Project 1 (Mini Project on Vehicle Direction Detection

AIM: To develop a simulink model for vehicle direction determination that satisfies the following requirements.

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).

THEORY:
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.

Simulation:

The steps to be followed for developing a simulink model for Vehicle direction detection satisfying the requirements are:

Change the model settings to MBD Compliances Changes:

This includes the solver settings, code generation target file and sample time for solver.

Develop the simulink model:
Based on the given requirements seperate subsystems are made for
requirement 1 and requirement 2.

Requirement 1 Subsystem:
• Steering wheel input as yaw rate (Signalname: 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 Subsystem:
• 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).

Develop the simulink data library for the model from the given data:
Signals & Calibration Data List:

Signal / Calibration Name Signal Type DataType Dimension Min Max InitialValue 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 - -

Under Modelling section of the simulink window open link to data dictionary and a new window will open.

Create a new sldd file for the model and click apply.

Set up the signals and parameters under design data used in the developed model.

Determine resolved signals and propagated signals in the model:

Code generation:
The code for the entire vehicle direction determination model is developed by Generating S-function.

Requirement tagging:
The subsystem are tagged to the respective requirements provided in a word file.

Similarly requirement 1 subsystem is tagged to the heading requirement 1 using the link to selection in word option.

Model Advisory Check for MAB standards:

Under Model Advisor window, choose by task and select Modeeling standards for MAB and select run selected checks option on the right.

After the checks a report will be developed showing the pass, fail and warnings for the model.

CONCLUSION:

The simulink model for the vehicle direction detection was developed with the given requirements and the model advisory check for the model was done and the results showed zero failed conditions and less than 15 warnings for MAB standards.The model advisory report and code generated for the model are attached with this report.