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 # sdc-console-python 
 [Click here](https://github.com/alexeysp11/sdc-console-python/blob/master/README_RU.md) to read russian version of README file.    
-SDC stands for Self Driving Car.  
+This application is written in Python and is called `sdc-console-python`, where` sdc` stands for *Self Driving Car*.    
+It is designed as a **console application** that allows you to simulate individual modules of the *sensor system of a self driving car* for different models of vehicle behavior (i.e. when it doesn't move, when it moves at a constant speed, or, for example, when it changes the angle of its movement).    
+This is done by entering the required commands through the **console**.
+## Application modules
+At the moment, several modules have been written:
+- Kalman filter and Real-Time Locating System,
+- Fuzzy controller,
+- A neural network for handwritten digit recognition.
+### Kalman Filter and Real-Time Locating System
+**Kalman filter** allows you to reduce *measurement error* and more accurately estimate the *true value* of the measured parameter based on previously measured values.    
+In the original version, the **Kalman filter** generated empirical data for a *GPS receiver*, processed this data, drew a graph of the dependence of measurements and calculations and output the calculation results to the console.    
+It should be noted that the **Kalman filter** was guided by the constant location of the car, and also *process variance* was a constant parameter.    
+Later, I divided the tasks that the **Kalman filter** performed between different modules and made it so that the *process variance* parameter changes its value with each iteration depending on the calculated *aposteri error* at the previous iteration ("the larger the error value at the previous iteration, the larger step we have to take in the current iteration to reduce this error").    
+This allowed the **Kalman filter** to be used to add models with *constant speed* and *random acceleration*, and to add a *gyroscope*.
+### Fuzzy regulator
+One of the ideas on how to teach a car to independently calculate the speed of its movement may be the following algorithm:
+1. Set the starting and ending points of the path,
+2. Estimate the location of the car at the current time and mark it on the map,
+3. Using the map, calculate the distance that the car will drive in a straight line without turning,
+4. Since almost any driver tries to slow down when cornering, it makes sense to teach a car the same (i.e. teach a car to think as a human being in this situation). 
+You can copy this thinking model by using a **fuzzy controller**.    
+In a general sense, **fuzzy controller** allows the car to adjust its speed according to the idea that if the pivot point is far away, then you can drive at a high speed, and if it's close, then the speed should be slowed down.
+1. Determine the boundaries of such **terms** of the **linguistic variables** *distance* and *speed* as *"close distance"*, *"far distance"*, *"low speed"* and *"high speed"* in numerical values,
+2. Build rulebase in the following way: *"if the distance is close then speed should be low"* and *"if distance is far then speed should be high"* and so on,
+3. Apply the **fuzzy inference algorithm** (the most used is the **Mamdani algorithm**).    
+Thus, the task of the **fuzzy controller** is to take the distance to the next pivot point and return the speed corresponding to that distance.
+### Neural network for handwritten number recognition
+A huge amount of information required for self driving car control system is visual (for example, *road markings*, *road signs* and *traffic signals*).    
+Moreover, this kind of information cannot be obtained using the so-called traditional measurement methods using *radar*, *lidar*, *GPS*, *gyroscope* and *accelerometer*. A well-established solution for **computer vision** is currently **neural networks**.    
+Now I only added a **neural network algorithm for recognizing handwritten numbers (MNIST)** to this app.
+## Commands
+Now I will briefly talk about the commands you can use in this application.
+Commands are entered as follows:
+```
+app module --operation_mode
+```
+For example, if you need to simulate the *GPS* module, provided that the car is moving at a constant speed, then you need to enter `sdc gps --v`.    
+If you need to simulate the operation of a *gyroscope* under the condition that the angle at which the car is moving is unchanged, then you should enter `sdc gyro --const`, etc.    
+More information on commands you can be found by typing `sdc` or `sdc -commands`.    
+Service modules are called as follows:
+```
+app -service_module
+```
+For example, `sdc -commands` or` sdc -help`.