Jack of all trades, master of none. Sometimes a team geek, sometimes a lone wolf, or even a dark matter developer. Able to keep his nose above water at all times.
Technology is developing so quickly that no one is surprised by ever-changing electromobility and artificial intelligence innovations. The combination of these fields has never been as fascinating as it is now. Self-driving cars already exist, and in this article, we will discuss what technologies they utilise and what road we still have to go down to take full advantage of them.
Seeing the road ahead: How cars use AI to navigate their surroundings
Automated technologies are already widely used in the automotive industry. These include camera, radar or laser sensor systems linked to the on-board computer. They have a significant impact on driving safety in modern cars. We are mainly talking about functions such as adaptive cruise control, lane control, emergency braking, and park assist. All these systems use sensors to support the driver while driving.
So-called ambient mapping has led a step further towards autonomisation. This involves creating highly accurate road maps and 3D models of the environment. Theoretically, this should allow the car to navigate autonomously through designated areas as if it were using advanced navigation. However, practice has shown that creating such maps is very demanding and expensive. Due to changing environments, road repairs, or non-standard traffic situations, frequent updates are needed.
Artificial intelligence and machine learning have proved to be a revolution. AI in self-driving cars uses a camera system that creates a 360-degree image. This allows the on-board computer to react to changing road conditions in real-time. The popularity of Chat GPT and AI in various fields has shown that there is a very promising direction, especially for the electromobility industry.
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AI in the driver's seat
Artificial intelligence plays a vital role in vehicle autonomy. A pioneer in this area is Tesla, which, in the 12.3 version of Full Self-Driving, uses only machine learning to drive the vehicle. The system consists of eight cameras that process images and learn road behaviour patterns. However, we should remember that this learning occurs within a vast neural network created with millions of cars and real drivers.
Previously, Tesla's software was developed based on hand-programmed descriptions of traffic situations and the correct car behaviour assigned to them. However, it is impossible to predict and cater for every event. Therefore, AI in self-driving cars increases the range of learned patterns based on actual driver behaviour and non-standard events. This enables the computer to anticipate possible situations and respond to them accordingly, improving safety.
AI vs. human error: Will self-driving cars make roads safer?
AI in self-driving cars using neural networks can help improve road safety. Approximately 90% of accidents are caused by driver errors, which is an important area for improvement.
A big issue at the moment is situations in which an imperfect algorithm causes an accident. Although such situations are rare, we cannot fully rule them out, as evidenced by the 2018 accident involving a self-driving Uber. Such cases trigger an avalanche of negative comments, with clickbait headlines adding fuel to the fire. Strong emotions put pressure on the governments, which leads to regulations and restrictions.
Despite understandable human concerns, it is worth looking at the actual figures. According to the Connected Cars report (Ericsson IndustryLab) and data from the Statista platform, self-driving cars are estimated to help reduce fatal accidents by 94%. This offers great potential when it comes to improving safety. Looking at the fact that Tesla can already drive itself a few dozen miles, it seems that we are already not far from the introduction of safety-enhancing vehicles. The Tesla autopilot function has already reduced accidents by 40%.
Dreams and challenges
The issue of developing self-driving cars goes hand in hand with electromobility. In both these areas, Tesla is in the lead. When we think of the cars of the future, we think of electric vehicles that are revolutionising transport – emission-free, intelligent and safe. Those two areas are therefore strongly linked. It is also worth mentioning that they will provide opportunities for efficient travel for people with disabilities, for whom driving a traditional car is not feasible.
However, innovation must be met with understanding from both people and governments. Currently, self-driving cars raise concerns for 93% of Americans. Therefore, we must also consider potential legislation restricting the use of AI in automotive technology. In Europe, the development of autonomous cars has been somewhat slower than in the United States, as regulations are more restrictive.
The issue of data privacy should also be clarified, as the car, by analysing driving style and camera images, processes information related to the driver and the places they visit. Admittedly, this data is also collected in traditional cars. However, its processing by artificial intelligence may raise concerns about whether the algorithm protecting sensitive data is reliable and whether it will be used for other purposes.
The road to revolution
We are one step away from the moment people realise that such technology is already widely available. Self-driving cars do already exist. Version 12.3 of Tesla's Full Self-Driving is already being used on public roads. It is no longer a question of the distant future but the prospect of a few years. Much depends on the policies of governments and possible restrictions on the movement and use of artificial intelligence. If tests confirm a decreasing number of accidents, this will help to increase trust in self-driving cars. However, we are confident these vehicles will soon be available on a larger scale and become a game-changer in the automotive and transport industries.
