How Does AI Work in Autonomous Vehicles?

AI has become a popular word tech industry, does it actually work in autonomous vehicles?

To understand the AI, first, we need to understand the human viewpoint of driving a vehicle with the use of sensory functions such as vision and sound to watch the road and the other vehicles on the road. When we halt at a red light or wait for a pedestrian to cross the road, we are using our memory to make these quick decisions. The years of driving practice lead us to look for the little things that we face often on the roads — it could be a nice route to the home that might avoid the bumps in the road.

We are building autonomous vehicles that drive themselves, but we want them to drive as human drivers do. That means we need to equip these vehicles with the sensory, cognitive functions (memory, logical thinking, decision-making, and learning) and administrative capabilities that humans use to drive vehicles on the roads. The automotive industry is continuously developing to produce this exactly over the last few years.

AI provides the computational requirements of robotaxis that help in perceiving the world through high-resolution, 360-degree surround cameras and lidars, localizing the vehicle within centimeter accuracy, tracking vehicles and people around the car, and planning a safe route to the destination. All this processing must be accomplished with multiple levels of repetition to ensure the greatest level of safety.

Garner insight says, by 2020, approximately 250 million cars will be correlated with each other and the infrastructure around them through various V2X (vehicle-to-everything communication) systems. As the amount of information being fed into IVI (in-vehicle infotainment) units or telematics systems grows, vehicles will be able to capture and share not only internal system status and location data according to its surroundings, all in real time. Autonomous vehicles are being fitted with cameras, sensors and communication systems to enable the vehicle to create massive amounts of data which enables the vehicles to see, hear, think and make decisions just like human drivers do.

AI Perception-Action Cycle in Autonomous Vehicles

A constant loop, called Perception-Action Cycle, is formed when the autonomous vehicle produces data from its surrounding environment and feeds it into the intelligent agent, who makes the decisions and allows the autonomous vehicle to do specific operations in that same environment. The below picture depicts the data flow in autonomous vehicles.

The whole process is divided into the following three components:

Component 1: In-Vehicle Data Collection & Communication Systems

In Autonomous vehicles, Numerous sensors, radars, and cameras are fitted to generate massive amounts of environmental data. All of these create the Digital Sensorium, by which the autonomous vehicle can observe, discover and feel the road, infrastructure, other vehicles, and other objects on/near the road, just like a human driver, It will pay attention to the road while driving. This data is then processed with super-computers and data communication systems are used to securely communicate valuable information (input) to the autonomous driving cloud platform. The autonomous vehicle first reaches the driving context and/or the particular driving circumstances to the Autonomous Driving Platform.

Component 2: Autonomous Driving Platform (Cloud)

The Autonomous Driving Platform in the cloud contains an intelligent agent which makes use of AI algorithms to make meaningful decisions. It serves as the control system or the brain of the autonomous vehicle. This intelligent agent is also related to a database which acts as a memory where prior driving experiences are saved. This abundant data of the previous driving experiences will help the intelligent agent to take decisions for inputs from the autonomous vehicle. The autonomous vehicle now knows exactly what to do in this driving environment and/or particular driving situation.

Component 3: AI-Based Functions in Autonomous Vehicles

Based on intelligent agent decisions, the autonomous vehicle detects the objects on the road, manage the traffic without human intervention and goes to the destination safely. Autonomous vehicles are outfitted with AI-based functional systems such as voice and speech recognition, signal controls, eye tracking, and other systems to monitor the driving, virtual assistance, mapping, and safety systems. These functions work on the decisions provided by the intelligent agent in the Autonomous Driving Platform. These systems have built to provide great user experience for customers and keep them safe on the roads. The driving experiences generated from every ride is recorded and stored in the database to help the intelligent agent make much more accurate decisions in the future.

This data circle, called Perception-Action Cycle, happens repetitively. The more the number of Perception-Action Cycles happens, that much more intelligent the agent becomes, resulting in a higher accuracy of making decisions, especially in complex driving situations. The driving experiences are based on the number of autonomous vehicles connected to the central platform. These driving experiences empower the intelligent agent to make decisions based on data generated by multiple autonomous vehicles.

Artificial intelligence, especially neural networks and deep learning, have become an absolute necessity to make autonomous vehicles function properly and safely. AI is driving the way for the launch of Level 5 autonomous vehicles, where there will be no necessity for a controlling the steering, accelerator or brakes.