Automotive, transforming
Tags: programming, discuss, career
Published: 2022-06-02 10:00:29

Automotive is one of those areas where most developers would like to work at least once.What do we associate with cars in everyday life? More often than not, it's traffic jams and the need for maintenance. But when you think about something less mundane - what cars will be able to do in the future and what they will give future users, it's a fascinating perspective: 

- unmanned cars
- "Smart cities without traffic jams.
- remote diagnosis of technical condition of a car.
- Augmented reality with message projection on the driver's window.
- Gesture control

These are 5 levels of autonomy - the accepted gradation for measuring the automation that enables unmanned driving. At the moment, most cars are at level 2, but the market leaders are already striving to get to level 3+, where you can already see what your car can do independently. It will be around 3-4 years from now. Whoever can do it first will win the market. 

## What inspires me about Automotive

First of all, I wonder who is going to win the technology race and be the first to reach the third level of autonomy. It is a highly competitive industry, and I like the level of challenge that lies ahead. It's both about the complexity of the systems being developed and the responsibility of management. Secondly, I understand that my project is the real result of my work, it drives on the road, you can touch it with your hands and it's not something distant and abstract. 

And you can also find all the mainstream trends in Automotive: ML, IoT, Cloud, big data, blockchain, 3D engines, 5G. Golang is becoming popular, C/C++ for developing internal vehicle systems and Java, Python, which support the development and testing infrastructure, have not gone anywhere. 

## Industry features for IT

What is Automotive now interested in for technicians? 

Systems complexity. The complexity of the code and the vehicle system as a whole is becoming a real challenge for any developer, tester and any technician who has anything to do with code. The most important thing to know here is that "automobile" code simply has so many lines. A bit of statistics. A combat aircraft is 30 million lines of code, Boeing 787 has 6.5 million lines of code for control systems and Mercedes S-class has 100 million lines of code. Impressive, isn't it? 

Now, a car can be printed on a 3D printer if you want, but the software for it will still be quite complex. It will be even more complex, so over time, development will take away more and more of the cost of the car itself, which for us as IT specialists is, in general, great. 

A high level of quality and a high cost of error. According to NASA, an average of 10,000 lines of code contain 1 defect. It is not difficult to calculate how many defects 100 million code lines may contain. That's why Automotive is also a very strict quality standard. Hence, there is a necessity in additional systems which should support the creation of such software, provide its validation and verification at the highest level. 

Importance of security. Safety is a basic and vital option for a vehicle, on which human lives will literally depend. The simplest example is seat belts, which save the lives of millions of people every year. But when it comes to development, technology has gone further - active safety technology, for example, is the various stabilisation systems that take over control of the vehicle in critical situations. This subject area has a direct impact on the complexity of development in Automotive.

The use of mathematics and algorithms. Everything is based on devices such as radars, lidars (laser radar), cameras, ultrasonics. We, for example, developed part of the algorithms for lidar, where a Kalman filter was used to filter out noise in the point cloud. So, mathematicians, C/C++, embedded developers, we are waiting for you - there is nowhere without mathematics. 

ADAS (Advanced driver-assistance systems) also uses navigation sensors, active mapping with position detection on the map (so-called SLAM algorithms), and information from sensors in the car.

If you're wondering

What is worth studying and what to read about if you want to get into the field of automotive engineering: 

- The life cycle of vehicle design;
- Validation and verification;
- CI/CD;
- Specifics of working with microcontrollers;
- Automotive networks;
- Operating systems;
- Programming languages and specific standards;
- Tools in the automotive industry;
- ASIL - automotive safety integrity levels;
- A-SPICE methodology;
- Functional Safety ISO 26262.

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