Project 1 (Mini Project on Vehicle Direction Detection

Aim: To design Vehicle Direction Determination ADAS using MATLAB SIMULINK

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:

1. To Development of MATLAB Simulink model as per requirement.
2. To Tag the requirements to the simulink model; tagging requirement 1 & requirement 2 to their corresponding subsystems is fine.
3. To complete MBD compliant changes, Data Dictionary creation (Not able to do code generation- in trail version of software)
4. 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. To Choose sample time for all signals as 0.01.

Step1:

MATLAB SIMULINK MODEL AS PER REQUIREMENT

Substem for requriment1:

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).

Substem for requriment2:

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).

Step2:

REQUIREMENT TAGGING TO CORRESPONDING SUBSYSTEM

Step 3:

SLDD CREATION AND CHOOSING STORAGE CLASS AND SAMPLE TIME

STEP4:

SIGNAL RESOLUTION FOR INPUTS AND OUTPUTS

Inputs and output signals are resolved so the signals will take the values from sldd and pass them to the logical blocks.

STEP5:

CONFIGURATION PARAMETER SETTINGS

STEP6:

MODEL ADVISOR CHECK AND REPORT GENERATION

Result

The vehicle direction determination is modelled as per the requirement, all the signals are defined in Simulink data dictionary. All input and output signals are resolved and propagated. Updated the model to check for static errors. Run the model advisor tool to see any errors. Model Advisor Report is generated