Project 1 (Mini Project on Vehicle Direction Detection

Aim: To develop a Vehicle Direction Detection model with aid of MATLAB and Simulink.

Description:

System description:

"Vehicle Direction Detection " is a one of the features in ADAS based cars.

It aims to provide the driver with the vehicle's direction based on the inputs from the Camera unit.

Main Objective :

1. Development of MATLAB Simulink model as per requirement.
2. Tagging the requirements to the simulink model; tagging requirement 1 & requirement 2 to their corresponding subsystems is fine.
3. To perform the MBD compliant changes.
4. To perform Data Dictionary creation
5. To perform code generation for the developed simulink model.
6. For 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.
7. To Choose sample time for all signals as 0.01s

Process overflow:

Step 1:Simulink model creation-To create a simulink model for the "Vehicle Direction Detection ".

Step 2:Requiremet tagging-To tag the given two requirements to the simulink model "VVehicle Direction Detection "

Step 3:Simulink data dictionary creation-To create simulink data dictionary from the Signals & Calibration Data List.

Step 4:Auto code generation-To perform auto-code generation for the given simulink model.

Step5:Model advisory check: To perform the model advisory check .Select any one of the standards listed : ISO 25119(example)

Project Description:

Step 1:To create a simulink model for the "Vehicle Direction Detection ".

Based on the two Requirements 1 and 2 ,there are 2 seperate subsystems taken for model development.

In the subsystem 1:

1. Steering wheel input as yaw rate (Signal name: SteeringWheel_YawDegreeInput) is the input for this system.
2. This input 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 determine which specific direction the steering wheel is turning towards and output of this subsystem is a local signal (Signal Name: Vehicle_Turn_Status).

In the subsystem 2:

1. Inputs to this requirement are local signal from subsystem 1 (Signal Name: Vehicle_Turn_Status) & another input signal from camera (Signal Name: CameraInput_RoadSign), which confirms the occurrence of a road sign.
2. Next,Signal Vehicle_Turn_Signal 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,
3. Using a logical operator block, only one among them is finally given as output signal (Signal Name: Vehicle_Direction_Indicator).

Simulink model for Vehicle Direction Detection :

Step 2:To tag the given two requirements to the simulink model of "Vehicle direction determination" .

Requirement1:

Requirement2:

Step 3:Simulink data dictionary creation-To create simulink data dictionary from the Signals & Calibration Data List.

SLDD creation:

SLDD file

Step 4:Auto code generation-To perform auto-code generation for the given simulink model.

"Embedder coder" is used to perform code generation

Step1:Open APPS->Embedded coder -> Quick start

Step2: Auto code starts to generate ,save the report

Following files are saved after code generation:

Step5:Model advisory check: Open the model advisory check tab .

Select any one of the standards listed : ISO 25119(example)

Run all the possible checks to perform the generation standardised of MBD model.

Result:

The simulink model for the Vehicle Direction Detection has been created as per requirements and all the MBD related process:Requirement Tagging & Traceability, SLDD creation, Configuration Parameter changes, Model Advisor check & Code Generation are done for the model.