Project 1 (Mini Project on Vehicle Direction Detection

all the necessary documents, matlab file , sldd file, c-code, MIL test report are attached.

https://drive.google.com/drive/folders/1zn-GtfHD9RspAFGexQ_4saiJP7-UUYyF?usp=sharing

ADAS:Vehicle Direction Determination

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.

Aim of 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).

TO DEVELOP MODEL AS PER THE REQUIREMENT:

REQUIREMENT – 1:

As per given statement, steering input value is used in inport.

Then it is compared with the constant variable defined as three different function.

Right_Turn_AngularLimit

Left_Turn_AngularLimit

Straight_Drive_Steering_Angle

These are the three constant variables defined in the model for direction detection of steering.

If the compared value is true, it will pass through the switch created in model.

If its false, it will check for other direction input value.

The result value is stored in vehicle_Turn_Status.

REQUIREMENT – 2:

For second statement, the vehicle_turn_status is taken as input.

And its value is compared with camera input value of road sign detection of direction.

It is done using AND & SWITCH block.

All the road_sign_status is compared with vehicle_turn_status, if the value is true, then it will again confirm with camera input value.

After that the output is given as vehicle direction.

The sample time is changed to 0.01

REQUIREMENT TAGGING:

A new sldd file is created for modelling, and all the variables, signals, constants are defined.

After that to model it, configuration parameters are set.

To authenticate the model,use model advisor, it will specifically generate report.

The next dialogue box will be shown here.

And by doing that, it will allow us tto check model according to model authenticities.

the next step as model based developer is generating code, using generate code command.

the ressultant C code is attached.

Conclusion:

In the result, we get the c-code for the modelled system for steering wheel detection system.

All the model in loop report is generated.