MBD - Adaptive Cruise Control
Aim:- To build an Adaptive Cruise control Model in Simulink as per the requirements and generate a code of it.
General Overview:
Adaptive Cruise Control Feature for passenger cars allows the host vehicle to adapt to the speed in line with the flow of traffic. Driving in heavy traffic or keeping a safe distance to the preceding vehicle calls for a high level of concentration. The Adaptive Cruise Control feature can reduce the stress on the driver by automatically controlling the vehicle speed & maintaining a predefined minimum distance to the preceding vehicle. As a consequence, the driver enjoys more comfort & can concentrate on the road little better.
A radar sensor is usually at the core of the Adaptive Cruise Control. Installed at the front of the vehicle, the system permanently monitors the road ahead. As long as the road ahead is clear, cruise control feature maintains the speed set by the driver. If the system spots a slower vehicle within its detection range, it gently reduces speed by releasing the accelerator or actively engaging the brake control system. If the vehicle ahead speeds up or changes lanes, the cruise control automatically accelerates to the driver’s desired speed.
Standard Adaptive Cruise Control can be activated from speeds of around 30 km/h (20 mph) upwards and supports the driver, primarily on cross-country journeys or on freeways. The cruise control stop & go variant is also active at speeds below 30 km/h (20 mph). It can maintain the set distance to the preceding vehicle even at very low speeds and can decelerate to a complete standstill. When the vehicle remains stopped longer, the driver needs only to reactivate the system, for example by briefly stepping on the gas pedal to return to cruise control mode. In this way, cruise control stop & go supports the driver even in heavy traffic and traffic jams.
Since Adaptive Cruise Control is a comfort and convenience system, brake interventions and vehicle acceleration only take place within defined limits. Even with Adaptive Cruise Control switched on, it remains the driver’s responsibility to monitor the speed and distance from the vehicle in front.
Objective of Main Project:
- Developing Adaptive Cruise Control feature as per the Requirement Document using MATLAB Simulink.
- Following all the MBD related processes: Requirement Tagging & Traceability, SLDD creation, Configuration Parameter changes, Model Advisor check & Code Generation.
- Using Embedded Coder to generate the code.
Model
https://drive.google.com/file/d/1KA_zP_oSz4ifMnBDSPFHMENNYCcq0QN_/view?usp=sharing
Model PDF
https://drive.google.com/file/d/1HG_heCYol2H0ziP9BXQHOMjyRp71z8DV/view?usp=sharing
Requirement 1
Requirement 2
Requirement 3
Logic inside State Flow
Simulink Data Dictionary
https://drive.google.com/file/d/1ZHAkswFazLzjdWU99aC-158pY0lo9l4f/view?usp=sharing
Code
/*
* File: modelacc.c
*
* Code generated for Simulink model 'modelacc'.
*
* Model version : 1.9
* Simulink Coder version : 9.5 (R2021a) 14-Nov-2020
* C/C++ source code generated on : Thu Oct 28 00:42:06 2021
*
* Target selection: ert.tlc
* Embedded hardware selection: Intel->x86-64 (Windows64)
* Code generation objectives: Unspecified
* Validation result: Not run
*/
#include "modelacc.h"
#include "modelacc_private.h"
/* Named constants for Chart: '/Chart' */
#define IN_LeadVehicle_Detected_Follow ((uint8_T)1U)
#define IN_LeadVehicle_Detected_Resume ((uint8_T)2U)
#define IN_LeadVehicle_Not_Detected_Res ((uint8_T)4U)
#define IN_LeadVehicle_Speed_equal_Set_ ((uint8_T)5U)
