In this blog post, we will examine how IT technology has emerged as the center of the automotive industry, focusing on autonomous vehicles.
Are IT companies driving the automotive industry?
Cars have become an indispensable part of our lives and can be considered the most familiar technology that transcends human physical limitations. In the past, engines were the most important element in the automotive market, but recently, most automotive devices have been digitized, and the emergence of cutting-edge safety systems and user-friendly equipment has changed the way consumers and developers view cars.
Now, the most important part of a car is no longer the engine, but its “brain.” In particular, with the emergence of IT, communications, and large-scale data processing and implementation technologies, autonomous driving cars, or driverless cars, are gaining attention. We will take a closer look at driverless cars, which are being actively researched by global companies such as Google and NVIDIA.
How should we handle driverless cars on the road?
Anyone who has taken a driving test will remember the tension of the driving exam. You must adhere to various traffic laws, adapt to traffic conditions, and respond to unexpected situations while keeping an eye on the road ahead and your surroundings. You must also determine the direction and make decisions to reach your destination. This is a highly stressful process. The tasks of a driverless car can be broadly divided into two categories: determining direction and understanding road conditions.
Google is developing GPS technology and LIDAR systems for self-driving cars. First, GPS compares the current location with the destination to determine the car’s direction of travel. At this stage, accurate information about the road’s physical condition (such as road closures or new construction) and its precise location relative to the map is essential. In this regard, Google Maps, which has access to global-scale maps, road conditions, and Street View, holds significant influence.
Even if GPS and navigation capabilities are resolved, accurately understanding the various physical conditions of the road is crucial. To address this, Google uses a sensor device called “LiDAR.” This device consists of a remote laser system, sonar equipment, a 3D camera, and radar equipment, enabling it to detect distances between objects and potential hazards on the road. In particular, the laser equipment collects information by measuring the time it takes for laser beams to reflect off objects from all angles, at a rate of 1.6 million times per second.
Additionally, NVIDIA, a company specializing in GPU (graphics processing unit) technology, is also worth noting. NVIDIA’s driving decisions are primarily based on information received from 12 cameras installed on the vehicle, which is analyzed by a miniature image processor. This image processor divides surrounding objects into small units, analyzes the information, and performs functions such as recognizing the meaning of traffic signs and identifying emergency vehicles. Notably, when the processor encounters information it cannot analyze, it learns new information through a network and continues to develop. This falls under the field of artificial intelligence known as “machine learning,” which shares the same learning pattern as the artificial intelligence system “AlphaGo.” What is interesting here is that this AI technology, which forms the basis of driverless car technology, is being developed by Google, the company that created AlphaGo.
Who is responsible for accidents involving driverless cars?
Legislation permitting driverless cars on public roads has already been passed in the US states of Nevada, Florida, Michigan, and California. However, there is still a restriction that a person must be present in the car. If truly autonomous driving is permitted, numerous ethical and legal issues must be addressed beforehand. First, if driving becomes fully autonomous, the system could be hacked remotely through a network, posing significant risks. Additionally, determining liability in the event of an accident would require deciding whether responsibility lies with the vehicle owner or manufacturer. The sheer number of unforeseeable situations on the road is also a major concern. For example, there could be sudden changes in the road or natural disasters.
However, these issues can be resolved!
As mentioned above, there are still many issues to be resolved in driverless car technology. However, considering that there are seven traffic accidents caused by drowsy driving every day in South Korea alone, it is clear that driverless car technology does not exist solely for convenience. When compared to the rapid development of artificial intelligence like AlphaGo, the technical limitations of autonomous driving systems are expected to be surpassed by human capabilities in the near future. After thorough discussions on institutional and ethical aspects, the day when we see our own cars driving themselves on the roads is not far off.
