Project 1 (Mini Project on Vehicle Direction Detection

Advanced Driver Assistance Systems

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).

Signals & Calibration Data List:-

1. Designing the MATLAB MODEL

This the main model subsystem that having two inputs SteeringWheel_YawDegreeInput and CameraInput_RoadSign entering into the Vehicle Detection Determination subsystem and one output Vehicle_Direction_Indicator

There are 2 requirements are designed in two subsystem

Requirement - 1

1. Steering wheel input as yaw rate (Signal name: SteeringWheel_YawDegreeInput) is the input for this system.
2. 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.
3. 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).

inside of the Vehicle_Turn_status_subsystem

Requirement – 2:-

1. 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.
2. 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,
3. Using a logical operator block, only one among them is finally given as output signal (Signal Name: Vehicle_Direction_Indicator).

inside of the Vehicle_Direction_Indicator_SubSystem

2.Requirement Tagging:-

all the requirements are tagged in order for better understandability, anyone who is reviewing the model or who is trying to update the model can get a clear idea of what logic is used in the system. from the requirement manager, we can see what are all are tagged and the descrip

Mini Project - Vehicle Direction Determination

General Overview:-

Requirement - 1:-

Requirement - 2:-

3.Developing SLDD:-

all the inputs, outputs, calibration parameters are saved in SLDD so while simulation the model takes all the values and its parameters from the Simulink DataDictionary

4.Signal Resolution for inputs and outputs:-

the inputs and output signals are resolved so the signals will take the values from sldd and pass them to the logical blocks. Otherwise, it may take some junk values if it is unresolved.

5.Model Update:-
The model update is done by Ctrl-D. this is done to check for any static errors. If there are no errors coming the model is working fine without any errors.

6.Simulation:-
The model is simulated too for checking for errors and warmings.

7.Configuration Parameter Update:-

Various configuration parameters are updated as per the code generation the solver type should be fix for code generation.

8.Model Advisory Report:-
By running the model advisor tool, we can see commonly made modelling errors.

9.Code generation:-
build model for generating code