Challenge

Project 1 (Mini Project on Vehicle Direction Detection

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:

Signal / Calibration Name

Signal Type

Data Type

Dimension

Min

Max

Initial Value

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

-

-

Same has been updated in the Design data of vehicle_direction_detection_dd.sldd

Simulink data dictionary is created with the file name of veh_dir_det_dd and the following simulink signal and parameter are added as per the given requirement.

iv) Requirement Tagging:-

A MS Word file is created which contain all the requirements and necessary information to develop the model appropiately. This Word file is tagged for both the subsystem requirement1 and Requirement2 respectively.

v) Signal Resolving and Signal Tagging:-

All the input signal are resolved at the root level of the model and propogated accordingly as shown below:-

vi) Model Advisor Report Generation:-

To generate the report we have to go over the Modelling tab and then there at Extreme left corner there is a option of Model Advisor and selecting Model Advisor in it.

It will ask to select the system for which the report generation is to be taken:-

Then under the By task option unselecting all the previously selcted option and then selecting the Modelling Standard for MAB there and in the right box there is option to Run sleected check and clicking over there will run the selected checks

The result of the Modelling Standard for MAB is as shwon below:-

Also a HTML report is generated thereafter by clicking over the option Generate Report

vii) Code Generation:-

The Code Generation is made by going over the APP tab and selecting the Embedded coder over there :-

Code generation:

Conclusion

Created Data dictonary file and simulink model for Vehicle Direction Detection System.

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