#define IN_LeadVehicle_Speed_lessthan_S ((uint8_T)6U)
#define mod_IN_LeadVehicle_Not_Detected ((uint8_T)3U)
#define modelacc_IN_ACC_OFF_MODE ((uint8_T)1U)
#define modelacc_IN_ACC_ON_MODE ((uint8_T)2U)
#define modelacc_IN_ACC_STANDBY_MODE ((uint8_T)3U)
#define modelacc_IN_NO_ACTIVE_CHILD ((uint8_T)0U)
/* Block states (default storage) */
DW_modelacc_T modelacc_DW;
/* External inputs (root inport signals with default storage) */
ExtU_modelacc_T modelacc_U;
/* External outputs (root outports fed by signals with default storage) */
ExtY_modelacc_T modelacc_Y;
/* Real-time model */
static RT_MODEL_modelacc_T modelacc_M_;
RT_MODEL_modelacc_T *const modelacc_M = &modelacc_M_;
/* Model step function */
void modelacc_step(void)
{
/* Sum: '/Add' incorporates:
* Inport: '/CameraInput_LeadVehicle'
* Inport: '/RadarInput_LeadVehicle'
*/
modelacc_Y.LeadVehicle_Speed = modelacc_U.CameraInput_LeadVehicle +
modelacc_U.RadarInput_LeadVehicle;
/* Sum: '/Sum' incorporates:
* Inport: '/CameraInput_DriveVehicle'
* Inport: '/RadarInput_DriveVehicle'
* UnitDelay: '/Unit Delay'
*/
modelacc_Y.DriveVehicle_Speed = (modelacc_U.CameraInput_DriveVehicle +
modelacc_Y.Acceleration_Mode) + modelacc_U.RadarInput_DriveVehicle;
/* Chart: '/Chart' incorporates:
* Inport: '/CruiseSwitch'
* Inport: '/RadarInput_DriveVehicle'
* Inport: '/SetSwitch'
* Inport: '/Set_Gap'
* Inport: '/Set_Speed'
* Inport: '/Time_Gap'
* UnitDelay: '/Unit Delay'
*/
if (modelacc_DW.is_active_c3_modelacc == 0U) {
modelacc_DW.is_active_c3_modelacc = 1U;
modelacc_DW.is_c3_modelacc = modelacc_IN_ACC_OFF_MODE;
modelacc_Y.Acceleration_Mode = 0.0;
} else {
switch (modelacc_DW.is_c3_modelacc) {
case modelacc_IN_ACC_OFF_MODE:
modelacc_Y.Acceleration_Mode = 0.0;
if (modelacc_U.CruiseSwitch == 1.0) {
modelacc_DW.is_c3_modelacc = modelacc_IN_ACC_STANDBY_MODE;
modelacc_Y.Acceleration_Mode = 1.0;
}
break;
case modelacc_IN_ACC_ON_MODE:
if (modelacc_U.SetSwitch == 0.0) {
modelacc_DW.is_ACC_ON_MODE = modelacc_IN_NO_ACTIVE_CHILD;
modelacc_DW.is_c3_modelacc = modelacc_IN_ACC_STANDBY_MODE;
modelacc_Y.Acceleration_Mode = 1.0;
} else {
switch (modelacc_DW.is_ACC_ON_MODE) {
case IN_LeadVehicle_Detected_Follow:
modelacc_Y.Acceleration_Mode = 2.0;
if (modelacc_U.RadarInput_DriveVehicle == 0.0) {
modelacc_DW.is_ACC_ON_MODE = mod_IN_LeadVehicle_Not_Detected;
modelacc_Y.Acceleration_Mode = 1.0;
} else if (((modelacc_U.RadarInput_DriveVehicle == 1.0) &&
(modelacc_Y.LeadVehicle_Speed < modelacc_U.Set_Speed)) ||
(modelacc_U.Time_Gap < modelacc_U.Set_Gap)) {
modelacc_DW.is_ACC_ON_MODE = IN_LeadVehicle_Speed_lessthan_S;
modelacc_Y.Acceleration_Mode = 4.0;
}
break;
case IN_LeadVehicle_Detected_Resume:
modelacc_Y.Acceleration_Mode = 3.0;
if ((modelacc_Y.DriveVehicle_Speed == modelacc_U.Set_Speed) &&
(modelacc_Y.LeadVehicle_Speed >= modelacc_U.Set_Speed) &&
(modelacc_U.Time_Gap >= modelacc_U.Set_Gap)) {
modelacc_DW.is_ACC_ON_MODE = IN_LeadVehicle_Detected_Follow;
modelacc_Y.Acceleration_Mode = 2.0;
} else if (modelacc_U.RadarInput_DriveVehicle == 0.0) {
modelacc_DW.is_ACC_ON_MODE = IN_LeadVehicle_Not_Detected_Res;
modelacc_Y.Acceleration_Mode = 1.0;
} else if ((modelacc_Y.DriveVehicle_Speed < modelacc_U.Set_Speed) &&
(modelacc_Y.LeadVehicle_Speed >
modelacc_Y.DriveVehicle_Speed) && (modelacc_U.Time_Gap >=
modelacc_U.Set_Gap)) {
modelacc_DW.is_ACC_ON_MODE = IN_LeadVehicle_Speed_equal_Set_;
modelacc_Y.Acceleration_Mode = 5.0;
}
break;
case mod_IN_LeadVehicle_Not_Detected:
modelacc_Y.Acceleration_Mode = 1.0;
if ((modelacc_U.RadarInput_DriveVehicle == 1.0) &&
