Project 1 (Mini Project on Vehicle Direction Detection

VEHICLE DIRECTION DETECTION

Objective:

• Development of MATLAB Simulink model as per given requirement.
• Tag the requirements to the simulink model; tagging requirement 1 & requirement 2 to their corresponding subsystems.
• MBD compliant changes, Data Dictionary creation & code generation is added advantage, and that is not scope of this project.
• If choosing code generation, Storage class for Input signals: ImportedExtern; Storage class for Output signal: Export to File; Storage class for local signals: localizable; Storage class for calibration signals: Const.
• Choose sample time for all signals as 0.01seconds.

Overview:

Identifying the direction of the vehicle is one of the important & diverse features in Autonomous driving & Advanced Driver Assistance Features. This particular sub-feature of identifying the direction of vehicle is basically identifying the direction the vehicle is taking based on the camera input.

Camera reads the road signs & stores into its memory with unique values for left turn, right turn & straight drive. Depending on the direction it is taking, final indication is given to the driver – as an indication if he is driving in the recommended direction or not.

Vehicle Direction Determination can also be coupled along - side features like GPS systems to identify whether the vehicle is reaching its destination in an optimized manner. This sub feature can also be used along with Lane Detection, Highway Warning, Ramp Entry / Exit in Wrong Way Detection etc.

Signals & Calibration Data List:

The following table shows the given signals and calibration data list.

Signal / Calibration Name	Signal Type	Data Type	Dimension	Min	Max	Initial Value	Units
SteeringWheel_YawDegreeInput	Input	Int16	1	-180	180	-	Deg
CameraInput_RoadSign	Input	Boolean	1	0	1	-	-
Vehicle_Turn_Status	Local	Int16	1	-180	180	-	Deg
Right_Turn_AngularLimit	Calibration	Int16	[1 1]	-180	180	30	Deg
Left_Turn_AngularLimit	Calibration	Int16	[1 1]	-180	180	-120	Deg
Straight_Drive_Steering_Angle	Calibration	Int16	[1 1]	-180	180	0	Deg
RightTurn_RoadSign	Calibration	Int16	[1 1]	-180	180	30
LeftTurn_RoadSign	Calibration	Int16	[1 1]	-180	180	-120
Straight_RoadSign	Calibration	Int16	[1 1]	-180	180	0
Vehicle_Direction_Indicator	Output	Boolean	1	0	1	-	-

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. Which is shown in the following figure.

After clicking on the Link to Data Dictionary, the following popup window will appears which ask us about data dictionary. If already created and to open SLDD, click on browse option and then select the respective file then click on ok. Here we are creating the new SLDD file so,

• 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 data_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 nature.
• If it is a signal then will select simulink signal if it is constant will select simulink parameter.

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.
• The given details are: Signal type, Data type, Dimension, Min & Max value, Storage class and Value for calibration parameter.
• The following figure shows the all designed data according to the given table.

This section of the dictionary stores variables that are visible to the Simulink models that reference this dictionary. These variables can be used to parameterize model, block and signal data.

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 creating 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 file so to match them again i 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 requirement_1 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. OR 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.

Requirement_2 subsystem Simulink model is shown in the following figure after resolving and propagation of signals.

• Inputs are propagated from the subsystem and output is resolved as it is the intial condition of output of the requirement_2 block.

TAGGING:

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 Requirement_1 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 requirement_1 we are right clicking on 1st 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 requirement_1 section.

Repeat the same procedure for Requirement_2 subsystem also. Select the relatable heading in the word file and do the same procedure.

• After the proccedure will be able to the Requiremet_2 word which is tagged at the top of requirements section.
• Which is shown in the following figure.

SOLVER SETTINGS:

To open the solver settings, go to the Modeling section which is at the top of simulink window. And select the Model settings under the modeling section.

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.
• These settings are shown in the following figure.

• In the same row set the Diagnostics settings change from none to error or warning.

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 for 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.

Then click report to generate report.

• 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.

• Rightclick on the subsystem and select block parameters(subsystem)

• select treat as atomic unit and apply.

• Next right click on the subsystem and select c\c++code and click on generate s function.

• Code will be generated as shown in the figure and the file will be automatically saved in your folder.

