Project 1 (Mini Project on Vehicle Direction Detection

*I'M A CHENNAI SKILL CENTRE STUDENT*

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).

Explanation :

The below image shows the overview of the vehicle direction detection Simulink model.

Where two inputs,

1. Steering wheel yaw degree
2. Camera roadsign

were linked from the sldd file created based on the information provided in the question.

Which is provided in the below diagram.

We have to map the input link from the SLDD file to the required signal input.

for that,

Right-click on the signal -> Properties -> Type the name (it will automatically give suggestions for the input link from the sldd file)-> check(select) the signal name must resolve to Simulink signal object -> ok.

After creating subsystems for requirement 1 as mentioned in the question, we must tag it with the word file following the steps.

• copying the requirements from the question
• creating it as a word document file and saving it in the same directory/location of the slx file.
• now, select the heading in the word document and,
• right-click on the subsystem -> Requirements -> Link to selection in word.
• the subsystem will be popped in yellow color after tagging.

Requirement document.

Requirement 1:

• Based on the degree of steering wheel yaw degree input, we have to find whether the vehicle is turning left or turning right, or going straight.
• here I have separated the turning cases by two switches,
• the inputs were, 1)right_turn _angularlimit, 2)left_turn_angularlimit, 3)straight_drive_steeringangle, and 4)steeringwheel_yawdegreeinput.
• in the first switch, we are comparing straight drive angle and right turn angular limit, with the steering wheel angular limit as base input.
• if the input from the steering wheel yaw degree input is equal to any of the other input conditions, the switch will give the output based on the inputs either true or false.
• also, we can split this switch into two by adding a constant input for comparison.
• if both the inputs are not equal to the steering wheel yaw degree input, switch one will give output as 0 and the condition will move to the second switch.
• where the input from the first switch and left turn angular limit is compared and output will be given out as 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).

After completing the signal connections we have to treat the subsystem as an atomic subsystem.

Right-click on the atomic subsystem -> BlockParameters -> Treat as atomic subsystem.

With this atomic subsystem, we have to generate code for the project of vehicle direction detection.

Modeling -> Model settings -> Code Generation -> System target file -> ert.tlc

Also, for code generation, we can directly get access through,

Apps -> Embedded Coder (Generate C and C++)

Then generate code using the Generate code option in c code window.

The below image shows the .c code generation.

MAB guidelines