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I'll tell you some knowledge shear about CARLA Simulator
These things all about Self-Driving Cars ðŸš¨ðŸš¨

The CARLA means (Car Learning to Act).

Simulations can be used to tune up performance, optimise a process, improve safety, testing theories, training staff and even for entertainment in video games! Scientifically modelling systems allows a user to gain an insight into the effects of different conditions and courses of action.🤞👨‍💻👩‍💻🧑‍💻

In simple terms how code and sensor really working in virtually...!
In the virtual process we create real words problem scenarios and with out any cost and Aviod damage things or parts

Simple way to explains total work flow:-

CARLA + simple controller for collecting data + training a neural network for steer control.

It's seems like risk free testing - everything & we create every weather & toughest senario

It's ending process of Self-Driving Cars 

Website:- https://carla.org/

History:-

CARLA was first officially released in 2017 at the Conference for Robot Learning (CoRL).
CARLA, a free, open-source simulator powered by Unreal Engine that has been designed from day one to support the development, training, and validation of autonomous driving systems. 






Carla simulator looks like this:- it's seems like a Game(gta)

Installation step by step:- windows Link, 

                                              Linux Link

Alternatives to CARLA:-

There are several open-source simulators for autonomous cars and/or racing, but very few with capabilities comparable to or greater than CARLA’s. Here’s a list of those that I’ve considered

- Autoware (Gazebo), 
- AirSim (UE4 & Unity), 
- TORCS (OpenGL)





Features 

  • Scalability via a server multi-client architecture: multiple clients in the same or in different nodes can control different actors.
  • Flexible API: CARLA exposes a powerful API that allows users to control all aspects related to the simulation, including traffic generation, pedestrian behaviors, weathers, sensors, and much more.
  • Autonomous Driving sensor suite: users can configure diverse sensor suites including LIDARs, multiple cameras, depth sensors and GPS among others.
  • Fast simulation for planning and control: this mode disables rendering to offer a fast execution of traffic simulation and road behaviors for which graphics are not required.
  • Maps generation: users can easily create their own maps following the OpenDrive standard via tools like RoadRunner.
  • Traffic scenarios simulation: our engine ScenarioRunner allows users to define and execute different traffic situations based on modular behaviors.
  • ROS integration: CARLA is provided with integration with ROS via our ROS-bridge
  • Autonomous Driving baselines: we provide Autonomous Driving baselines as runnable agents in CARLA, including an AutoWare agent and a Conditional Imitation Learning agent.
  • Quickstart: Getting started with CARLA is easy, this guide will show you how to install and run the simulator.
  • Actors: CARLA's actors are entities that interact within the simulation like vehicles, pedestrians and traffic signals. Get to know them here.
  • Sensors: CARLA boasts an impressive array of models of real world sensors like cameras, LIDAR and RADAR. The simulator also gives access to privileged information such as ground truth semantic segmentation and depth information.
  • Traffic Manager: CARLA's Traffic Manager controls NPCs to challenge your autonomous driving agent.
  • ROS bridge: CARLA's ROS bridge enables seamless connection with the Robot Operating System.
  • You're creating own race tracks and used it also LINK

Support sources of CARLA

See this image carefully

Supported Sensor's link:- Link

IN CARLA SIMULATOR WE CAN DO PID CONTROL SYSTEM TESTING & DEPLOY

Doubt's:-

MATLAB-How can you connect the CARLA autonomous driving simulator with simulink?

Ans:- The connection could be established using CARLA ROS Bridge and MATLAB ROS toolbox. MATLAB ROS toolbox will give you the ability to create customized ROS messages to exchange data between MATLAB/Simulink and CARLA Simulator via CARLA ROS Bridge. Once that connection is established, you will be able to send commands to the ego vehicle\CARLA simulation environment and read information from the said environment.

Visit the links below for more information:
https://carla.readthedocs.io/en/latest/
https://www.mathworks.com/products/ros.html
You need to use the Python API in Carla and Matlab. Then you run the simulation step by step and exchange the data between Carla and Matlab.

F.A.Q. :- Link

Dis-advantages of carla :-

- However, the current official CARLA does not provide a bus model that can offer the
opportunity to research self-driving buses
- huge computing power (must graphics card required)
- More Ram 8gb or 16gb

LAST WORDS:-
One thing to keep in the MIND Ai and self-driving Car technologies are very vast...! Don't compare yourself to others, You can keep learning..........

Competition And Innovation Are Always happening...!
so you should get really Comfortable with change...

So keep slowly Learning step by step and implement, be motivated and persistent



Thanks for Reading This full blog
I hope you really Learn something from This Blog

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I'M NATARAAJHU