Project 1 (Mini Project on Vehicle Direction Detection

First we have to design this data in the Simulink Data Dictionary that is the form of SLDD.

SLDD CREATION:

The SLDD data files are related to the MATLAB/Simulink. Mathworks Simulink is a multidomain simulation and Model-Based Design for dynamic systems. The SLDD file stores some kind of data used by MATLAB. The following procedure shows how to create and add data to the SLDD file.

• To create a SLDD file, Open the simulink model and go to Modeling section.
• Then select Link to Data Dictionary option from Modeling section.

After clicking on the Link to Data Dictionary,

• Click on New and then save with a name. After saving the new SLDD file, uncheck the enable model access to base workspace because as it is new file there is no data to add workspace. If it is already created one then we can click on enable model access to base workspace.

After saving the file the above popup window will closes.

• To open the SLDD file go to the Modeling section and then select Model explorer. Which is showing in the following figure.

After clicking on the Model explorer, the following window will opens. Where we can see our created SLDD file at left side of the window if we extend that will be able to see Design Data. By clicking on that we can add our given signals or parameters.

• I have given the name as sldd_direction to the SLDD file, if we extend the file design data option appears as shown in the following figure.

If we see at the top left side of the window, there are few option like file, edit, view, tools, add and help. If we click on add button it will show some options as shown in the following figure.

• From the options we can select our variable according to its natuure.
• If it is a signal then will select simulink signal if it is constant will select simulink parameter like that.

Now enter all signals and parameters according to the given signals and calibration data.

• To avoid the errors just copy paste the given signal/calibration name.
• And fill all the respective details accordingly.

After designing the SLDD file, right click on the SLDD form here it is saved as sldd_direction. Righ click on it and save changes. Which is shown through following figure.

• After saving the data we can close the model explorer window and we can start modelling.

MODELING:

The modeling can be done according to the given requirements. So as we have two given requirements, we are taking a main subsystem first and naming it as Vehicle_Direction.

• Added a subsystem to the empty simulink model. And named it as Vehicle_Direction.
• Taken its inports and outports according to the given data.

After making a subsystem, double click on it to model the given requirements. The following figure shows the two subsystems under the Vehicle_Direction subsystem.

• These two subsystems are named as Requirement1 and Requirement2.
• The inports and outports are considered according to the given data.
• Now will see how these subsystems are modeled.

Requirement - 1:

• Steering wheel input as yaw rate (Signal name: SteeringWheel_YawDegreeInput) is the input for this system.
• This is compared against 3 angular values, one each for left turn, right turn & straight drive (Calibration Values: Right_Turn_AngularLimit, Left_Turn_AngularLimit, Straight_Drive_Steering_Angle) to say which specific direction the steering wheel is turning towards.
• Use switch blocks to compare & develop this requirement. Keep this requirement in a subsystem & output of this requirement is a local signal (Signal Name: Vehicle_Turn_Status).

The signal names and calibration values are copy pasted to avoide the errors. Because we have taken exact values in SLDD form so to match them again i have did the same. All the ports and blocks are named according to the requirement. To compare the three angular values we have taken the compare to zero blocks and to give the output after comparison we have taken switch blocks. The following figure shows the model under requirement1 subsystem.

Requirement – 2:

• Keep this requirement as a separate subsystem. Inputs to this requirement are local signal from requirement 1 (Signal Name: Vehicle_Turn_Status) & an input signal from camera (Signal Name: CameraInput_RoadSign), which confirms the occurrence of a road sign.
• Signal Vehicle_Turn_Status is compared against calibration values (Calibration Values: RightTurn_RoadSign, LeftTurn_RoadSign, Straight_RoadSign), if each of them is found equal, then each of the three corresponding output is compared against the camera input signal,
• Using a logical operator block, only one among them is finally given as output signal (Signal Name: Vehicle_Direction_Indicator).

Here also to avoid the errors i have copy pasted the signal and calibration values given in the table. In req.2 we have two inputs as named above. To compare the input1 with given 3 calibration values i have taken relational operator block. To give output finally one among them AND operator block is taken. Mux block is used to give single output and to avoid the errors we have taken signal conversion block. To avoid the lines crossover taken from and go to blocks blocks. The following figure shows the model under requirement2 subsystem.

RESOLVING & PROPAGATING:

By resolving and propagrating the signals we can migrate design attribbutes from existing simulink signal objects into the model by using block parameters and signal properties here in the model explorer we have designed the attributes in SLDD form. To force signal resolution for a signal in a MATLAB Function block, follow these steps:

• In the Simulink model, right-click the signal line connected to the respective input or output that you want to resolve and select Properties from the context menu.
• In the Signal Properties dialog, enter a name for the signal that corresponds to the signal object.

