ご存じの通り、自動車ソフトウェアは業界でホットな話題となっています。モダンな電気自動車会社から伝統的な自動車メーカーまで、誰もがソフトウェアの課題と機会について活発に議論しています。

フォード·モーター社の CEO である Jim Farley 氏は、Fully Charged の最近のインタビューでソフトウェアを適切に開発することの難しさについて語っています。彼は強く主張したのは、「複数のソフトウェアプロバイダーとそれらの間において統合がなされていない」という問題についてです。フォードが電気アーキテクチャの開発を内製化することになったのは、それが理由であると述べています。

Farley 氏は、「伝統的な自動車メーカーにとって、ソフトウェアを適切に開発するのは非常に難しいのです。なぜなら、150 社もの異なる企業によってソフトウェアが作られており、互いに連携していないためです。(中略) 使用するプログラミング言語、ソフトウェアの構造がそれぞれ異なり、コード行数も数百万行に上るので、すべてを把握することすらできません。フォードでは電気アーキテクチャを完全に内製化した背景には、そうした理由があります。しかしその場合、すべてのソフトウェアを自分たちで書く必要があります。ここで問題になるのは、一般的に自動車会社はソフトウェアを書いた経験が一度もない、という事実です。これまでに一度も、です。したがって、当社では自動車を操作するためのソフトウェアを、文字通り初めて書くことになったのです」と述べています。

こうした問題は、フォードだけではなく、テスラも同様に直面しています。Farley 氏は、Twitter のスペースでのインタビューで Elon Musk 氏とソフトウェアに関する対談を行っています。テスラはソフトウェア デファインド ビークル企業においてトップですが、この際、Musk 氏も「自動車のソフトウェアは非常に難しい」と認めています。

ステランティスも例外ではありません。「 は過度に複雑かつ高価になっています。(中略) 起動方法すら誰かに聞かないとわからない車もあります」と、ステランティスの CTO、Ned Curic 氏は Grenoble で開催された CEA-Leti の Innovation Day での講演 で述べています。

シトロエン、フィアット、プジョー、アルファロメオ、オペル、ダッジ、ジープ、ボクスホールのブランドで自動車を製造しているステランティスは、現代の自動車がいかに複雑になっているかをよく認識しています。同講演中、Curic 氏は次のように説明しています。「より少ないリソースでより多くの成果を上げる方法を考え出す必要があります。キャビン内の 250 の機能のうち、(中略) 150 の機能を削りました。車両には 270 個のシリコン デバイスが搭載されていますが、これを 70 個にまで減らしました」

ソフトウェアについて、ここまで深く考えているブランドは他にもあります。Reuters Events の最近のレポートでは、コネクテッド ビークルとソフトウェア デファインド ビークルに一貫して焦点を当てています。会議参加者の約 60% も、この分野に興味があると答えています。

このレポートでは、大手メーカーの多くがソフトウェア開発を社内で行っていることも強調されています。アウディの CEO、Markus Duesmann 氏は、ソフトウェアに関する外部との連携は当面予定していないと説明しています。彼は、「現時点では、開発速度の低下と複雑性の増加を招くことになります。そして当社には、十分な人員と拡張性があります」と語ります。

トヨタの新 CEO 佐藤恒治氏もソフトウェアに注力しています。4 月の発表で、「最新のハードウェアとソフトウェアをつなげることで、クルマとさまざまなソフトウェアが自由につながるようになります。(当社のソフトウェア プラットフォームである) Areneは、こうした進化を支えるプラットフォームとして重要な役割を果たすことになるでしょう。当社は Woven By Toyota とともに、2026 年に向けた次世代 BEV の開発に全力を尽くします」と語っています。

他のブランドも独自のソフトウェア プラットフォームの開発に取り組んでいます。メルセデス·ベンツは、車両の他の部分とつなげ、Google や Nvidia などのテクノロジー企業と連携して構築する新しい MB.OS インフォテインメントシステムの導入を予定しています。メルセデスの CEO、Ola Källenius 氏は、「私たちは、世界で最も魅力的な車を作ることに全力を尽くしています。当社は、自社のオペレーティング システムを自分たちで設計することにしました。チップからクラウドまで、車両のハードウェアおよびソフトウェア コンポーネントに対して完全なアクセスと活用が可能な、独自のアーキテクチャです」と語ります。

AI は実用的な洞察を生み出す

これらの業界リーダーの発言はすべて、メーカーが直面している課題に対処できる解決策が求められていることを示唆しています。AI ベースのツールは、要件からコーディング、継続的インテグレーション、継続的デプロイメント (CI/CD) に至るまで、これらの多くのハードルを克服するのに役立ちます。

