Project 1 (Mini Project on Vehicle Direction Detection

Mini Project - Vehicle Direction Determination

General 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.

Objective of Mini Project:

1. Development of MATLAB Simulink model as per requirement.
2. Tag the requirements to the simulink model; tagging requirement 1 & requirement 2 to their corresponding subsystems is fine.
3. MBD compliant changes, Data Dictionary creation & code generation is added advantage, and that is not scope of this project.
4. 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.
5. Choose sample time for all signals as 0.01s

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).

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).

Signals & 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	-	-

Answers: -

AIM: -

To Study & Create Vehicle Direction Detection mini-Project, provided with the information as given,

Processor: -
Fistly, We can create a MATLAB Simulink Model as per given information, in this model create a two subsystem as per requirement

SLDD: -

-Fistly, we can go modelling - modelling setting and click on it -go solver – solver selection type are ‘Fixed-step’ & solver are ‘Discrete’ and Fixed-step size are 0.01 s.
-then go to the code generation – Browse – select Embedded code and click ok.

-again go to modelling – Link to Data Dictionary – External data – new -ok. create new SLDD file and link it.
-update all the given data in the SLDD file: -
Signals & 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	-	-

-SLDD File are creating & updating show in image

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).

Create Subsystem Requirement: -

-Open the Simulink and Create the new Black Model.
-Create ‘Subsystem’ go inside the subsystem gives one of the input is ‘SteeringWheel_YawDegreeInput’
-next compare 3 angular values, create three constant Block and gives name : Right_Turn_AngularLimit, Left_Turn_AngularLimit, Straight_Drive_Steering_Angle
-Then Use Switch Blocks to compare & develop the model & give the output are Vehicle_Turn_Status.

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).

Create Subsystem Requirement: -

-Create another subsystem & go inside, this system are two input one is Vehicle_Turn_Status and other are camera signal ‘CameraInput_RoadSign’.

-Create three constant blocks for the calibration values & this value compare to the Vehicle_Turn_Status. Comparison of this signal, use the ‘Relational Operator’ Block sign are(==).
-then camera input signal ‘From’ & ‘Goto’ Block used

-all camera output signal are connected to the logical operator ‘AND’ block, this block connected to the logical operator OR block and they gives one output Vehicle_Turn_Status.

Subsystem: - 1 & 2

Simulink Model Vehicle Direction Determination: -

the inputs and output signals are resolved so the signals will take the values from sldd and pass them to the logical blocks. Otherwise, it may take some junk values if it is unresolved

Model Update.

The model update is done by Ctrl-D. this is done to check for any static errors. If there are no errors coming the model is working fine without any errors

Model Advisor Reports: -
-go to the Modeling – model Advisor – Select model simulink for JMAAB
-Then click ‘Run selected checks’
-after running they can indicate the Summary: pass, Fail, Warning & Not Run.
-we can see the pass :115 and warning:10 and other two are zero.
-correction of the wrong warning signal and run it again.
-then generate the Model advisor report, we can see click on this link and download the reports.

We can see the Model Advisor Reports
-in this model advisor reports are download click on print option.

Code Generation: -
-generate the coding, we can go to the ‘APPS’ – Select the Embedded Code – C Code – Build option – Select Generation Code option.
-Then Generate the code.
-Next select ‘open Report’ option, then pop up the new page.

-see the page for code generation, we can go and click on ‘ert_main.c’ option and download the the file.

Generated Code: -

/*

* File: Vehicle_Direction_Determinatio.c

*

* Code generated for Simulink model 'Vehicle_Direction_Determinatio'.

*

* Model version : 1.5

* Simulink Coder version : 9.5 (R2021a) 14-Nov-2020

* C/C++ source code generated on : Mon Aug 15 00:02:37 2022

*

* Target selection: ert.tlc

* Embedded hardware selection: Intel->x86-64 (Windows64)

* Code generation objectives: Unspecified

* Validation result: Not run

*/

#include "Vehicle_Direction_Determinatio.h"

#include "Vehicle_Direction_Determinatio_private.h"

/* External inputs (root inport signals with default storage) */

ExtU_Vehicle_Direction_Determ_T Vehicle_Direction_Determinati_U;

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

ExtY_Vehicle_Direction_Determ_T Vehicle_Direction_Determinati_Y;

/* Real-time model */

static RT_MODEL_Vehicle_Direction_De_T Vehicle_Direction_Determinat_M_;

RT_MODEL_Vehicle_Direction_De_T *const Vehicle_Direction_Determinat_M =

&Vehicle_Direction_Determinat_M_;

/* Model step function */

void Vehicle_Direction_Determinatio_step(void)

{

/* Outputs for Atomic SubSystem: '<Root>/Vehivale_Direction_Determination' */

/* Outport: '<Root>/Vehicle_Direction_Indicator' incorporates:

* Inport: '<Root>/CameraInput_RoadSign'

* Logic: '<S3>/or'

*/

Vehicle_Direction_Determinati_Y.Vehicle_Direction_Indicator =

(Vehicle_Direction_Determinati_U.CameraInput_RoadSign != 0.0F);

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

}

/* Model initialize function */

void Vehicle_Direction_Determinatio_initialize(void)

{

/* (no initialization code required) */

}

/* Model terminate function */

void Vehicle_Direction_Determinatio_terminate(void)

{

/* (no terminate code required) */

}

/*

* File trailer for generated code.

*

* [EOF]

*/

Result

The vehicle direction determination is modelled as per the requirement, all the signals are defined in Simulink data dictionary. All input and output signals are resolved and propagated. Updated the model to check for static errors. Run the model advisor tool to see any errors. since there are no errors in Model Advisor Report. Code has been generated using Embedded Coder.