To propagate the signal, right click on it then select properties. And tick the option show propagated signals. Which is shown in the following figure.

or

Double click on signal and type '<>' then click on enter button in the keyboard. Then it will appears as shown below.

Once the signal is resolved then noo need to resolve again just propagate the signal.

To perform Tagging first we have to create a word file with all details reagarding about the model we are creating. Tagging enables us to view the procedure which is used to build the model or to know more details about the designed model. To tag the given requirement blocks the followinng procedure has been followed.

• First we need select the respective heading in the word file. Like in the followinng figure we can see that Requirement1 is a heading in which the procedure to build the model has been given.
• The word file which is created must be saved in the same folder of our simulink model.

In the above figure it show the selection of word, now to tag this to the subsystem:

• Right click on the respective subsystem, as we have selected a word regarding about requirement1 we are right clicking on 1 subsyetm.
• Go to Requirements option from the context. In requirements select Link to selection in word.
• If we click on that it is automatically tagged to the word in word file.

Now will be able to see the tagging. Repeat same procedure like right click on subsystem go to requirements and from the options, the top 1. represents the word which is tagged to the subsystem.

• To know about the subsytemm building or any other details which are written in the word file, click on that 1st option it will take you to the word file requirement1 section.

Repeat the same procedure for Requirement2 subsystem also. Select the relatable heading in the word file and do the same procedure.

• After the proccedure will be able to the Requiremet2 word which is tagged at the top of requirements section.
• Which is shown in the following figure.

SOLVER SETTINGS:

Solver settings are important to simulate the model. To open the solver setings, go to the Modeling section which is at the top of simulink window. And select the Model settings under the modeling section. Which is shown in the following figure.

After clicking on model settings the following window will appears. The window presents the configuration of the parameters in our simulink mode.

• In the configuration window, click on solver to model the solver parameters.
• Now change the type to Fixed-step, Solver to discrete(no continuous states) and take sample time as 0.01sec. Then click Ok.

In the same configuration window there another settings to model, which is Code generation. Click on code generation,

• Choose the system targer file as ert.tlc (Embedded coder) by clicking on the browse option.
• Then click on Ok and close the window.

MAB GUIDEINES:

The MAB (MathWorks Advisory Board) Guidelines are a set of modeling guidelines developed by an independent industry working group for the usage of MATLAB, Simulink, Stateflow and Embedded Coder. The guidelines are the culmination of years of engineering expertise and best practices for developing, maintaining and documenting control algorithm models used in the development of production software.

• To perform the MAB guidelines test on our simulink model, go to modeling section and select Model Advisor which is at the top left corner of the window.
• You can use the Model Advisor to verify compliance of your model with the MathWorks Advisory Board (MAB) guidelines.

By clicking on the Model Advisor, a window will ask us to confirmation if we click on Ok then it will opens a window which is shown in the following figure.

• In the Model advisor there are number of guidelines, among them will select only Modeling Standards fro MAB.
• If we expand the section will be able to see which are tested under the MAB guidelins. If we again expand there will be many sub sections in each section.
• After selecting MAB guidelines, click on Run Selected checks.
• Then it asks again for confirmation, click on continue. Then the testing will begins. It takes time to perform the guidelines test.

After the MAB guidelined test completion, it should be mandatory that 0 fail conditions. If any fail conditions are there rectify them and again make them to 0. The warnings are permittable to some limit.

• After getting 0 fails click on Generate report. This report will gives all data about the smulink model we have created.

After clicking Generate report in the above window, a popup window will appears as shown in the followinng figure.

• It shows the directory, at where the report is going to save. It will save in the same folder of our simulink model.
• Give a name to the report. Then click on OK.

After clicking on Ok. It will save in the folder and opens as shown in the followig diagram.

• The report shows all the checks performed under MAB guidelines.

C CODING:

Now we are converting all our model in terms of C Code. To create C code of our simulink model, follow the procedure as explained below.

• Go to the Apps section which is at top of the window.
• Under Apps section, click on Embedder coder which is shown in the followinng figure.

After clicking on EMbedded codel option, aother window will creates as C CODE, which is shown in the following figure.

• Go to the C Code section, and click on Build option to build the code.

After clicking on Build it will generate the C Code of our simulink as shown inn the following figure.

• The C code shows all the data of our simulink model. The C code file is also saved in the same folder of our simulink model.