自動車メーカーが開発プロセスを加速させ、ソフトアップデートをより早くリリースする方法の 1 つは、Aurora Labs が提供する AI ツールを使用することにあります。これにより、ソフトウェア開発ライフサイクルへのフォーカスとトレースが可能になり、開発からテスト、導入まですべてがスピードアップします。

これらの課題を解決するプロセスには、大きな機会が眠っています。フォード、テスラ、メルセデス·ベンツ、VW、トヨタ、ステランティスなどの業界大手はいずれもこの問題に正面から取り組んでおり、ソフトウェア開発の内製化の価値と課題を認識しています。自動車ブランドがソフトウェアを社内で開発する場合でもアウトソーシングする場合でも、成功の鍵は、ソフトウェアの開発と保守のプロセスで AI ベースのツールが果たす役割を理解することにあります。

常にイノベーションが求められている中、自動車業界のすべての企業は、将来の自動車に不可欠な要素としてソフトウェアの役割をよく考える必要があります。AI を活用して、より迅速かつ効率的な開発サイクルを実現することは、常に進化する市場で存在感と競争力を維持するための鍵となります。メーカーが直面している大きな課題を AI がどのように解決できるかについて詳しく知りたい場合、右記のホワイトペーパーをダウンロードしてください。自動車業界における 5 つのソフトウェア開発の課題と、AI がそれらにどのように対処しているのか。

In the automotive industry, electronic control units (ECUs) have evolved into complex systems that are heavily reliant on software. While the bill of material (BOM) cost is a crucial consideration for ECU product owners, it is equally important to understand the costs and challenges that arise after the ECU is built. Software integration into the full vehicle system, software certification, multiple over-the-air (OTA) updates, and continuous testing throughout the ECU's lifetime introduce significant challenges, costs and opportunities for vehicle OEMs and specifically for ECU product owners.

Software Integration and Full Vehicle System:

Once an ECU is built, it must seamlessly integrate into the full vehicle system, harmonizing with other ECUs and components. Achieving interoperability among various ECUs, each with its own software stack and interfaces can be challenging. Different coding standards, software architectures, and communication protocols must be carefully coordinated to ensure smooth integration. However, the challenge does not end here. Every time one part of the system (ECU) is updated, it invariably has a detrimental effect on the rest of the system, and this is a far bigger challenge, one that often leads to delays in product releases.

AI-based tools should be considered to remove the blame game and accurately visualize the software changes made and their effect on the rest of the system. This will enable fast and accurate error resolution for smoother integration.

Software Certification:

Certification is a critical aspect of ECU development and vehicle production, ensuring compliance with industry standards and regulations. However, software changes and updates after the initial build can trigger the need for recertification, requiring clear evidence and documentation of the changes. When making software updates, it is essential to provide evidence that demonstrates the changes made and their impact on regulated functions. This evidence is necessary to meet certification requirements such as WVTA (Whole Vehicle Type Approval), proving that the modifications do not compromise safety or emissions, to name a few.

Current methods for collecting and documenting this evidence requires manual tracking, analysis, and documentation. While this methodology would suffice for physical vehicle updates that traditionally occurred once every two years, new methods and tools are required for software updates that are a continuous feature of vehicle software. AI-based tools can clearly visualize not only the newly added and updated software functions in a new version of ECU software but also the software functionality paths and behaviour. This capability will automatically provide the required evidence of what regulated functions have and have not been affected by the software update.

Reducing OTA Update Costs and Enabling Seamless Updates:

ECUs require regular OTA updates to address software-related issues, security vulnerabilities, performance enhancements and to enable new revenue streams. Minimizing OTA update costs and enabling seamless updates without vehicle downtime is crucial for a superior user experience:

a) Cost Comparison: Let's consider a hypothetical scenario for a truck manufacturer that produces 100,000 vehicles per year. Traditionally, a full image update involves transferring the entire software image for each ECU to each vehicle, which can be costly in terms of bandwidth consumption, data transfer and flash memory redundancy. Using a cost consideration simulator and assuming a conservative estimate of 50 ECUs per vehicle and four updates per year, the cost for a full image update could amount to $14 million.

