Self-driving cars (autonomous vehicles) A self-driving car is a vehicle that is capable of operating itself without direct intervention from the driver. Instead of relying on humans, self-driving cars use advanced technologies such as artificial intelligence (AI), sensors, navigation systems, and data networks to detect and handle complex traffic situations.
According to the National Highway Traffic Safety Administration (NHTSA), 90% of traffic accidents are caused by human error, such as distraction, intoxication, or fatigue. Self-driving cars with AI-powered analytics and decision-making capabilities have the potential to significantly reduce these risks, improving safety.
Self-driving car technology is classified into 6 levels, from 0 to 5, based on the level of automation and driver intervention. The great benefits of this type of car include: improving traffic safety, reducing congestion, saving energy and improving transportation efficiency. However, self-driving technology also faces significant challenges, from high costs, legal issues, security issues to limited ability to operate in bad weather conditions.
In addition, self-driving cars will have a profound impact on society by reshaping the labor market, changing the way vehicles are used, creating new legal challenges and bringing different travel experiences.
Follow the article to understand more about self-driving cars and the levels of self-driving cars.
Self-driving cars are vehicles that can operate without a direct driver thanks to advanced automated systems. Artificial intelligence (AI) plays a central role in processing information from sensors; LIDAR, radar to help the car identify obstacles, surrounding vehicles and predict potential traffic situations.
Thanks to its ability to analyze the environment and make automatic decisions, the car can accelerate, decelerate, maintain a safe distance, and even change lanes automatically.
An important point to note is that self-driving cars are not only capable of moving by themselves, but can also learn from traffic situations they encounter, thanks to the built-in machine learning system. With each move, data collected from the surrounding environment will be processed and help the car improve its response, creating an increasingly intelligent and safer system.
According to the Society of Automotive Engineers (SAE) standards, self-driving cars are classified into 6 levels based on the level of automation and driver intervention, including level 0, level 1, level 2, level 3, level 4, level 5.
Vehicles at this level are not capable of automation, the entire operation is controlled by the driver. Support features such as collision warning or emergency braking assist only provide information and do not directly interfere with the control system.
A typical example is today's conventional cars with warning systems, but still require driver attention and operation.
At this level, the car can perform some basic tasks such as maintaining speed and maintaining a safe distance thanks to the Adaptive Cruise Control system. However, the driver still needs to keep his hands on the wheel and monitor the driving process at all times. Level 1 cars cannot fully control themselves and only provide partial assistance.
Level 2 vehicles can simultaneously control acceleration and braking, as well as lane keeping automatically, but the driver must still monitor and be ready to intervene when needed.
Tesla Autopilot is a prime example of level 2 technology, where the car can drive itself on the highway but still requires the driver's attention.
Level 3 vehicles can drive autonomously in certain conditions, such as highways or pre-programmed routes. The driver can temporarily leave constant supervision, but must intervene when the system warns.
An example is the Audi A8 with self-driving capabilities in highway environments under congested traffic conditions.
At this level, the vehicle can drive completely autonomously without driver supervision in pre-determined environmental conditions. The driver does not need to intervene in most situations. However, in complex situations beyond the vehicle's control, the vehicle still requires driver intervention.
The highest level of self-driving cars, cars can operate themselves in all conditions without any intervention from the driver. Level 5 cars will not have a steering wheel or traditional control pedals.
At the moment, this technology is still in development and testing, but promises to be the future of the transportation industry.
Comparison table of autonomous vehicle levels:
Level | Name | main feature | Driving responsibility |
Level 0 | No automation | No automatic features. Full driver control. | The driver is solely responsible. |
Level 1 | Driver assistance | There are assist systems such as cruise control, but they require the driver to control the steering wheel. | The driver still needs to keep his hands on the steering wheel. |
Level 2 | Partial automation | Cars can automatically control speed and keep lanes, but drivers need to monitor | The driver monitors and intervenes when necessary |
Level 3 | Conditional Automation | The vehicle can operate autonomously under certain conditions. The driver needs to intervene when the system requires it. | The driver only intervenes when requested by the system. |
Level 4 | Highly automated | The vehicle operates completely autonomously under pre-programmed conditions, without the need for constant supervision. | No driver intervention required under ideal conditions |
Level 5 | Fully automated | The car is fully autonomous in all conditions without driver intervention. | No driver required |
Self-driving cars have many advantages, such as improving traffic safety, reducing congestion, saving fuel, assisting people with disabilities, and improving logistics efficiency. However, disadvantages include legal issues, high costs, data security, and limited handling in complex weather conditions.