Generated C CODE:

/*
 * File: Direction_detection.c
 *
 * Code generated for Simulink model 'Direction_detection'.
 *
 * Model version                  : 1.31
 * Simulink Coder version         : 9.5 (R2021a) 14-Nov-2020
 * C/C++ source code generated on : Sat May 14 17:59:26 2022
 *
 * Target selection: ert.tlc
 * Embedded hardware selection: Intel->x86-64 (Windows64)
 * Code generation objectives: Unspecified
 * Validation result: Not run
 */

#include "Direction_detection.h"
#include "Direction_detection_private.h"

/* Exported data definition */

/* Definition for custom storage class: ExportToFile */
boolean_T Vehicle_Direction_Indicator[3];/* '/Signal Conversion' */

/* Const memory section */
/* Definition for custom storage class: Const */
const int16_T LeftTurn_RoadSign = -120;/* Referenced by: '/Constant1' */
const int16_T Left_Turn_AngularLimit = -120;/* Referenced by: '/Constant1' */
const int16_T RightTurn_RoadSign = 30; /* Referenced by: '/Constant' */
const int16_T Right_Turn_AngularLimit = 30;/* Referenced by: '/Constant' */
const int16_T Straight_Drive_Steering_Angle = 0;/* Referenced by: '/Constant2' */
const int16_T Straight_RoadSign = 0;   /* Referenced by: '/Constant2' */

/* Real-time model */
static RT_MODEL_Direction_detection_T Direction_detection_M_;
RT_MODEL_Direction_detection_T *const Direction_detection_M =
  &Direction_detection_M_;

/* Model step function */
void Direction_detection_step(void)
{
  /* local block i/o variables */
  int16_T Vehicle_Turn_Status;

  /* Outputs for Atomic SubSystem: '/Vehicle_Direction' */
  /* Switch: '/Switch' incorporates:
   *  Constant: '/Constant'
   *  Constant: '/Constant'
   *  Inport: '/SteeringWheel_YawDegreeInput'
   *  RelationalOperator: '/Compare'
   *  RelationalOperator: '/Compare'
   *  Switch: '/Switch1'
   */
  if (SteeringWheel_YawDegreeInput > 0) {
    /* Switch: '/Switch' incorporates:
     *  Constant: '/Constant'
     */
    Vehicle_Turn_Status = Right_Turn_AngularLimit;
  } else if (SteeringWheel_YawDegreeInput == 0) {
    /* Switch: '/Switch1' incorporates:
     *  Constant: '/Constant2'
     *  Switch: '/Switch'
     */
    Vehicle_Turn_Status = Straight_Drive_Steering_Angle;
  } else {
    /* Switch: '/Switch' incorporates:
     *  Constant: '/Constant1'
     *  Switch: '/Switch1'
     */
    Vehicle_Turn_Status = Left_Turn_AngularLimit;
  }

  /* End of Switch: '/Switch' */

  /* SignalConversion: '/Signal Conversion' incorporates:
   *  Constant: '/Constant'
   *  Constant: '/Constant1'
   *  Constant: '/Constant2'
   *  Inport: '/CameraInput_RoadSign'
   *  Logic: '/AND'
   *  Logic: '/AND1'
   *  Logic: '/AND2'
   *  RelationalOperator: '/Relational Operator'
   *  RelationalOperator: '/Relational Operator1'
   *  RelationalOperator: '/Relational Operator2'
   */
  Vehicle_Direction_Indicator[0] = ((Vehicle_Turn_Status == RightTurn_RoadSign) &&
    CameraInput_RoadSign);
  Vehicle_Direction_Indicator[1] = ((Vehicle_Turn_Status == LeftTurn_RoadSign) &&
    CameraInput_RoadSign);
  Vehicle_Direction_Indicator[2] = ((Vehicle_Turn_Status == Straight_RoadSign) &&
    CameraInput_RoadSign);

  /* End of Outputs for SubSystem: '/Vehicle_Direction' */
}

/* Model initialize function */
void Direction_detection_initialize(void)
{
  /* (no initialization code required) */
}

/* Model terminate function */
void Direction_detection_terminate(void)
{
  /* (no terminate code required) */
}

/*
 * File trailer for generated code.
 *
 * [EOF]
 */

CONCLUSION:

The Vehicle Direction Detection is modeled as per the given requirements, all the signals and calibrated values are defined in the Simulink Data Dictionary(SLDD). All input and output signals are resolved and propagated. Model Advisory check is done with MAB guidelines and there is 0 fail conditions. Since there are no errors in Model Advisory report C Code has been generated by using Embedded coder. MIL and SIL tests are also perfromed sucessfully.