However, adopting an AI-based line-of-code update approach can dramatically reduce costs. By leveraging machine learning algorithms to analyze the code changes between versions, only the modified lines of code need to be transferred during an update. Such additive updates can be applied to the next free space on the ECU flash, removing the need for expensive flash memory redundancy (A/B memory). Using this method to perform OTA updates to any and all ECUs in the vehicle could reduce the data transfer, flash memory redundancy and installation costs to less than $165,000. This represents a significant cost reduction compared to a full image update, saving the OEM over $13.5 million annually.

b) Over-the-Air Updates without Vehicle Downtime: Enabling OTA updates without taking the vehicle offline is critical to ensure a seamless user experience and vehicle uptime. Implementing dual-bank memory architectures, where one bank is updated while the other remains operational, allows updates to be performed in the background without interrupting the vehicle's normal operation, assuming that there are enough CPU/RAM resources to enable execution from one bank in parallel to update/write on the second, which is not always the case. This approach minimizes inconvenience to the user and maximizes vehicle uptime; however, this method is extremely expensive and resource-reliant, as mentioned above.

AI-based additive updates can be written to the next free space in the ECU flash without interfering with the regular use of the ECU software in a method that is called Read-While-Write (RWW). In this manner, only the changed software is written to the flash while the vehicle is in use, and the update is seamlessly applied when the vehicle is next started, minimizing the required time in a safe state. Even if RWW is not possible on the ECU flash writing the tiny update file while the vehicle is in a safe-state will still take a fraction of the time of writing the full software version image file.

Continuous Testing, even on the road:

Ensuring vehicle software reliability and performance requires continuous testing and maintenance throughout the vehicle's lifecycle. While the vehicle is on the road, it is essential to monitor and collect data to identify potential software issues, hacks, or anomalies. This data can be used to improve future software updates, enhance vehicle performance, and address any emerging deviations in the software behaviour. By using AI-based technology to monitor various software parameters, such as CPU usage, memory allocation, function paths and communication patterns, anomalies can be detected early, and predictions reached for how long remains until the ECU malfunctions. Furthermore, such AI-based systems will reduce error-resolution time by specifically identifying which software functions are misbehaving. This proactive approach to software maintenance minimizes the risk of unexpected failures, optimizes vehicle performance, and enhances customer satisfaction.

Conclusion:

While the bill of material (BOM) cost is an essential consideration for ECU product owners, it is crucial to recognize the significant costs and challenges that occur after the ECU is built. Software integration into the full vehicle system, vehicle software certification, multiple OTA updates and continuous testing throughout the ECU's lifetime can significantly impact overall costs, time-to-market, and customer satisfaction. These challenges can be mitigated by proactively implementing AI-based software development tools to generate actionable insights throughout the ECU's software lifecycle.

There's a push for individuals, fleets, and businesses to all become more efficient in the journey to hit their own sustainability goals. This is the case for automakers, too. They're not just looking for ways to make their vehicles, materials, and factories more sustainable but the entire process from the idea through to the aftersales.

The automotive industry is one of the biggest contributors to environmental degradation. As such, there is an urgent need for automakers to embrace sustainable practices in their manufacturing processes. One area that offers immense potential for promoting sustainability in the automotive industry is vehicle software.

When you consider how crucial software is in modern vehicles -- determining the car's performance, safety features, and overall functionality -- it's key for manufacturers to look for ways to maximize this to increase sustainability while also shortening the development process.

The Aurora Labs Vehicle Software Intelligence (VSI) tools play a significant role here in helping automakers reach their sustainability goals. Here's how we do it.

Making the process more efficient

One of the key benefits of using Aurora Labs vehicle software intelligence is that it can help automakers optimize their manufacturing processes. By creating smaller software packages, developers can reduce the time and resources required to build and test the software. This, in turn, reduces the production time, speeding up the time to market while also improving error resolution. In this way, automakers can save energy, developer time, and electricity use while launching new cars.

Reducing semiconductor use

Semiconductors play a crucial role in modern vehicles. They are used in various systems, such as infotainment, safety, and engine management. With the increasing shortage of semiconductor components and precious metals used to make them, it is essential to reduce the use of these materials.

By adopting Aurora Labs vehicle software intelligence, manufacturers can take a different approach to updates. The Line-of-Code Intelligence^TM updates take up less space on the flash memory, reducing the amount of flash memory required within a vehicle while making it last up to 40 times longer.

With these components -- and the precious metals used to make them -- in increasingly short supply, manufacturers can reduce the need to lean on the supply chain. With fewer materials in each vehicle, this can improve overall sustainability.

Using less energy

Running tests on hundreds of millions of lines of code is incredibly energy intensive. With Auto Detect from Aurora Labs, developers can speed up software testing, identifying exactly which tests are necessary ahead of release. This eliminates the need to run every single test, and developers can focus on the affected functions only. This reduces the time and electricity needed to identify bugs and release updates. Additionally, smaller update files require less network storage and data communication resources, which further reduces ongoing energy use.

