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	-	-

Matlab model :

In requirement 1 we create a subsystem

• SteeringWheel_YawDegreeInput is input of requirement1 then input gives to switch block this switch once reach the condition the output is Right_Turn_AngularLimitotherwise switch 2 condition is activated
• switch 2 condition is SteeringWheel_YawDegreeInput is not equal to zero the output is Left_Turn_AngularLimit otherwise Straight_Drive_Steering_Angle is output.

requiremet 1 subsystem :

In requirement 2:

• output of rquirement 1 is input of requirement2 that the signal named as Vehicle_Turn_Status
• another input is CameraInput_RoadSign
• then compare the two inputs and give to relational operator and the three outputs are give to mux block the outut name is Vehicle_Direction_Indicator
• display is connected to outport block it is show vehicle direction .

subsystem Model :

next process creating a tagging system :

• first we select the which block create a tagging then right click the block choose requirement then select link to ms word the coppied words are linked to block
• already requirement of block feed into word file and saved in matlab path way
• the first subsystem is used in tagging image attached below
• then create a tagging for subsystem 2 also second tagging system image attached below

after tagging signals and caliobration are added to data dictionary

the process to add the data dictionary given below

first select the file location and added to matlab path and signals are added in data dictionary in manual when see a added values click on the model advisor and see the listed values

then check the model is proper working using model advisor first step is choose a system then run the model for selected checking conditions.

the selected boxes are checking conditions of the model after checking model advisor will create a report otherwise any fail or waring are shown in the report all the warings and fails are cleared in manual

next we generate a code generation for the model

in model properties setting select the embedded coder then run the model under coverage after completion if running coverage report will generate automatically .

first we select the code generation setting in the model properties

• 

this is coverage report then create a code generation

CODE :