Project 1 (Mini Project on Vehicle Direction Detection
Aim:
To create a Simulink model of Vehicle Direction Detection as per the Requirement data.
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_Signal 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).
Objectives of the 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
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 |
- |
- |
Simulink model:
SLDD_file:
Requirement Tagging:
The SLDD_file is created to store the calibration values and input and output signals.
Requirement Tagging & Tracebility:
In Model-Based Design (MBD), "signal resolving" typically refers to the process of mapping or resolving signals between different components or elements within a system model. It involves connecting and routing signals from one block or component to another.
In MBD, a system model is typically represented using interconnected blocks, where each block represents a specific function or behavior. These blocks communicate with each other through signals, which carry information such as data, commands, or events.
Signal resolving involves specifying how signals are transmitted and received between blocks within the system model. This can include defining signal connections, assigning input and output ports, and configuring the data flow between blocks.
The goal of signal resolving is to establish the proper communication channels between blocks, ensuring that signals are correctly propagated through the model and that the desired system behavior is achieved.
In Model-Based Development (MBD), signal propagation refers to the flow of signals between different components or elements within a model. MBD involves the use of models to design, simulate, and implement complex systems.
In MBD, a system model typically consists of interconnected components or blocks, each representing a specific function or behavior. These blocks communicate with each other by exchanging signals. Signal propagation in MBD refers to how these signals are transmitted, routed, and received between the blocks within the model.
The signal propagation process involves:
-
Defining signal connections: Determining which signals are transmitted from one block to another and establishing the necessary connections between them. This could include specifying input and output ports for the blocks.
-
Propagating signals: Once the signal connections are defined, the signals are propagated from the source block to the destination block through the established connections. This ensures that the necessary information flows through the system.
-
Processing signals: As signals propagate through the model, they may undergo processing or transformations in different blocks. This could involve mathematical operations, filtering, or any other computations that affect the signal characteristics.
-
Receiving signals: Finally, the propagated signals are received by the appropriate blocks or components, where they are used for further processing, decision-making, or control actions within the system.
Signal propagation in MBD allows for the analysis and simulation of the system's behavior, enabling engineers to evaluate system performance, verify functional requirements, and identify potential issues or optimizations.
Blocks used:
Blocks used to create a model are
Input Blocks: To provide the input signals
Output Blocks: To send the output signals
Constant Blocks: To define the calibration values
Logical operator Blocks: AND blocks are used to compare and the road signs with camera input and to get the boolean output.
Switch Blocks: To compare the input with the calibration values.
Mux Block: To combined the signals
Display Block: To display the results
Procedure:
The logic in the Requirement_1 is, If the input is >=30 (because the initial value is 30) the vehicle will take the Right turn, else If the input is not-equal to zero (~=0) the vehicle left_turn, else stright_drive (if the input is equal to zero).
The input yaw rate is given to the middle port of the switch, and the threshold value is 30. If the input is greater than threshold value then the switch will takes the True condition (Right_Turn_AngularLimit) else false condition. In the second switch the threshold value is zero, if the threshold value is not equal to zero then the switch will takes the true condition (Left_Turn_AngularLimit) else takes the false condition (Sitight_Drive steering_Angle). This output from the second switch is given as a false condition to the first switch. And the output for the Requirement_1 is "Vehicle_Turn_Status".
The logic in the Requirement_2 is to compare the "Vehicle_Turn_Status" (Output of Requirement_1) with "RoadSign" and an input signal from camera to get the Vehicle Direction indicaton.
After comparision with "Vehicle_Turn_Status" if each of them is found equal, then each of the three corresponding output is compared against the camera input signal, by using the 'logical OR' Blocks will get the true case and to take only one among them as output, the 'Mux' block is used.
And the final output from the Vehicle_Detection Model will indicates the vehicle_Direction indication.
Next by adding the SLDD_file to the model and by loading the calibration values and input/output values are defined.
By running the simulation will get the vehicle direction.
Results:
- The signs are in the way that Right, Left and Straight respectively.
- If both inputs A and B are 1, indicating that both the left and right turn signals are active, the AND gate will output 1.
- If input A is 1 and input B is 0, the AND gate will output 0. This indicates that only the left turn signal is active.
- If input A is 0 and input B is 1, the AND gate will output 0 as well. This indicates that only the right turn signal is active.
- If both inputs A and B are 0, the AND gate will output 0. This means that neither the left nor the right turn signal is active,
- After running the simulation, we can clearly see that the vehicle is moving the straight direction.
Conclusion:
Autonomous vehicles consists of various Advance Driver-Assistance System (ADAS) features. Vehicle Driection Detection is one the features of the vehicles.
Hence, created an Simulink model of Vehicle Direction Detection as per the Requirement data.