The automotive industry is in the middle of a complex, expensive and revolutionary path to software-defined vehicles. Every company will need to develop, buy and manage a lot of software to remain leaders in this software-centric generation. This column will provide an overview of the factors and complexities that impact the journey to the software-defined vehicle era.
The first step is to understand that the auto industry has features that increase software complexity compared to most other industries.
The definition of “software-defined” means that a large majority of car functionality is now implemented by software applications that run on required processors, memory and sensors. Additionally, most of the functionality is defined by how well the human-machine interface is implemented in software.
There are numerous choices and questions when it comes to what paths to take regarding existing, emerging and new potential technologies. Additionally, regulations on software lifetime management have been introduced and more are expected; especially for autonomous driving software.
With all vehicles becoming connected, over-the-air software updates and cybersecurity software become a must. These technologies add complexity while also providing tremendous opportunities and advantages for auto manufacturers and vehicle users.
Auto industry software complexities
The auto industry has multiple characteristics that complicate the development, maintenance and management of its rapidly growing software portfolios. The next table summarizes these features with information on how they affect automotive software platforms, ultimately increasing the complexities of reaching a software-defined vehicle era.
The lifetime of auto industry products is among the longest of any industry — at least, among volume products counted in the tens of millions of sales units per year. The auto software complexity and program size have increased dramatically and will continue to do so another decade or more. The sum of the numerous auto software platforms exceed 100 million lines of code in many vehicles today and may double or triple in the coming decade.
These factors will challenge OEMs and their suppliers in terms of software development, maintenance, bug fixes, recalls and updates across 10 to 15 years of customer use. This is complicated enough for one specific auto model that is usually updated every 3-4 years and this may happen from 2-4 times. The complexity increases tremendously when major OEMs have 10-20 models with some regional variations that are going through these model update cycles.
The transition from internal combustion engine vehicles (ICEVs) to battery electric vehicles (BEVs) adds another dimension to car software renewal and management. Developing new BEV models provides opportunities to start with a new, clean sheet of software instead of relying on legacy software platforms that may be antiquated and should be replaced with state-of-the-art software architectures.
Legacy software systems
The large amount of required legacy system expertise and maintenance demands for up to a decade is a challenge all auto OEMs and their suppliers face. Most of these legacy systems must be superseded by modern software platforms as new vehicle models are introduced.
This requires a lot of re-training and new expertise that will take time and money to acquire and develop. These constraints are significantly slowing down the switchover to software-defined vehicles for all OEMs and their suppliers.
Connected network of functions
For the past thirty years, auto electronics functions have grown into connected networks of functionality. Most new functions were an ECU with a microprocessor and relevant sensor as well as a growing amount of software over time. Many functions needed to communicate with other functions, and electronics buses were added. The networks are currently dominated by the CAN bus, but are expected to move to Ethernet-based networks at a growing rate.
As telematics and other connected car functions increased, the need for cybersecurity became a requirement and OTA software updates emerged as valuable functionality. By 2020, a high-end vehicle had over 50 ECUs connected via a multitude of interconnected buses. Further expanding this structure was not viable and the domain ECU became a better solution.
Domain ECU era
A domain ECU combines multiple small ECUs into a single ECU with a more powerful processor, larger memory and more capable software platforms and applications. Legacy systems are being replaced by domain ECUs and software-defined architectures. For some OEMs, this transition could take as long as a decade and most OEMs only started a few years ago.
The growth and capability of cloud-based software development platforms are speeding up creation of new software architectures and expanding their features and capabilities. The cloud-based approach is also adding software-as-a-service (SaaS) functionality at a rapid rate.
Many auto applications are classified as real-time software. This means that there are specific time limits to complete the software codes. Otherwise, the software that controls car operations, such as the engine, brakes, steering and acceleration, may fail and create safety issues. ADAS and AV functions are also examples of real-time software that is growing in importance.
The extra timing restrictions makes the development of real-time software more complex and costly compared to regular software.
Functional and AV safety
Functional safety is now a core feature for all real-time software platforms and is regulated by the ISO 26262 standard. Many software platforms must pass functional safety testing to be legally used in modern vehicles.
AV functions are next on this path, with new standards specifying how AV technology must be designed, in effect extending functional safety to automated driving systems. The key standards are ISO 21448, UL 4600 and IEEE P2851.
Key software legislation is focused on cybersecurity and OTA software update management. The UNECE WP.29 legislation passed in Europe in 2020 and regulates both cybersecurity and OTA software updates.