Self-driving cars offer outstanding advantages such as safety and reducing traffic congestion, saving fuel, supporting the disabled and the elderly, and increasing logistics efficiency. Specifically:
The self-driving car model has limitations related to legal issues, costs, cybersecurity as well as the ability to handle complex conditions. Specifically:
Self-driving cars have far-reaching impacts on society, from changing the labor market, changing vehicle usage patterns, reducing environmental impacts, creating new regulatory needs. In particular, this line of cars promises and brings a completely new travel experience to users.
The proliferation of self-driving cars could lead to major changes in the labor market, especially in transportation-related industries. Truck drivers, taxi drivers, and ride-hailing drivers could be affected, as companies turn to self-driving cars to save on labor costs and optimize operations.
However, the development of this technology also creates new demand for maintenance technicians, AI programmers and jobs related to managing self-driving car systems. Therefore, job transformation will take place, and require retraining of human resources.
According to research by McKinsey Global Institute (2019, 'The Future of Work in America', USA), an estimated 8.5-9 million jobs in the transportation and logistics sector could be affected by the development of self-driving cars by 2030.
With the advent of autonomous vehicles, we may see a shift from individual car ownership to a shared car model. Services such as self-driving taxis may become more common, reducing the need for private car ownership and optimizing costs for users.
This could lead to changes in the way cities design space, reducing the amount of parking and dedicating more space to other purposes, such as parks or housing.
Research by the MIT Transportation Research Center (2022, 'Shared Autonomous Vehicle Implementation', USA) predicts that by 2030, the number of private cars in urban areas could be reduced by up to 80% through the application of autonomous car sharing models.
Self-driving cars have the potential to contribute to reducing emissions and pollution. By optimizing the route and controlling speed, self-driving cars can save energy and reduce fuel consumption. Furthermore, when combined with electric vehicles, the positive impact on the environment will be even greater, supporting the goals of sustainable development and climate change mitigation.
Self-driving technology will also have a major impact on legal regulations, especially in determining liability in the event of an accident. Countries are already starting to adjust their traffic and insurance laws to accommodate the development of self-driving cars. However, more extensive regulation will be needed around liability, data security, and privacy.
Self-driving cars could completely transform the travel experience. Passengers would have time to relax, work, or play without having to worry about driving. The interior of self-driving cars could be redesigned to accommodate these needs, providing greater comfort and convenience throughout the journey.
Self-driving cars are equipped with LIDAR sensors, thermal cameras, and high-bandwidth radar systems that help identify objects in weather conditions such as heavy rain, snow, or fog. However, performance can still be reduced compared to ideal conditions.
To learn more about sensors, you can refer to the article: Overview of sensors car sensors – Function, importance.
Self-driving cars can alert the driver directly through sounds, warning lights, and sometimes use voice control technology to request human intervention when necessary.
Self-driving cars require specific maintenance related to sensors, software, and AI systems. Electronic components need to be regularly inspected and updated, but mechanical maintenance may be less required because they don’t need to replace as many traditional components as gasoline engines.
Countries like the US, China, Germany… are currently leading the way in developing and testing self-driving cars, with many large companies like Waymo, Tesla, and Baidu stepping up research and development.
Self-driving cars could become part of public transport systems, with self-driving buses and autonomous taxis reducing operating costs and increasing efficiency in urban mobility.
Insurance companies are looking at cutting costs car insurance self-driving cars thanks to the technology's ability to reduce accidents. However, insurance prices will depend on the level of autonomy and the risks involved in the technology.
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