In this blog post, we will look at how the development of IT technology has come to the center of the automotive industry, focusing on autonomous vehicles.
IT companies are driving the automotive industry?
The car, which has become an indispensable part of our lives, is the most familiar technology that allows us to overcome the physical limitations of humans. In the past, the engine was the most important element in the automotive market, but recently, as most automotive devices have become electronic and cutting-edge safety systems and user-friendly equipment have emerged, the way consumers and developers view cars has changed. Now, the most important thing in a car is not the engine, but the “brain.” In particular, with the emergence of IT, communication, and super-large data processing and implementation technologies, autonomous vehicles, or driverless cars, are attracting attention. Let’s take a look at driverless cars, which are being actively researched by global companies including Google and NVIDIA.
How will we deal with driverless cars on the road?
Anyone who has taken a driver’s license test will remember the tension of the driving test. You have to pay attention to the road ahead and your surroundings to adjust to traffic conditions and deal with unexpected situations while observing various traffic laws, and you have to judge and steer to reach your destination. This is a very stressful process. The tasks of an unmanned vehicle are largely divided into steering and understanding road conditions.
Google is building GPS technology and LIDAR systems for autonomous driving. First, the current location and destination are compared using GPS to determine the direction in which the car is traveling. At this point, the road connection status (road closures, new roads, etc.) and the accurate location relationship of the road based on the map are essential. In this respect, Google Maps, which has a global map, road status, and street view, has a very large influence.
Even if the GPS and navigation capabilities are solved, it is important to accurately identify the various physical conditions of the road. To do this, Google uses a sensor device called “LiDAR.” This device consists of a remote laser system, sound wave equipment, 3D cameras, and radar equipment to detect the distance between objects and hazards on the road. In particular, laser equipment collects information through objects and reflected lasers from all angles at 360 degrees, reading 1.6 million pieces of information per second.
The actions of NVIDIA, a company specializing in GPU (graphics processing unit) technology, are also noteworthy. NVIDIA’s driving judgment mainly analyzes the information received through 12 cameras installed in the vehicle with an ultra-compact image processor. This image processor analyzes information by dividing the surrounding objects into small units to understand the meaning of signs and recognize ambulances. In particular, when the processor encounters information that it cannot analyze, it learns new information through the network and evolves. This falls under the field of artificial intelligence called “machine learning,” which is the same learning pattern as the artificial intelligence “AlphaGo.” What is interesting here is that this AI technology, which is the basis for driverless car technology, is being developed by Google, the same company that created AlphaGo.
Who is responsible in the event of a driverless car accident?
Legislation that allows driverless cars to be driven on 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 in the car. If the driving of truly autonomous vehicles is permitted, a number of ethical and legal issues will need to be considered before this can happen. First of all, if the driving of a car is fully automated, the system could be hacked remotely via a network, which could lead to major risks. In addition, the responsibility for accidents should be determined by the owner or manufacturer of the car. Another problem is that there are an incalculable number of unexpected situations on the road. For example, there may be sudden changes in the road or natural disasters.
But it can be solved!
As mentioned above, there are still many issues to be solved in the technology of driverless cars. However, when you consider the fact that there are an average of seven traffic accidents caused by drowsy driving in Korea alone, you can see that driverless car technology is not just for convenience. Compared to the speed of development of artificial intelligence AlphaGo, the technical limitations of autonomous driving systems are predicted to be overcome in the near future. After sufficient discussion from the institutional and ethical perspectives, it will not be long before we see our own cars driving themselves on the road.
