Project 1 (Mini Project on Vehicle Direction Detection

Project 1 (Mini Project on Vehicle Direction Detection)

Aim

To create a SIMULINK model of Vehicle Direction Detection as per given requirements.

Objective

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

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.

Steps involved in creating Mini Project on Vehicle Direction Detection

Step 1: Development of MATLAB Simulink model as per requirement.

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).

CREATED SUBSYSTEM FOR REQUIREMENT 1

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).

CREATED SUBSYSTEM FOR REQUIREMENT 2

SIMULINK MODEL OF VEHICLE DIRECTION DETECTION SYSTEM

SUBSYSTEMS

Input Ports

1. SteeringWheel_YawDegreeInput - Here the vehicle direction input is taken in degrees and sent for comparison with road signs.

2. CameraInput_RoadSign - Here is the camera detects the direction road sign and inputs for comparison. Camera reads the road signs & stores into its memory with unique values for left turn, right turn & straight drive.

Output Ports

1. Vehicle_Direction_Indicator -

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.

Step 2: To create SLDD and link it with Simulink Model.

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	-	-

Steps involved in creating a SLDD

• Create a simulink model
• Choose 'link to Data Dictionary' option from Modeling tab
• In model properties window, select New option and uncheck access to base workspace
• Naming file as 'Vehicle_Direction_Detection' and SLDD gets linked to Model.

Adding Values, signals and variables as per given Input.

Sample time for all signals taken are 0.01s

Step 3: Tag the requirements to the simulink model.

The requirements ‘Requirement-1’ and ‘Requirement-2’ are tagged to their corresponding subsystem in the Simulink Model in WORD.

We follow the below steps,

• First highlight the subsystem for which requirement needs to be tagged.
• Right click on the subsystem > Requirements > Link to Selection to Word.
• Before proceeding with the above two steps, kindly keep the word file ready and open.

REQUIRMENT TAGGING DEMO

Step 4: MAB Guidelines Model Advisor

To check whether the developed simulink model meets the modeling standards for MAB, we run Model Advisor using Model Advisor tool.

To run model advisor, Go to model advisor and click or select Model standards for ‘MAB’ then run the programme.

Step 5: Embedded Coder (Code Generation)

In this step, we convert our Simulink model to a C code file known as Code generation file using embedded coder.

CODES

RESULT

Thus the Vehicle Direction Detection system is successfully developed as per requirements.

The requirements has been tagged to respective subsystems.

MBD compliant changes, Data Dictionary creation & code generation is by following and adhering to respective conditions.

All input and output signals are resolved and propagated.

Errors are resolved and no errors found in Model Advisor under MAB standards.

And finally Autocodes has been successfully generated using Embedded Coder.

CONCLUSION

Upon testing the model using possible test values, it can be concluded that the above indication confirms that the vehicle is projecting in a straight path for which the Logic output is (0 0 1).

The Logic output of (1 0 0) indicates that the vehicle is taking a right turn.

The Logic output of (0 1 0) indicates that the vehicle is taking a left turn.