AI is growing in importance in the auto industry and will have a profound impact in the next decade. Specifically, AI tech advances are needed in the next decade and AI black box issues must be solved. The AV software driver depends on AI technology innovation. We are also counting on AI to improve software coding with fewer bugs, better efficiency and lower costs.
One of the more difficult issues to emerge is AV road legislation that will greatly impact future AV software. New laws, infrastructure and AV safety tracking systems are needed. These solutions often include difficult and controversial societal and political decisions on initial AV safety levels versus historical human driver safety. Multiple countries have started passing AV laws and much more is on the way.
Content consumption in the car has grown dramatically in the last decade due to mobile device proliferation, with smartphones leading the parade. Auto OEMs attempted to develop their own software platforms to connect to smartphones but failed as software platforms from Apple and Google are now dominant.
Content usage rules vary between drivers and passengers due to driving distraction issues that are major causes of car crashes. AVs hold the promise of increased content consumption when available, which will expand the market opportunities for content software platforms in the auto industry.
Auto OEM software platform phases
It is clear that the auto OEMs have a lot on their plates to become successful players in the software-defined vehicle era. The next figure is a simple block diagram summary of what OEMs must do over the next 15 years to become viable competitors, with two main stages: software developments in green blocks and the customers’ use phase of the software platforms in red blocks. The development phase for most software platforms takes 1-3 years, while the software platform usage stage is much longer at 10-15 years.
The auto industry is already levering software development platforms originally created for IT and other industries. The Integrated Development Environment platforms such as Eclipse are heavily used to create auto software platforms. Cloud platforms focused on software development have also grown strongly in recent years, with AWS and Microsoft Azure as the leaders.
A new approach to developing software known as “no-code” or “low-code” has emerged in the IT industry. It is based on creating higher-level developmental platforms that simplifies the process of creating software code. At the top of this trend is AI-based code generation. This trend is expected to see growing impact on automotive software development.
Another approach is to tailor software development to a specific application segment. Apex.AI, for example, focuses on functional safety software platforms.
All these software development platforms are used to create a large variety of automotive software platforms as shown in the above figure. Each vehicle family will have a portfolio of software platforms as shown in the two green boxes labelled Vehicle Family #1 and #N. This implies there are several additional vehicle families.
The more software platforms that can be shared and re-used across models and generations, the better the economics of the auto software business model becomes. In the past, this was a low priority on many auto OEMs’ strategy list. Now it is required, and all the auto OEMs are focusing on leveraging software platforms as much as they can.
In the above figure, the red blocks show the software platform use phase by vehicle customers with similar labels of Vehicle Family #1 and #N. The top red block shows the cloud-based platforms required to manage operations, updates and other activities the OEMs will need for a profitable software business.
The figure also lists the typical sales range of vehicle family platforms with high volume in the range of 0.5-2 million units per year. Low volume platforms are in the 50K to 150K yearly sales range.
There are many more details needed that go beyond the scope of this short article. Future perspectives and analysis may be worthwhile topics.
The auto industry is on a path to provide software-defined vehicles that will greatly improve functionalities that will continue to expand during their lifetimes. To get there is a challenge that the OEMs and suppliers are attacking with expanded technologies and new business models. Advancing software development platforms with a better fit to automotive complexities are especially important and are starting to appear.
A combination of buying some software platforms and insourcing other software platforms seems to be a common strategy. Growing use of cloud-based software development platforms is a favorite approach across the board.
Many questions remain on which paths are winning strategies and which OEMs and auto suppliers will remain leaders in the new software-defined vehicle era. How important will the high-tech industry become as their core software competencies become the driving forces of the automotive and transportation industries?
>> This article was originally published on our sister site, EE Times.
|Egil Juliussen has over 35 years’ experience in the high-tech and automotive industries. Most recently he was director of research at the automotive technology group of IHS Markit. His latest research was focused on autonomous vehicles and mobility-as-a-service. He was co-founder of Telematics Research Group, which was acquired by iSuppli (IHS acquired iSuppli in 2010); before that he co-founded Future Computing and Computer Industry Almanac. Previously, Dr. Juliussen was with Texas Instruments where he was a strategic and product planner for microprocessors and PCs. He is the author of over 700 papers, reports and conference presentations. He received B.S., M.S., and Ph.D. degrees in electrical engineering from Purdue University, and is a member of SAE and IEEE.|
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