AI is transforming the automotive sector

Nearly 30% of automotive budgets are now dedicated to innovation. This strategy is disrupting standards and fundamentally redefining the industry. And at the heart of these major changes is artificial intelligence, which is taking hold in the automotive world.

The numbers speak for themselves: “By 2030, 20% of all new vehicles sold will have autonomous driving capabilities.” A statistic that proves how much AI is accelerating advances in the automotive industry.

In autonomous driving, it is the brain in control: “detect their environment, analyze data in real time and make intelligent decisions for safe driving”But it doesn't stop there. AI is also reinventing the on-board experience. Automatically adjusting features based on preferences, intuitive interaction with the vehicle, and instant parameter adjustments...

How does AI contribute to road safety?

Road safety and vehicle efficiency remain major issues for car manufacturers such as BMW, Volkswagen, BYD etc. In this context, AI plays a crucial role, acting upstream to prevent risks.
It mainly intervenes through two approaches: predictive maintenance et predictive driving.

1. Predictive maintenance: prevent before repairing

Using sensors built into vehicles (radar, cameras, GPS, real-time traffic data, temperature and tire pressure, etc.), AI instantly collects and analyzes massive volumes of data. Its algorithms then detect anomalies and trigger alerts before a breakdown occurs, allowing for timely intervention.

For exemple, For tires, sensors continuously measure their pressure and temperature. If a leak or deformation is detected, the AI alerts the driver, preventing a dangerous blowout.
This anticipation not only reduces the risk of accidents, but also extends the life of the vehicle.

2. Predictive driving: anticipating dangers

Predictive driving relies primarily on anticipating danger before it even becomes a threat. By combining radar, lidar, cameras, and real-time traffic data, AI detects every detail of the environment and reacts… even before the driver does. Speed, trajectory, braking: everything can be adjusted automatically to avoid accidents and save lives.

At Mercedes-Benz, this vision comes to life with the Pre-Safe Impulse Side. When a side collision is deemed unavoidable, the system triggers airbags integrated into the seats in a fraction of a second, slightly moving the occupant away from the impact. This system will allow a significant reduction the force of the impact and potential injuries.

Thanks to the combination of two approaches which are Additional, the AI transforms the vehicle into real intelligent copilot, capable of predicting, preventing and acting to make the road safer.

How does AI actually work to prevent and anticipate danger?

In-vehicle AI relies on a set of technologies that allow the system to perceive and understand one's environment.
To achieve this, it uses data transmitted in real time by various sensors, for example:

Cameras : capture images to identify objects, road markings, signs, etc.
Radars : measure the distance and speed of surrounding elements (other vehicles, pedestrians, animals, etc.).
LiDARs : send laser pulses to generate a ultra-precise 3D map of the environment.

All data sent by these sensors are "analyzed and interpreted by artificial intelligence algorithms operating through machine learning, such as deep learning which is based on neural networks."

Following this analysis, the AI algorithms make autonomous decisions. Each piece of information gathered about the environment allows them to determine the actions deemed necessary (braking, accelerating, changing direction, or activating a camera) while ensuring compliance with driving regulations and the safety of the driver and their environment.

Automotive AI: innovations and obstacles

Integrating AI into vehicles raises several major challenges. First, there is the question of high costs Between sophisticated sensors, LiDAR systems, radars, and software development, the investment is significant. This impacts the final price of vehicles, making the purchase more substantial for consumers. Furthermore, if a sensor, software, or control system malfunctions, repairs can also be costly.

Then the AI faces a regulatory and legal challenge. The data collected by smart vehicles raises questions of confidentiality and protection, particularly with regard to the GDPR. But the most sensitive question concerns the liability in the event of an accident related to a sensor or software failure: should the manufacturer, the technology provider or the driver be held liable?

In addition, there are ethical issues crucial. AI replaces some human decisions, including in emergency situations. It is therefore essential to establish precise safety rules regarding the decisions to be made in the event of imminent danger. "The car responds in the way it has been programmed. It is not capable of performing an ethical analysis of the situation before making a decision. It is therefore important that all situations are taken into account from the moment it is created and programmed.".

Conclusion

There's strong evidence that AI is profoundly transforming the automotive industry. Through advanced systems, it makes driving more efficient, reduces human error, and helps prevent fatal accidents. “Tesla’s integration of AI has had a significant impact. For example, real-time data indicates a 40% reduction in accident rates for vehicles equipped with Autopilot.”

However, like any innovation, AI faces several challenges: high costs, a complex regulatory framework, ethical issues, etc. Added to this is a crucial point: user experience, which directly influences the adoption of these technologies.

The role of AI is therefore not limited to hazard detection. It personalizes the on-board environment, adjusts settings to the driver's preferences, and offers tailored services. This leaves one essential question: What are the main user experience challenges associated with integrating AI into vehicles?

Source

Marwa Frawes, AMOA project manager at UX-Republic