In conclusion, Aurora Labs Vehicle Software Intelligence (VSI) offers immense potential for promoting sustainability in the automotive industry. By leveraging software intelligence, automakers can optimize their manufacturing processes, reduce semiconductor use, and conserve energy. As we strive to achieve a more sustainable future, embracing vehicle software intelligence is an essential step toward achieving sustainability in the automotive industry.

To find out more about how Aurora Labs' technology works, get in touch.

It's quite clear that modern cars are sophisticated computers on wheels. In fact, many newer manufacturers are focusing on software first and building vehicles around that. These software-defined automakers tend to specialize in electric cars because the software element is more important than ever when dealing with battery management and maximizing powertrain efficiency.

This approach is causing a shift in the automotive industry, and traditional vehicle manufacturers are increasingly focusing on software, especially as many transition to making more electric vehicles (EVs).

Here are some of the areas where software has become crucial.

Safety systems

The latest Vehicle Safety Regulation introduces a number of mandatory advanced driver assist systems (ADAS) for all new vehicles and establishes a framework for driverless vehicles in the future. It's likely these regulations will become more stringent in the future and will go into more detail on over-the-air (OTA) updates (R156), Cyber-Security (R155) and more. Software is the key to all these features, as it allows manufacturers to deliver what's expected from both regulators and customers.

Connectivity and entertainment

The software in a vehicle determines just how connected it is. Connectivity features such as app access, OTA updates, and voice control are all powered by software. Not only does this link to entertainment features and services but also practicality and safety, too.

Many manufacturers are looking at ways to make controlling the car's features safer than ever. BMW has gesture control, Stellantis is working on a SmartCockpit, and numerous other brands are using software to make the driver and passenger experience more connected than ever.

Updates

Drivers have come to expect instant over-the-air (OTA) updates and will not tolerate a trip to a dealership for software issues, updates, or bug fixes. Currently, not all manufacturers are able to update a vehicle's firmware over the air -- even if they can wirelessly apply minor updates to the navigation, for example. To keep up with software-defined vehicle companies and the standard they're setting for customers, legacy manufacturers are focusing on their software to enable them to deliver updates in a similar way.

Software updates also enable manufacturers to create new revenue streams. Whether offering paid-for upgrades over the air (as Tesla does with its Autopilot system) or through a subscription model for certain features (as BMW does), this is something a lot of automakers are exploring. And rightly so; In our 2022 Automotive Software Survey, 44% of respondents stated they'd prefer to pay for their optional vehicle functionality as a download.

Battery management

Almost 10% of all global car sales were electric in 2021, which brought the total number of electric cars on the world's roads to about 16.5 million, triple the amount in 2018. Despite this interest in EVs, however, consumers are still concerned about range.

Software has the power to improve battery management, meaning manufacturers need to spend less on hardware to improve the efficiency -- and, therefore, range -- of a vehicle. This could be key in the future as the EV market becomes even more competitive.

Autonomous driving

Goldman Sachs reports that Level 3 and higher autonomous technologies will account for approximately 15% of sales in 2030, up from 0% in 2020. Any autonomous capability relies on software to provide the required functionality, so it makes sense that automakers are directing some of their attention to this technology. It's clear from the report that manufacturers will need to focus on their software in order to capitalize on this area of the market in the future.

Enabling new mobility services

The way we move is changing, and it's the software in a vehicle that will unlock new services such as pay-as-you-go car hire, ride-sharing and carpooling, and subscription services for a pool of vehicles. This software will also enable a more advanced transport-as-a-service (TaaS) model for autonomous vehicles and other fleets. This will not only enable fleet managers to offer their vehicles for use by others but also monitor and maintain them.

As a key differentiator

It's not just cars that are evolving but the tastes of buyers too. There's a need for automakers to appeal to the new generation of digital natives. These people will expect a smartphone-like experience from their cars, meaning connectivity, OTA updates, and the ability to easily add new features. This gives automakers the chance to stand out from their competition.

With more than 100 million lines of code, vehicle software is complex. It's vital manufacturers are using the right tools within the development process to ensure their software is high-quality while meeting the demands of modern consumers. On top of this, the Automotive Software Survey showed that it's more crucial than ever for manufacturers to be able to predict software anomalies rather than simply react to them --- 85% of respondents considered this "important" or "very important".

If you'd like to explore how the Aurora Labs suite of AI-powered tools can help improve the quality of your software while reducing the time-to-market, get in touch today.