Project 1 (Mini Project on Vehicle Direction Detection

Q.

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 the vehicle is identifying the direction the vehicle is taking based on the camera input.

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

Vehicle Direction Determination can also be coupled alongside 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.

The objective of the Mini Project:

1. Development of MATLAB Simulink model as per requirement.
2. Tag the requirements to the Simulink model; tagging requirements 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 the 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 a 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 & the 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 a local signal from requirement 1 (Signal Name: Vehicle_Turn_Status) & an input signal from the camera (Signal Name: CameraInput_RoadSign) that 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 an 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	-	-

ans:-

AIM

To create a Simulink model of Vehicle Direction Detection as per the Requirement data

Advanced Driver Assistance System

Mini project -Vehicle Direction Determination

General overview

Identifying the vehicle's direction is one of the important & diverse features of the Autonomous driving & Drive Assistance feature. this particular sub_feature of identifying the direction of the vehicle is identifying the direction the vehicle is talking based on the camera input.

The camera reads the road signs &stores them into unique values for the left turn, right turn, and straight drive Depending on the direction it is taking the final indication is given to drive _as an indication if he is driving in the recommended direction or not

Vehicle Direction Determination can also be coupled alongside features like a GPS to identify whether the vehicle is reaching its destination in an optimized manner.

The objective of the Mini project:

1. Development of MATLAB Simulink model as per requirement.
2. Tag the requirements to the Simulink model; tagging requirements 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 the 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

1. Desingning the MATLAB MODEL

This is the main model subsystem that has two inputs Steeringwheel_yawdegreeinput and Camerainput_roadsing entering into a subsystem and one output Vehicle_Direction_indicator

There are 2 requirements are designed in two subsystem

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 a 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 & the 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 a local signal from requirement 1 (Signal Name: Vehicle_Turn_Status) & an input signal from the camera (Signal Name: CameraInput_RoadSign) that 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 an output signal (Signal Name: Vehicle_Direction_Indicator).

2. Requirement Tagging

all the requirements are tagged for better understandability, anyone who is reviewing the model or who is trying to update the model has ideal data of what is logical data used in the system.

General overview

3. Developing SLDD

all the inputs, outputs, calibration parameters are saved in SLDD so in white simulation, the model takes all the values and their parameters from the Simulink Data Dictionary

4. Signal Resolution for input and outputs

5. model update

The model update is done by Ctrl_D .this is done to check for any static errors. if no errors are coming the model is working fine without any error.

6. simulation

The model is simulated too to check for errors and warning

7. configuration parameter updates

embed coder:-

Output:-

Result:-

Thus, we have successfully analyzed the signal in the way that Right, left, and Straight, respectively.

As the output is boolean,

if we get (0 0 1), then the vehicle moving in the straight drive

if we get (1 0 0), then the vehicle moving in the Right drive

if we get (1 0 1), then the vehicle moving in the left drive