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8 Revolutionary Software Development Trends in the Automotive Industry

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John Smith
8 Revolutionary Software Development Trends in the Automotive Industry

The automotive industry is increasingly reliant on digital technologies. The automotive industry has not been spared from digital transformation. Cars are no longer just automobiles; they are supercomputers on wheels. However, since their primary function remains the same, all of their value-added features turn the emphasis away from hardware and toward software content.

According to Reuters, the demand for advanced safety features in automated and self-driving vehicles will more than quadruple automotive tech revenues to $1.2 trillion per year by 2030. As of now, vehicle software generates $280 billion in annual sales, which is quite an incredible figure.

As a result, automotive software developers must adapt their technological development activities to keep up with the changing demand.

Let's take a look at some of the most important developments in automotive technology.

Mobility Data that is Bigger and Faster

Many descriptions and reviews of the new car models would most likely use the phrase "supercomputer on wheels." There's a very good explanation for this. Aside from enhanced tech, we've seen an increase in the use of various sensory-based instruments. They are resolving more issues and providing consumers with new options.

A sensor fusion technology that manages all of the data delivered by a large number of sensors installed in our vehicles is needed. This information is disseminated through ever-evolving connectivity. Modern cars, for example, can communicate with each other and other connected devices thanks to new technology like 5G.

Automotive Artificial Intelligence

Artificial intelligence (AI) has been a buzzword in a variety of sectors in recent years. Automotive software development is aimed at increasing comfort, protection, and efficiency. This makes Contextual Artificial Intelligence and Deep Learning a development to keep an eye on. In the face of simulation research, image processing, recognition, and deep learning for better decision-making, automotive companies have already begun to invest in this trend. Brain-to-vehicle technology is now being tested for improved car safety.

Artificial Intelligence's broad variety of applications is expected to develop as the technology advances.

Functional Safety

We can't avoid talking about safety again because it's the most important aspect of any car, and we've discussed it many times in previous trends. Functional protection is a mechanism that must be incorporated into the design process from the outset. It is attracting a lot of attention. Processors that aren't built to functional safety standards may result in time-consuming and expensive certification processes for safety-critical applications.

Strengthened Open Source Software (OSS)

Open Source Software is now being adopted by a growing number of OEMs and Tier 1s. While Linux has been used in this space for some time, Automotive Grade Linux will eventually win out. In IVI, Android OS is also gaining popularity.

Open Source Software elements that endorse practical safety use cases have been built with the rigour needed.

Security Requirements Have Become More Stringent

The rise in connectivity requirements, as we've already discussed, has resulted in a significant increase in security requirements. Modern smart vehicles need much more sophisticated protection than just protecting the vehicle's physical networks.The main focus will be on two-way protection, which can avoid both external and internal vulnerabilities.

Human Adaptability

Being more human is the secret to a company's development and success in the digital automotive world. Following the new industry trends isn't enough for developers. OEMs must consider the driver's experience and comfort, not just creativity, since certain innovations can repel rather than attract customers.

Vehicles that are crammed with all of the latest updates aren't what make them popular. Users' expectations must be recognised and aligned with the company's strengths by automotive software developers.

Artificial Intelligence (AI) must be tailored to human activity in order to enhance the user experience. Instead of a car packed with all the latest technology, a great one should be your differentiating factor.

Electronic Control Unit (ECU) Functionality

With the rise in functional requirements, automotive software developers are free to explore new forms of workloads. They can consolidate functionality thanks to feature-rich silicone platforms and improvements in vehicle design.

Embedded real-virtualization solutions support virtual ECUs, which are becoming more popular. We're getting close to a point where the amount of ECUs outnumbers the room available to house all of the electronics and cabling needed to link it.

Furthermore, the cabling used to connect all of the ECUs is one of the most expensive car parts. ECUs are sweeping the automotive industry for this purpose. The trend toward consolidation will undoubtedly continue as cars become smarter.

Over the Air (OTA) Updates

It's no longer necessary to visit a vehicle service centre to update the software on an ECU. ECUs are supposed to be able to upgrade over the air in this technical age of advanced electronics (OTA). You don't go to an Apple store to upgrade your iPhone, do you? Given that this feature has been available on smartphones for over a decade, it is likely that it will soon be available on all computer platforms. You should be able to upgrade the software in your car just as you do your smartphone.

Moving Forward

Automotive software development services allow your company to meet current and future demands for vehicle operation, repair, and maintenance workshops through automation and integration. With modernised processes and all necessary features, workers will function more efficiently and productively, resulting in more time and improved income.

The demand for automotive software will undoubtedly increase. They have an effect on how vehicle architectures are implemented. As a result, OEMs must consider a more systematic approach to vehicle design. Using AI to create a human-friendly vehicle is likely to be the most effective.

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