Generated C/C++Code:

/*
 * Event Support License -- for demonstration use and event support.  Not
 * for government, research, commercial, or other organizational use.
 *
 * File: project.c
 *
 * Code generated for Simulink model 'project'.
 *
 * Model version                  : 1.15
 * Simulink Coder version         : 9.7 (R2022a) 13-Nov-2021
 * C/C++ source code generated on : Thu May 18 12:18:43 2023
 *
 * Target selection: ert.tlc
 * Embedded hardware selection: Intel->x86-64 (Windows64)
 * Code generation objectives: Unspecified
 * Validation result: Not run
 */

#include "project.h"
#include "rtwtypes.h"
#include "project_private.h"

/* Exported data definition */

/* Const memory section */
/* Definition for custom storage class: Const */
const int16_T LeftTurn_RoadSign = -120;/* Referenced by: '<S3>/Constant1' */
const int16_T Left_Turn_AngularLimit = -120;/* Referenced by: '<S2>/Constant2' */
const int16_T RightTurn_RoadSign = 30; /* Referenced by: '<S3>/Constant' */
const int16_T Right_Turn_AngularLimit = 30;/* Referenced by: '<S2>/Constant' */
const int16_T Straight_Drive_Steering_Angle = 0;/* Referenced by: '<S2>/Constant1' */
const int16_T Straight_RoadSign = 0;   /* Referenced by: '<S3>/Constant2' */

/* External outputs (root outports fed by signals with default storage) */
ExtY_project_T project_Y;

/* Real-time model */
static RT_MODEL_project_T project_M_;
RT_MODEL_project_T *const project_M = &project_M_;

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

  /* Outputs for Atomic SubSystem: '<Root>/Vehicle_Direction' */
  /* Switch: '<S2>/Switch' incorporates:
   *  Constant: '<S4>/Constant'
   *  Constant: '<S5>/Constant'
   *  Inport: '<Root>/Inport'
   *  RelationalOperator: '<S4>/Compare'
   *  RelationalOperator: '<S5>/Compare'
   *  Switch: '<S2>/Switch1'
   */
  if (SteeringWheel_YawDegreeInput >= 0) {
    /* Switch: '<S2>/Switch' incorporates:
     *  Constant: '<S2>/Constant'
     */
    Vehicle_Turn_Status = Right_Turn_AngularLimit;
  } else if (SteeringWheel_YawDegreeInput == 0) {
    /* Switch: '<S2>/Switch1' incorporates:
     *  Constant: '<S2>/Constant1'
     *  Switch: '<S2>/Switch'
     */
    Vehicle_Turn_Status = Straight_Drive_Steering_Angle;
  } else {
    /* Switch: '<S2>/Switch' incorporates:
     *  Constant: '<S2>/Constant2'
     *  Switch: '<S2>/Switch1'
     */
    Vehicle_Turn_Status = Left_Turn_AngularLimit;
  }

  /* End of Switch: '<S2>/Switch' */

  /* Outport: '<Root>/Vehicle_Direction_Indicator' incorporates:
   *  Constant: '<S3>/Constant'
   *  Constant: '<S3>/Constant1'
   *  Constant: '<S3>/Constant2'
   *  Inport: '<Root>/CameraInput_RoadSign'
   *  Logic: '<S3>/AND'
   *  Logic: '<S3>/AND1'
   *  Logic: '<S3>/AND3'
   *  Logic: '<S3>/OR'
   *  RelationalOperator: '<S3>/Relational   Operator'
   *  RelationalOperator: '<S3>/Relational  Operator'
   *  RelationalOperator: '<S3>/Relational Operator'
   */
  project_Y.Vehicle_Direction_Indicator = (((Vehicle_Turn_Status ==
    RightTurn_RoadSign) && (*CameraInput_RoadSign)) || ((Vehicle_Turn_Status ==
    LeftTurn_RoadSign) && (*CameraInput_RoadSign)) || ((Vehicle_Turn_Status ==
    Straight_RoadSign) && (*CameraInput_RoadSign)));

  /* End of Outputs for SubSystem: '<Root>/Vehicle_Direction' */
}

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

/* Model terminate function */
void project_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.