How C++ Is Making Autonomous Vehicles Possible

C++ is an old programming language, but it’s still the main language used in the development of automobiles. Why has this language remained such a crucial part of the automotive industry despite its long and time-consuming coding process? The answer is quite simple – C++ is the key to making autonomous vehicles a reality.

Self-driving cars have been lagging behind in development in the last few years, so the role of C++ is arguably more important than ever. Let’s explore why this language is so important for autonomous vehicles and take a look into the future of the automotive industry.

The Role of C++ in Automotive Development

Decades ago, C was the standard programming language for vehicle software. Once C++ was created, it became C’s natural predecessor. The Motor Industry Software Reliability Association (MISRA) and the Automotive Open System Architecture (AUTOSTAR) are the two main language standards used by manufacturers around the world.

As vehicle software becomes more complex, so does C++. This natural progression has been especially significant for safety systems, such as brake and engine monitors. Not only can it provide high-level functionality to these systems, but it also has low-level mechanisms that almost match the system’s assembly language.

It might be older than other languages and more difficult to code, but it’s far too ingrained in the automotive industry for manufacturers to abandon it. This programming language is here to stay.

Versatility 

C++ is a versatile language that developers can easily adapt to meet their needs. It is compatible with other programming languages, which means we can use it in conjunction with systems that utilize newer languages. This versatility is especially important for computer vision and image processing — the two crucial elements of autonomous vehicles.

C++ is the perfect language for dealing with the various sensors inside a self-driving vehicle. For example, OpenCV is a computer vision library all within C++ that developers can use to change the colors, contours and pixels of images to help vehicles process them with greater precision. TensorFlow is C++’s main deep learning framework that could make or break the success of autonomous vehicles.

Engine control units are also best paired with C++ because of its advanced structure combined with low-level mechanisms. Smart cars have more than 100 ECUs that complete everything from engine ignition to park assist. The more ECUs we add to our vehicles, the more important C++ will become.

Efficiency 

C++ is a close replica of the binary architecture of all computer systems. It has a very similar structure to machine-level code, which means it’s extremely efficient with vehicle applications and requires minimal steps for developers. The computers can easily understand the language and perform with greater predictability, which is a huge advantage for autonomous vehicles.

Safety

Safety is the main obstacle inhibiting the growth of autonomous vehicles. They simply aren’t safe enough for people to drive on a massive scale. However, C++ can change that. This language meets the auto industry’s functional safety standards as laid out in the ISO 26262. Safety, scalability, dependability and compatibility are all top priorities in these standards, and C++ checks all of the boxes.

Community Support

Another huge advantage is that it has great support from a global community.  This language has been around since 1979. There are thousands of expert developers and thousands more learning resources for up and coming developers. The barrier for entry into the C++ sphere is non-existent compared to other languages.

So, this language’s old age is actually an advantage for the automotive industry. It is reliable and has extensive coding frameworks. It’s the perfect code for the development of self-driving cars.

Driving the Future of Autonomous Vehicles

Autonomous driving is incomprehensibly complex. Even with perfectly written code, it might not be possible. C++ is the best option we have because of its history, versatility, compatibility and safety. Despite its old age, this language is driving the future of autonomous vehicles and will remain relevant for years to come.