Skip to main content

what is self driving car



A self-driving car (sometimes called an autonomous car or driverless car) is a vehicle that uses a combination of sensors, cameras, radar and artificial intelligence (AI) to travel between destinations without a human operator. To qualify as fully autonomous, a vehicle must be able to navigate without human intervention to a predetermined destination over roads that have not been adapted for its use.

Companies developing and/or testing autonomous cars include Audi, BMW, Ford, Google, General Motors, Tesla, Volkswagen and Volvo. Google's test involved a fleet of self-driving cars -- including Toyota Prii and an Audi TT -- navigating over 140,000 miles of California streets and highways.
AI technologies power self-driving car systems. Developers of self-driving cars use vast amounts of data from image recognition systems, along with machine learning and neural networks, to build systems that can drive autonomously.
The neural networks identify patterns in the data, which is fed to the machine learning algorithms. That data includes images from cameras on self-driving cars from which the neural network learns to identify traffic lights, trees, curbs, pedestrians, street signs and other parts of any given driving environment.
For example, Google's self-driving car project, called Waymo, uses a mix of sensors, Lidar (light detection and ranging -- a technology similar to radar) and cameras and combines all of the data those systems generate to identify everything around the vehicle and predict what those objects might do next. This happens in fractions of a second. Maturity is important for these systems. The more the system drives, the more data it can incorporate into its deep learning algorithms, enabling it to make more nuanced driving choices.

Comments

Post a Comment

Popular posts from this blog

What is Artificial Intelligence,its type and applications

AI is a part of Computer Science.AI is anything that makes machine more intelligent. AI is a technology which can not replace human intelligence but rather it can extend human capabilities.Now a days AI is most wanted and powerful technology.Every industry wants to have its AI system because it can process very large amount of data in less time. How does AI learn ? The intelligence which machine having is only provided by us.So basically we provide to machine  ability to examine and create machine learning models based on inputs and desired output and we do this based on supervised learning,unsupervised learning and reinforcement learning. Types of AI based on Strength Weak or Narrow AI- Narrow AI is that applied on specific domain.It can perform specific task but can not learn new things its own.It can only make decision based on programmed algorithms and trained data.For example AI powered based searches,virtual assistant,self driving cars,language translato...
4 comments
Read more

ANN in depth

Artificial Neural Network Layers Artificial Neural network is typically organized in layers. Layers are being made up of many interconnected ‘nodes’ which contain an  ‘activation function’.  A neural network may contain the following 3 layers: a. Input layer The purpose of the input layer is to receive as input the values of the explanatory attributes for each observation. Usually, the number of input nodes in an input layer is equal to the number of explanatory variables. ‘input layer’ presents the patterns to the network, which communicates to one or more ‘hidden layers’. The nodes of the input layer are passive, meaning they do not change the data. They receive a single value on their input and duplicate the value to their many outputs. From the input layer, it duplicates each value and sent to all the hidden nodes. b. Hidden layer The  Hidden layers  apply given transformations to the input values inside the network. In this, incoming arcs that go...
Post a Comment
Read more

5 machine learning applications

Artificial Intelligence (AI) is everywhere. Possibility is that you are using it in one way or the other and you don’t even know about it. One of the popular applications of AI is Machine Learning (ML), in which computers, software, and devices perform via cognition (very similar to human brain). Herein, we share few examples of machine learning that we use everyday and perhaps have no idea that they are driven by ML. 1. Virtual Personal Assistants Siri, Alexa, Google Now are some of the popular examples of virtual personal assistants. As the name suggests, they assist in finding information, when asked over voice. All you need to do is activate them and ask “What is my schedule for today?”, “What are the flights from Germany to London”, or similar questions. For answering, your personal assistant looks out for the information, recalls your related queries, or send a command to other resources (like phone apps) to collect info. You can even instruct assistants for certain tasks l...
Post a Comment
Read more