AI in Autonomous Vehicles
- 1. AUTONOMOUS VEHICLES AND AI A Self Driving vehicle is a car or some other vehicle which is capable of sensing it’s environment and moving with little or no human input.
- 2. Overview
- 3. WHAT IS ARTIFICIAL INTELLIGENCE ? AI is defined as the ability of a computer program or machine to think, learn and make decisions. In general use, the term means a machine which mimics human cognition. Deep learning technology, which is a technique for implementing machine learning (an approach to achieve AI), is expected to be the largest and the fastest-growing technology in the automotive AI market. It is currently being used in voice recognition, voice search, recommendation engines, sentiment analysis, image recognition and motion detection in autonomous vehicles.
- 4. How Does AI Work in Autonomous Vehicles? 01 Simulating the computer process with the human intelligence For eg - Whatever the human is able to do , think and react to particular situations, we are able to simulate the same thinking with the vehicles in the real time. 02 As the amount of information being fed into telematics systems grows, vehicles will be able to capture and share not only internal system status and location data but also the changes in its surroundings, all in real time.
- 5. AI Perception Action Cycle in Autonomous Vehicles A repetitive loop, called Perception Action Cycle, is created when the autonomous vehicle generates data from its surrounding environment and feeds it into the intelligent agent, who in turn makes decisions and enables the autonomous vehicle to perform specific actions in that same environment.
- 6. 3 main components of the Perception Cycle : 1. Component 1: In-Vehicle Data Collection & Communication Systems 2. Component 2: Autonomous Driving Platform (Cloud) 3. Component 3: AI-Based Functions in Autonomous Vehicles
- 8. Semantic Segmentation - The process of identifying and classifying objects from sensor data is known as semantic segmentation. DETAIL :- For human adults, they are trained to recognise patterns from birth – this is a slightly abstract concept; we see an image of a car and instinctively know what it is, even if we don’t know what exactly it is. For computers, however, this poses a significant challenge. The system has to recognise that, say, a small change in an object property could determine an absolutely different class at first.
- 9. This is an illustration of how an deep neural network classifies the different objects . For eg - Cars, Cycles Essentially, what it does is feed the data into the mass of interconnected neurons – each of which can have tens of thousands of connections to the others – and then compare the observed output to the target. Over successive iterations the network refines itself, changing the strength of certain connections until the input exactly matches the desired output
- 10. Is there more to come ? Artificial intelligence, especially neural networks and deep learning, have become an absolute necessity to make autonomous vehicles function properly and safely. AI is leading the way for the launch of Level 5 autonomous vehicles, where there will be no need for a steering wheel, accelerator or brakes.