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Project 1 (Mini Project on Vehicle Direction Detection

PPraveen Kumar23 Aug 2022
MATLABMBD

AIM

To Identify the direction of vehicle based on camera input.

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

-

-

Advanced Driver Assistance Sysytem:

An advanced driver-assistance system (ADAS) is any of a groups of electronic technologies that assist drivers in driving and parking functions. Through a safe human-machine interface, ADAS increase car and road safety. ADAS use automated technology, such as sensors and cameras, to detect nearby obstacles or driver errors, and respond accordingly. ADAS can enable various levels of autonomous driving, depending on the features installed in the car.

ADAS is a one advanced feauture where it ensure the safety of the driver and passengers.For that the ADAS system takes many input for analyzing purpose ehther to turn right or left or to continue on straight line.One such important input for ADAS is camera input.Here,In this project we are going to create a simulink model for vehicle direction detection according to camera input

Simulink Model:

The simulink model for the vehicle direction detection is shown below

The steering wheel and camera sign are given as input

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).

Data dicitonary:

An data dictionary is created for the required model and input are given as per the requirement

Solver settings:

Solver Type is changed from variable step to Fixed step and Solver type is selected as Discrete ( No continuous state) and also sample time is declared as 0.01 sec as per the project requirement.

Also under the Code generation option selecting embedded real time as system target file under target selection option.

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.

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

Code generation:

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

Now clicking over the build option will create the C code as shown below:-

The .c code is generated as below:-

* File: Project_Vehicle_direction_detection.c
*
* Code generated for Simulink model 'Project_Vehicle_direction_detection'.
*
* Model version : 1.2
* Simulink Coder version : 9.5 (R2021a) 14-Nov-2020
* C/C++ source code generated on : Tue Aug 23 11:07:08 2022
*
* Target selection: ert.tlc
* Embedded hardware selection: Intel->x86-64 (Windows64)
* Code generation objectives: Unspecified
* Validation result: Not run
*/
#include "Project_Vehicle_direction_detection.h"
#include "Project_Vehicle_direction_detection_private.h"
/* Real-time model */
static RT_MODEL_vehicle_Direction_Dete_T vehicleDirection_Determinatio_M_;
RT_MODEL_vehicleDirectionDete_T *const vehicleDirectionDeterminatio_M =
&vehicleDirectionDeterminatio_M_;
static void rate_scheduler(void);
/*
* This function updates active task flag for each subrate.
* The function is called at model base rate, hence the
* generated code self-manages all its subrates.
*/
static void rate_scheduler(void)
{
/* Compute which subrates run during the next base time step. Subrates
* are an integer multiple of the base rate counter. Therefore, the subtask
* counter is reset when it reaches its limit (zero means run).
*/
(vehicleDirectionDeterminatio_M->Timing.TaskCounters.TID[1])++;
if ((vehicleDirectionDeterminatio_M->Timing.TaskCounters.TID[1]) > 99) {/* Sample time: [0.01s, 0.0s] */
vehicleDirectionDeterminatio_M->Timing.TaskCounters.TID[1] = 0;
}
}
/* Model step function */
void Project_Vehicle_direction_detection_step(void)
{
/* local block i/o variables */
int16_T Vehicle_Turn_Status;
boolean_T Right_Turn_Status_Check;
boolean_T LeftOrStraight_Status_Check;
boolean_T Right_Turn_Status;
boolean_T Right_Turn_Indicator;
boolean_T Left_Turn_Status;
boolean_T Left_Turn_Indicator;
boolean_T Straight_Drive_Status;
boolean_T Straight_Drive_Indicator;
if (Project_Vehicle_direction_detection_M->Timing.TaskCounters.TID[1] == 0) {
/* Outputs for Atomic SubSystem: '/Project_Vehicle_direction_detection' */
/* RelationalOperator: '/RelationalOperator' incorporates:
* Constant: '/Constant'
* Inport: '/SteeringWheel_YawDegreeInput '
*/
Right_Turn_Status_Check = (SteeringWheel_YawDegreeInput >=
Right_Turn_AngularLimit);
/* RelationalOperator: '/RelationalOperator1' incorporates:
* Constant: '/Constant1'
* Inport: '/SteeringWheel_YawDegreeInput '
*/
LeftOrStraight_Status_Check = (SteeringWheel_YawDegreeInput <=
Left_Turn_AngularLimit);
/* Switch: '/Switch' incorporates:
* Switch: '/Switch1'
*/
if (Right_Turn_Status_Check) {
/* Switch: '/Switch' incorporates:
* Constant: '/Constant3'
*/
Vehicle_Turn_Status = Right_Turn_AngularLimit;
} else if (LeftOrStraight_Status_Check) {
/* Switch: '/Switch1' incorporates:
* Constant: '/Constant4'
* Switch: '/Switch'
*/
Vehicle_Turn_Status = Left_Turn_AngularLimit;
} else {
/* Switch: '/Switch' incorporates:
* Constant: '/Constant2'
* Switch: '/Switch1'
*/
Vehicle_Turn_Status = Straight_Drive_Steering_Angle;
}
/* End of Switch: '/Switch' */
/* RelationalOperator: '/RelationalOperator' incorporates:
* Constant: '/Constant'
*/
Right_Turn_Status = (Vehicle_Turn_Status == RightTurn_RoadSign);
/* Logic: '/AND' incorporates:
* Inport: '/CameraInput_RoadSign'
*/
Right_Turn_Indicator = (Right_Turn_Status && CameraInput_RoadSign);
/* RelationalOperator: '/RelationalOperator1' incorporates:
* Constant: '/Constant1'
*/
Left_Turn_Status = (Vehicle_Turn_Status == LeftTurn_RoadSign);
/* Logic: '/AND1' incorporates:
* Inport: '/CameraInput_RoadSign'
*/
Left_Turn_Indicator = (Left_Turn_Status && CameraInput_RoadSign);
/* RelationalOperator: '/RelationalOperator2' incorporates:
* Constant: '/Constant2'
*/
Straight_Drive_Status = (Vehicle_Turn_Status == Straight_RoadSign);
/* Logic: '/AND2' incorporates:
* Inport: '/CameraInput_RoadSign'
*/
Straight_Drive_Indicator = (Straight_Drive_Status && CameraInput_RoadSign);
/* SignalConversion: '/Signal Conversion' */
Vehicle_Direction_Indicator[0] = Right_Turn_Indicator;
Vehicle_Direction_Indicator[1] = Left_Turn_Indicator;
Vehicle_Direction_Indicator[2] = Straight_Drive_Indicator;
/* End of Outputs for SubSystem: '/Project_Vehicle_direction_detection' */
}
rate_scheduler();
}
/* Model initialize function */
Project_Vehicle_direction_detection_initialize(void)
{
/* (no initialization code required) */
}
/* Model terminate function */
Project_Vehicle_direction_detection_terminate(void)
{
/* (no terminate code required) */
}
/*
* File trailer for generated code.
*
* [EOF]
*/
Thus the code generated and the required documents are attached below.
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