Project 1 (Mini Project on Vehicle Direction Detection

AIM :- Creating a Simulink Data Dictionary(SLDD) and Simulink Model for Vehicle Direction Detection using MATLAB and Simulink.

THEORY :- Vehicle Direction Detection.

Identifying the direction of the vehicle is one of the important and diverse feature in Autonomous driving and Advanced Driver Assistance System (ADAS) feature. This particular sub-feature of identifying the direction of vehicle basically identifying the diection of the vehicle is taking based on the camera input.

Camera reads the road sign and stores into the memory with the unique value for the left turn, right turn, and 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 dirction or not.

Vehicle Direction Determination can also be coupled along - side feature like gps systems to identify whether the vehicle is reaching its destination in an optimised maner. this sub feature can also be used along with Lane Detection. Highway Warning,Ramp entry/Exit in Wrong Way Detection etc.

OBJECTIVE OF THIS PROJECT :-

1. Developement of MATLAB Simulink model as per requiment.

2. Tag the requirement to the simulink modle; tagging requirements 1and 2 to their corresponding subsystems.

3. MBD compliant changes, Data Dictionary creation and code generation.

REQUIREMENTS:-

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	-	-

PROCEDURE:

First we created a Simulink Data Dictionary (SLDD) from given signal and calibration data list.

we are going through model configuration for creating Simulink data dictionary and make the file. the signal and calibration are added as per the requirements and then accordingly we fill the data.

Fig: SLDD file for Vehicle Direction Detection.

Then we created a main Model/Sub-System with the inputs SteeringWheel_YawDegree and CameraInput_RoadSign and Output as a Vehicle_Diection_Detection.

Fig:Main Sub-system of Vehicle Direction Detection .

Under the main sub-system,we created two more sub-system as per the requirements.

as per the first requirement-1 we created a sub-system 1

Fig: Sub-System 1 As per requirement-1.

then we created second sub-system as per requirement-2.

Fig: Sub-System 2 as per requirement-2.

Then the output of this compared with the camera input, which gives the direction to the vehicle.

Fig: Model inside the Main Sub-System.

the following is the Main Simulink model of Vehicle Direction Detection System.

Fig: Simulink model for Vehicle Direction Ditection.

RESULT:-

The results are observed in the Display bolck as follows.

If the output is (0,0,1). the vehicle is moving the Straignt drive signal is shown.

If the output is (1,0,0). the vehicle is taking the Right turn signal is shown.

If the output is (1,0,1), the vehicle is taking the Left turn signal is shown.

CONCLUSION:- Identifying the direction of vehicle basically identifying the diection of the vehicle is taking based on the camera input. and Identifying the direction of the vehicle is one of the important and diverse feature in Autonomous driving and Advanced Driver Assistance System (ADAS) feature.