Project 1 (Mini Project on Vehicle Direction Detection

AIM OF PROJECT:

identifying the direction of vehicle based on the camera input.

OBEJECTIVE OF PROJECT:

• Development of MATLAB Simulink model as per requirement.
• Tag the requirements to the simulink model; tagging requirement 1 & requirement 2 to their corresponding subsystems is fine.
• MBD compliant changes, Data Dictionary creation & code generation is added advantage, and that is not scope of this project.
• 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.
• Choose sample time for all signals as 0.01s

INTRODUCTION:

Vehicle examination is a critical undertaking in different applications. It is an important process in several purposes. Various such applications are driver assistance system, electronic toll collection, intelligent parking system. Particularly in wrongdoing anticipation and mischance examination, the assignment can give helpful data.

One such application in order to enhance the detection of vehicles is to determine the direction of vehicles. Using the increasing need for security consciousness

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, night tum & 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.

Development of the Target Model:

As per the requirement as shown below the target model has been developed

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).

The overall model of vehicle direction detection as shown in below

The subsytem of main model as shown in below:

As per requriment 1 model as show in below

As per requriment 2 model as show in below

Tagging requriment with model

Liniking model with SSLDD as shown

Requriment 1 SLDD

Requriment 2SLDD

Change the configuration parameter for simulation and code generation

For code generation embedded coder is target

model advisor

Simulation anyalsis:

after the simulation model following result are coming in display block which connected to check whether model is working as per requriment or not :

the output of the display block is denoting that the Right Turn is executed which is because the Initial Value of the input mal SteeringWheel_YawDegreelnput is taken as 30 in the SLDD as shown below.

similar is done for left turn and stright drive

left turn:

straight drive:

coclusion:

The model corresponding to Vehicel Direction Detection is successfully implemented. All the compliant changes pertaining to MBD. requirement tagging, linking of the model to the SLDD, Code generation and ultimately generation of the Model Advisor Report is presented with detailed analysis.