Vehicle Direction Detection

Aim: To create the Vehicle Direction Determination model according to the given requirements.

Objective:

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 the 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

Theory:

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 the vehicle is basically identifying the direction the vehicle is taking based on the camera input.

The camera reads the road signs & stores them into its memory with unique values for a left turn, right turn & straight drive. Depending on the direction it is taking, the 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 alongside 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.

Matlab model:

Subsystem 1-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 a 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 & the output of this requirement is a local signal (Signal Name: Vehicle_Turn_Status).

Subsystem 2-Requirement 2:

• Keep this requirement as a separate subsystem. Inputs to this requirement are a local signal from requirement 1 (Signal Name: Vehicle_Turn_Status) & an input signal from the 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).

Model explorer:

SLDD file:

Output:

Straight turn:

Right turn:

Left turn:

Code generated:

MINI_projrct_ADAS.c
/*
* File: MINI_projrct_ADAS.c
*
* Code generated for Simulink model 'MINI_projrct_ADAS'.
*
* Model version : 1.1
* Simulink Coder version : 9.5 (R2021a) 14-Nov-2020
* C/C++ source code generated on : Wed Jun 30 13:24:57 2021
*
* Target selection: ert.tlc
* Embedded hardware selection: Intel->x86-64 (Windows64)
* Code generation objectives: Unspecified
* Validation result: Not run
*/

#include "MINI_projrct_ADAS.h"
#include "MINI_projrct_ADAS_private.h"

/* External inputs (root inport signals with default storage) */
ExtU_MINI_projrct_ADAS_T MINI_projrct_ADAS_U;

/* External outputs (root outports fed by signals with default storage) */
ExtY_MINI_projrct_ADAS_T MINI_projrct_ADAS_Y;

/* Real-time model */
static RT_MODEL_MINI_projrct_ADAS_T MINI_projrct_ADAS_M_;
RT_MODEL_MINI_projrct_ADAS_T *const MINI_projrct_ADAS_M = &MINI_projrct_ADAS_M_;

/* Model step function */
void MINI_projrct_ADAS_step(void)
{
int16_T rtb_Switch;

/* Outputs for Atomic SubSystem: '/Subsystem' */
/* Switch: '/Switch' incorporates:
* Constant: '/Left_Turn_AngularLimit'
* Constant: '/Right_Turn_AngularLimit'
* Inport: '/SteeringWheel_YawDegreeInput '
* Switch: '/Switch1'
*/
if (MINI_projrct_ADAS_U.SteeringWheel_YawDegreeInput > 0.0) {
rtb_Switch = Right_Turn_AngularLimit;
} else if (MINI_projrct_ADAS_U.SteeringWheel_YawDegreeInput > 0.0) {
/* Switch: '/Switch1' incorporates:
* Constant: '/Straight_Drive_Steering_Angle'
*/
rtb_Switch = Straight_Drive_Steering_Angle;
} else {
rtb_Switch = Left_Turn_AngularLimit;
}

/* End of Switch: '/Switch' */

/* Outport: '/Vehicle_Direction_Indicator' incorporates:
* Constant: '/LeftTurn_RoadSign'
* Constant: '/RightTurn_RoadSign'
* Constant: '/Straight_RoadSign'
* Inport: '/CameraInput_RoadSign'
* Logic: '/AND'
* Logic: '/AND1'
* Logic: '/AND2'
* Logic: '/AND3'
* Logic: '/AND4'
* Logic: '/AND5'
* Logic: '/OR'
*/
MINI_projrct_ADAS_Y.Vehicle_Direction_Indicator =
((MINI_projrct_ADAS_U.CameraInput_RoadSign && ((rtb_Switch != 0) &&
(RightTurn_RoadSign != 0))) || (MINI_projrct_ADAS_U.CameraInput_RoadSign &&
((rtb_Switch != 0) && (LeftTurn_RoadSign != 0))) ||
(MINI_projrct_ADAS_U.CameraInput_RoadSign && ((rtb_Switch != 0) &&
(Straight_RoadSign != 0))));

/* End of Outputs for SubSystem: '/Subsystem' */
}

Steps followed for generating code:

Right-click on main subsystem -> Block parameters(subsystem) -> Tick on Treat as atomic size -> model configuration-> solver (fixed step) -> sample time (0.01) -> code generation -> ert.tlc -> app (Embedded code) -> build (generate code).

Model advisor check:

Conclusion:

Successfully created the model from the given requirement data and generated the code and advisor report.