sheer volume, number of variations, and unprecedented complexity of embedded software is straining the organic ability of OEMs and suppliers to reskill and ramp up critical embedded software development capabilities.

The obstacle isn’t in writing the software code itself. As companies adopt agile development methods and use modelling tools that generate quality code at a click of a mouse, much of the coding has become automated. Rather, managing the seemingly infinite number of features and feature-combinations, and validating the design against an ever-growing volume of complex and interdependent requirements is a monumental development burden, stressing the traditional product development methods and tools that have not kept pace with the increased complexity.

And the gap in between the pace of innovation and increase in product complexity, and the capabilities of available design and validation tools continues to widen.


As autonomous driving capabilities continue to progress towards higher level of autonomous operation, the role of electronic control systems that host advanced software-driven functionality, especially for advanced safety systems (ADAS) and autonomously-driven cars, is expanding quickly. The need to incorporate additional sensors and increase the density of electronic controllers, while struggling with physical space, weight, power consumption, and costs is driving innovation and experimentation with new controller architectures and renewed motivation to move to 48V power rails.

As designers of semi- and fully-autonomous vehicles systems rely increasingly on nondeterministic, artificial intelligence-based control systems, traditional prototyping and physical testing are no longer feasible, nor are they sufficient. As the number of theoretical test scenarios is exploding beyond control, simulation and test tools must evolve from physics based modelling and analysis to behaviour modelling, allowing new vehicle designs to be “driven” millions of virtual miles before a system can be validated and signed off.


Siemens PLM has a long history of providing product development and engineering software to the auto industry and industries that share similar lifecycle characteristics, such as heavy equipment and industrial machinery. The company recognises the transformation its customers are undergoing requires new tools and methods to support the new challenges in product development and lifecycle management.

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