Could driverless cars be our future mode of transportation? Advances in autonomous driving technology and legal and ethical challenges

Driverless cars have the potential to reduce traffic accidents and provide efficient transportation with the advancement of autonomous driving technology, but there are doubts due to consumer anxiety and accident cases. There is a need to improve technical reliability and security, and to address legal and ethical issues.

 

The field of driverless cars is an area of active research with the development of artificial intelligence. In particular, autonomous driving technology has the potential to reduce traffic accidents, ease traffic congestion, and provide efficient transportation. However, the concept of driverless cars is not yet commercially viable, and the psychological factor of not being in direct control has led to increased anxiety among consumers.
The fear of driverless cars also stems from real-life accidents. Accidents involving Google’s AI-powered driverless cars and the death of a driver in a Tesla self-driving car in 2016 have raised consumer concerns. In addition, on March 24, 2017, an Uber self-driving car was taken out of service in Arizona after it rear-ended an oncoming car during a test run and rolled over. These incidents, which are common across companies, have led to widespread skepticism about self-driving cars.
However, these doubts are misconceptions based on consumer psychological anxiety without an understanding of how they work. To correct this, it is necessary to know how autonomous driving works and to have an accurate understanding of driverless cars.
In order for a driverless car to drive, it must first recognize its surroundings using cameras, radar, GPS, and other sensors. It collects a lot of data, digitizes and transmits it, and then decides what direction and speed to move in.
To talk about the stability of driverless cars, we need to understand the detailed driving principles. An autonomous vehicle is divided into systems to recognize the vehicle’s surroundings, systems to determine the vehicle’s absolute position, and systems to avoid obstacles. They are equipped with cameras, computers for real-time control, computers to process data from images and lasers, and information processing computers to collect information from the external environment and relay it through the network. Like a child learning on its own, a driverless car learns by constantly repeating the process of recognizing, grasping, avoiding, and processing, and uses functional driving assistance systems to drive, brake, and react to unexpected situations.
In order to maintain stability through the system, driverless cars are equipped with hardware sensors and software that are independently configured so that even if a camera or laser sensor is damaged in the middle and cannot work, the overall system can still operate. In addition, the vehicle control system is equipped with a switch with a stop function to stop the vehicle in case of an emergency. Each data is transmitted to the computer through the network, and the data is extracted from the network and used according to each algorithm module, so the algorithm module and sensor module are independently organized, so even if some sensors fail, the system can operate normally.
Other factors that contribute to the instability of driverless cars include hacking and cyberattacks. This is because the algorithms and data of driverless cars are influenced by artificial intelligence and computer programs. In recent years, RSA ciphers, which use prime factorization for ciphers in cybersecurity, such as networks, have become a mainstay. The idea of RSA ciphers is to represent important information in two prime numbers, and then send the product of the two prime numbers with a hint as a password. RSA ciphers are the dominant cryptographic method. In recent years, researchers have been working on algorithms to reduce the time it takes to decompose prime factors using various approaches. However, even with a supercomputer running, it takes a long time, so RSA ciphers can effectively delay the time.
In response, a new paradigm of cryptography called quantum cryptography is emerging to create more secure and robust ciphers. Quantum cryptography is an application of Heisenberg’s indeterminacy principle, which states that when a qubit is observed from the outside, it can take on the values of 0 and 1 simultaneously, and then be determined to be either 0 or 1. By tracking the changes in the quanta, it is possible to determine if someone is eavesdropping on the network and keep the internet network secure.
Self-driving cars are still far from being reliable in terms of safety and technology. The technical aspects, in particular, have been exaggerated by the media, which often sensationalizes them by maximizing the error of a few mechanical glitches. However, the technical aspects of driverless cars are equipped with advanced safeguards that make them safer than human drivers. They also have advanced security systems in place to prevent hacking or cyberattacks. The last thing we want to hear about is driverless cars causing accidents.
The commercialization of driverless cars requires not only technological advances, but also legal and ethical issues. Legal mechanisms must be put in place to clearly define who is responsible when a self-driving car causes an accident, and the standards for ethical judgment by self-driving algorithms must be clearly established. Only when these issues are resolved will driverless cars become a part of our lives.