You are currently viewing AI and the Autonomous Vehicles

AI and the Autonomous Vehicles

  • Post author:
  • Post category:Blog

Artificial intelligence (AI) is revolutionizing the automotive industry. The key to this revolution is the rise of autonomous cars which are fundamentally changing the industry landscape. Equipped with advanced AI technology, these autonomous cars will not only redefine the concept of driving but also shape our cities and society.

The role of AI in autonomous driving is to enable a safer and more comfortable autonomous driving experience by processing large amounts of sensory data, analyzing complex situations, making intelligent decisions, and continuously learning. These technology’s development and continuous improvement are key to realizing autonomous driving technology. Summarized by the industry, there are several applications of AI in autonomous driving (Kerem Gülen,2022)

Sensing and perception

Autonomous cars collect data by using a variety of sensors, such as cameras, lidar, radar, and ultrasonic sensors. This data will be processed and analyzed by using AI algorithms to create a detailed map of the environment and to identify pedestrians, vehicles, traffic lights, and road signs.

Decision making

The real-time decisions can be made based on the data they gather from their sensors. For example, if a self-driving car detects a pedestrian crossing the road, it will use AI to determine the best course of action, such as slowing down or stopping.

Predictive modeling

Autonomous cars use AI to predict the behavior of other road users, such as pedestrians and other vehicles. This helps the car to anticipate potential problems and take appropriate action to avoid them.

Natural language processing

Using AI to understand and respond to spoken commands. Some Autonomous cars are equipped with voice recognition technology that allows passengers to communicate with the car using natural language.

From the users’ perspective, Autonomous driving could be defined into the following 5 levels (Jessica Shea Choksey and Christian Wardlaw, 2021)

Level 0: No Driving Automation. No driving automation technology at all but only relies on drivers to steer a car.

Level 1: Driver Assistance. It refers to a vehicle with an advanced driving assistance system (ADAS) which can support the drivers to better steel a vehicle especially for acceleration and braking in some scenarios. the driver must remain alert and is required to actively supervise the technology.

Level 2: Partial Driving Automation. It is also known as Partial Driving Automation, pertains to vehicles equipped with advanced driving assistance systems (ADAS) capable of assuming control over steering, acceleration, and braking under specific conditions. However, despite the capability of Level 2 driver support to manage these fundamental driving tasks, it is a must for the driver to actively oversee the technology constantly.

Level 3: Conditional Driving Automation. It is a big leap from level 2 to level 3. It applies different kinds of driver assistance systems and AI tech. Drivers do not always supervise the technology so they can do their own activities. But they still need to be present and alert in case of emergency.

Level 4: High Driving Automation. It does not require any drivers to engage in the vehicle’s operation. It could be even without a steer wheel or pedals! Public transportation could greatly use the tech from destination A to B.

Level 5: Full driving Automation. It is the ultimate form of automation driving. The vehicles can drive all by themselves everywhere in any conditions of weather without drivers in different weather conditions.

Like coins have two sides: autonomous driving has its own advantages and disadvantages. Based on the analysis (Kerem Gülen,2022), people will benefit from autonomous driving since it will reduce accidents, improve the traffic flow by optimizing the routes, increase mobility for those people who are unable to drive because of their old age or disability, and in some way, it will reduce the emissions and make the positive influence of environmental preservation. On the other side, the disadvantages are also quite apparent such as: under some extreme conditions, people are uncertain about the reliability and safety of autonomous driving. It will also result in unemployment since not so many drivers are needed. Besides, legal issues would occur due to how to allocate the burdens for passengers and pedestrians in car accidents. Furthermore, since automatic drivers rely on the internet and cyber, it is significant to conquer those cyber security risks.

For traditional automakers, as vehicles become more and more automated, they are also facing new challenges: they need to reconsider their business models. And some are even being forced to invest more in software and transform themselves into tech companies in some way. To make themselves competitive in new markets, they are investing heavily in AI research and development, synergy strategic partnerships with tech companies, and acquiring even some startups. In addition, the shift to autonomous driving would make automakers explore new revenue streams such as mobility services or car-sharing businesses.


  1. Kerem Gülen, (November 14, 2023). Artificial Intelligence And Self-driving Cars Explained.
  2.  Jessica Shea Choksey and Christian Wardlaw, (May 05, 2021), Levels of Autonomous
    Driving, Explained. JD Power