How will artificial intelligence improve autonomous vehicle driving?

Autonomous vehicles rely heavily on software-based systems and developing these smart, reliable, and error-prone systems is a highly complex task. It is also expensive, and error-prone. A key reason for this difficulty is that the sheer complexity of the systems keeps growing, making it increasingly difficult for human minds to form a comprehensive picture of all relevant elements and behaviors of the system and its environment.

To mitigate this difficulty, research in the field of artificial intelligence (AI) has been promoting a different approach to programming. Algorithms are given training examples, typically pairs of inputs and outputs, from which they automatically extrapolate a software implementation rather than having humans provide the logic. The learned model is then capable of generalizing and producing desirable outputs, even for previously unknown inputs. AI is becoming increasingly scalable and efficient, and in the coming decade more and more real-world vehicles will be powered by AI.

What is AI?

It is defined as a technology that enables computers to think, learn, and make decisions. Generally, the term refers to machines that mimic human cognitive processes.

Autonomous vehicles and AI

New vehicles will feature AI-based systems, especially in these two categories:

  1. Human-machine interfaces for information technology, including speech recognition, gesture recognition, eye tracking, driver monitoring, virtual assistance, and natural language interfaces.
  2. Sensor-based engine control units (ECUs) and advanced driver assistance systems (ADAS) for autonomous vehicles, such as camera-based machine vision systems, radar-based detection units, and driver condition assessment systems.

Autonomous vehicles are fitted with cameras, sensors, and communication systems that generate massive amounts of data that, which when combined with artificial intelligence, enable autonomous vehicles to see, hear, think, and act like humans.

Autonomous Vehicles: The AI Perception-Action Cycle

As the autonomous vehicle generates data from its surroundings and feeds it to the intelligent agent, a repetitive loop called the Perception-Action Cycle is created. This allows the autonomous vehicle to perform specific actions in the same environment by making decisions and enabling the intelligent agent to act.
Let's break down this process:

  1. Data collection and communication systems for vehicles
  2. Autonomous vehicles equipped with sensors, radars, and cameras. Through these sensors, autonomous vehicles can see, hear and feel the road, infrastructure, other vehicles, and objects on/near the road, just as a human driver would do while driving. Massive amounts of data are generated by the equipment in these vehicles. After this data is gathered, it is processed with supercomputers and securely communicated to the autonomous driving cloud platform using data communication systems.

  3. Cloud-based platform for autonomous driving
  4. A cloud-based autonomous driving platform contains an intelligent agent that uses AI algorithms to make meaningful decisions. It serves as the autonomous vehicle's control policy or brain. A database is also connected to this intelligent agent, which acts as a memory for past driving experiences. With this knowledge, the autonomous vehicle knows exactly what to do in various situations.

  5. Vehicles with AI-based functions
  6. Autonomous vehicles can detect objects on the road and maneuver through traffic without human intervention based on the decisions made by the intelligent agent. Several AI-based functionalities are also being integrated into autonomous vehicles, such as voice recognition, gesture controls, eye tracking, mapping systems, and safety systems.

    Every ride is recorded and stored in a database to help the intelligent agent make more accurate decisions in the future.

    This data loop, called Perception-Action Cycle, occurs repeatedly. With a greater number of Perception-Action Cycles, the intelligent agent becomes more intelligent, which results in a higher level of decision accuracy, especially when driving on complex roads.

The impact of AI on driving safety

Data from current manufacturers cites four years as the time required to design and produce a new vehicle. As far as computer technology is concerned, this is an extremely long time. Consequently, cars quickly lose their technological edge.

With AI, drivers gain access to the latest developments in driver safety. The use of artificial intelligence also allows drivers to obtain real-time information on fuel usage, vehicle location, speed, and behavior. Drivers can use voice commands, instead of using their phone interfaces, for tasks such as locate nearby restaurants or gas stations, get any information from the internet, and the like. As a result of artificial intelligence, road safety will be improved, reducing the overall number of accidents. Auto braking and the ability to recognize road signs will also be enhanced by artificial intelligence.

Artificial intelligence will improve vehicle safety and connectivity for all. It will improve driver habits and lead to a better future.

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