(modelacc_Y.DriveVehicle_Speed == modelacc_U.Set_Speed) &&
(modelacc_Y.LeadVehicle_Speed >= modelacc_U.Set_Speed) &&
(modelacc_U.Time_Gap >= modelacc_U.Set_Gap)) {
modelacc_DW.is_ACC_ON_MODE = IN_LeadVehicle_Detected_Follow;
modelacc_Y.Acceleration_Mode = 2.0;
} else if (((modelacc_U.RadarInput_DriveVehicle == 1.0) &&
(modelacc_Y.LeadVehicle_Speed < modelacc_U.Set_Speed)) ||
(modelacc_U.Time_Gap < modelacc_U.Set_Gap)) {
modelacc_DW.is_ACC_ON_MODE = IN_LeadVehicle_Speed_lessthan_S;
modelacc_Y.Acceleration_Mode = 4.0;
}
break;
case IN_LeadVehicle_Not_Detected_Res:
modelacc_Y.Acceleration_Mode = 1.0;
break;
case IN_LeadVehicle_Speed_equal_Set_:
modelacc_Y.Acceleration_Mode = 5.0;
if ((modelacc_U.RadarInput_DriveVehicle == 0.0) ||
(modelacc_Y.DriveVehicle_Speed <= modelacc_U.Set_Speed)) {
modelacc_DW.is_ACC_ON_MODE = IN_LeadVehicle_Not_Detected_Res;
modelacc_Y.Acceleration_Mode = 1.0;
} else if (((modelacc_Y.DriveVehicle_Speed < modelacc_U.Set_Speed) &&
(modelacc_Y.LeadVehicle_Speed >
modelacc_Y.DriveVehicle_Speed)) || (modelacc_U.Time_Gap >=
modelacc_U.Set_Gap)) {
modelacc_DW.is_ACC_ON_MODE = IN_LeadVehicle_Detected_Resume;
modelacc_Y.Acceleration_Mode = 3.0;
} else if (((modelacc_Y.LeadVehicle_Speed < modelacc_U.Set_Speed) &&
(modelacc_Y.LeadVehicle_Speed <
modelacc_Y.DriveVehicle_Speed)) || (0.75 *
modelacc_U.Set_Gap == modelacc_U.Time_Gap)) {
modelacc_DW.is_ACC_ON_MODE = IN_LeadVehicle_Speed_lessthan_S;
modelacc_Y.Acceleration_Mode = 4.0;
}
break;
default:
/* case IN_LeadVehicle_Speed_lessthan_Set_Speed: */
modelacc_Y.Acceleration_Mode = 4.0;
if ((modelacc_U.RadarInput_DriveVehicle == 0.0) &&
(modelacc_Y.DriveVehicle_Speed == modelacc_U.Set_Speed)) {
modelacc_DW.is_ACC_ON_MODE = mod_IN_LeadVehicle_Not_Detected;
modelacc_Y.Acceleration_Mode = 1.0;
} else if ((modelacc_Y.LeadVehicle_Speed * 1.25 >=
modelacc_Y.DriveVehicle_Speed) &&
(modelacc_Y.LeadVehicle_Speed * 0.75 <=
modelacc_Y.DriveVehicle_Speed) &&
(modelacc_Y.DriveVehicle_Speed < modelacc_U.Set_Speed) &&
(modelacc_U.Time_Gap <= 1.25 * modelacc_U.Set_Gap) &&
(modelacc_U.Time_Gap >= 0.75 * modelacc_U.Set_Gap)) {
modelacc_DW.is_ACC_ON_MODE = IN_LeadVehicle_Speed_equal_Set_;
modelacc_Y.Acceleration_Mode = 5.0;
}
break;
}
}
break;
default:
/* case IN_ACC_STANDBY_MODE: */
modelacc_Y.Acceleration_Mode = 1.0;
if (modelacc_U.CruiseSwitch == 0.0) {
modelacc_DW.is_c3_modelacc = modelacc_IN_ACC_OFF_MODE;
modelacc_Y.Acceleration_Mode = 0.0;
} else if (modelacc_U.SetSwitch == 1.0) {
modelacc_DW.is_c3_modelacc = modelacc_IN_ACC_ON_MODE;
modelacc_DW.is_ACC_ON_MODE = IN_LeadVehicle_Detected_Follow;
modelacc_Y.Acceleration_Mode = 2.0;
}
break;
}
}
/* End of Chart: '/Chart' */
/* Outport: '/LeadVehicle_Detected' incorporates:
* Inport: '/RadarInput_DriveVehicle'
*/
modelacc_Y.LeadVehicle_Detected = modelacc_U.RadarInput_DriveVehicle;
}
/* Model initialize function */
void modelacc_initialize(void)
{
/* (no initialization code required) */
}
/* Model terminate function */
void modelacc_terminate(void)
{
/* (no terminate code required) */
}
/*
* File trailer for generated code.
*
* [EOF]
*/
Model Advisor Report
https://drive.google.com/file/d/1c9DG6gf8XzOXfNb8RGk72tMrDpKjwNI9/view?usp=sharing
Requirement Traceability Report
Requirements
Report
https://drive.google.com/file/d/1OJ4MVpu_gpFpv61pu-fLU1_pGLEJHKCG/view?usp=sharing
Conclusion: Hence we have build a model for Adaptive Cruise Control in Simulink. All the MBD related processes are followed. Requirement Tagging & Traceability, SLDD creation, Configuration Parameter changes, Model Advisor check & Code Generation