Project 2 Adaptive Cruise Control

                                                                                                                    EV BATCH - 17

Aim:

• To desing and Simulate Adaptive Cruise Control in matlab Simulink
• To developing Adaptive Cruise Control feature as per the Requirement Document using MATLAB Simulink.
• To Follow all the MBD related processes: Requirement Tagging & Traceability, SLDD creation, Configuration Parameter changes, Model Advisor check & Code Generation.
• To change in Configuration Parameters: enable “Support Floating Numbers” under Code Generation settings.
• To use Embedded Coder to generate the code.
• To consider If choosing code generation, Storage class for Input signals: Imported Extern; Storage class for Output signal: Export to File; Storage class for local signals: localizable; Storage class for calibration signals: Const.
• To choose sample time for all signals as 0.01s

Theory:

>> Adaptive Cruise Control (ACC):

                  

          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.

                 

Explanation:

• To create the word document for given question for better understanding and do requirement tag and that word document will place one particular folder for this whole model use that folder
• Then open the matlab and then open simulink blank model. Then go to modeling tab and click on the link to data Dictionary in the design data

                           

• Then create one new file  of SLDD file for data and open the that file in model explorer and add signals and date in that file is shown in give below figure 

           

• Then go to Library and add required block for builed the Adaptive Cruise Control model for given requirements 
• After that made connections as the requirement for the block it will given below

         

>> Requirement 1– Lead Vehicle:

                        

• Lead Vehicle is a vehicle which is driving in the road ahead of our drive vehicle. Two input signals (Signal Name: CameraInput_LeadVehicle & RadarInput_LeadVehicle).
• Ideally sensor fusion techniques will be deployed to process & analyze data from camera & radar. For complexity reasons, let’s not adapt to any such algorithms.
• We can simply add both the radar & camera inputs & the corresponding output is read as Speed profile output (Signal Name: LeadVehicle_Speed).
• Speed data of the lead vehicle is critical in implementing the Adaptive Cruise Control algorithm. The Model will given below figure 

                        

• For Lead vehicle Model use blocks of Input, Output and Add Block and made connections by giving in the requirements
• After made this block we made a Requirement tag for lead vehicle by right clicking on the block then clink on the requirement then click on the link to selection in word.

            

>> Requirement 2 – Drive Vehicle:

                      

• Drive Vehicle is the vehicle driven by the user & this is the vehicle which has ACC algorithm in it.
• Like the Lead Vehicle, Drive Vehicle algorithm also has 2 input signals (Signal Name: CameraInput_DriveVehicle, RadarInput_DriveVehicle) & one signal coming as an Input to this subsystem (Signal Name: Acceleration_Mode) – three inputs into this requirement in total.
• Like the above requirement, sensor fusion techniques will also be deployed here, for complexity reasons we are ignoring them.
• Two output signals come from this subsystem (Signal Name: DriveVehicle_Speed & LeadVehicle_Detected).
• Signal DriveVehicle_Speed is summation of three input signals mentioned above & LeadVehicle_Detected is renamed from Input Signal RadarInput_DriveVehicle by mere use of Signal Conversion block.

         

• For Drive vehicle Model use blocks of Input, Output and Add Block and made connections by giving in the requirements
• After made this block we made a Requirement tag for Drive vehicle by right clicking on the block then clink on the requirement then click on the link to selection in word.

        

>> Requirement 3 – Adaptive Cruise Control Algorithm:

                                          

• Adaptive Cruise Control feature has 3 major modes of operation: OFF Mode, STANDBY Mode & ON Mode. This particular requirement has to be implemented as state machine logic in Simulink.
• The input signals to this state machine system are (Signal Name: Time_Gap, Set_Speed, Set_Gap, CruiseSwitch, SetSwitch).
• Also, the output signals (Signal Name: DriveVehicle_Speed & LeadVehicle_Detected) from requirement-2 is fed back as an input signal into this state machine block.
• Additionally, output signal (Signal Name: LeadVehicle_Speed) from requirement-1 is given as an input signal to this state machine block as well.
• Output from this subsystem is a signal (Signal Name: Acceleration_Mode) which governs the vehicular speed of the drive vehicle which automatically adjusts its speed & velocity to match the lead vehicle.

 

          

                       

• For Adaptive Cruise Control Algorithm Model use blocks of Input, Output and Chart Block and made connections by giving in the requirements
• After made this block we made a Requirement tag for Adaptive Cruise Control Algorithm by right clicking on the block then clink on the requirement then click on the link to selection in word.

                   

>> Requirement 3a – ACC OFF MODE state logic:

• This is the default state inside state machine logic. Output signal Acceleration_Mode is at value 0 in this state.
• This state is governed by input signal CruiseSwitch.
• If CruiseSwitch is equal to 1, state ACC STANDBY mode will get activated. If CruiseSwitch is equal to 0, state ACC OFF mode will get activated, from either ACC ON mode or ACC STANDBY mode

                                                 

>> Requirement 3b – ACC STANDBY MODE state logic:

• This is the second activated state inside state machine logic. Output signal Acceleration_Mode is at value 1 in this state.
• This state is governed by both input signals CruiseSwitch & SetSwitch.
• If CruiseSwitch is equal to 1, state ACC STANDBY mode will get activated. If CruiseSwitch is equal to 0, state ACC OFF mode will get activated, from either ACC ON mode or ACC STANDBY mode
• If SetSwitch is equal to 1, state ACC ON mode will get activated. If SetSwitch is equal to 0, state ACC STANDBY mode will get activated.

                                                 

>> Requirement 3c – ACC ON MODE state logic:

This state will be activated when input signal SetSwitch is equal to 1. There are 6 sub states to this state logic: They are:

• LeadVehicle_Detected_Follow (Default)
• LeadVehicle_Not_Detected
• LeadVehicle_Detected_Resume
• LeadVehicle_Not_Detected_Resume
• LeadVehicle_Speed_lessthan_Set_Speed
• LeadVehicle_Speed_equal_Set_Speed

              

>> Requirement 3c (i) – LeadVehicle_Detected_Follow (ACC ON MODE):

• This is the default sub state inside ACC ON MODE state. Output signal Acceleration_Mode is equal to 2.
• Condition to transit from LeadVehicle_Detected_Follow to LeadVehicle_Not_Detected; Input signal condition LeadVehicle_Detected == 0.
• Condition to transit from LeadVehicle_Detected_Follow to LeadVehicle_Speed_lessthan_Set_Speed; Input Signals condition (LeadVehicle_Detected == 1) && (LeadVehicle_Speed < Set_Speed) || (Time_Gap < Set_Gap).

>> Requirement 3c (ii) – LeadVehicle_Not_Detected (ACC ON MODE):

• Output signal Acceleration_Mode is equal to 1.
• Condition to transit from LeadVehicle_Not_Detected to LeadVehicle_Detected_Follow; Input signals condition [(LeadVehicle_Detected==1) && (DriveVehicle_Speed == Set_Speed) && (LeadVehicle_Speed >= Set_Speed) && (Time_Gap >= Set_Gap)]
• Condition to transit from LeadVehicle_Not_Detected to LeadVehicle_Speed_lessthan_Set_Speed; Input signals condition [(LeadVehicle_Detected == 1) && (LeadVehicle_Speed < Set_Speed) || (Time_Gap < Set_Gap)]

>> Requirement 3c (iii) – LeadVehicle_Detected_Resume (ACC ON MODE):

• Output signal Acceleration_Mode is equal to 3.
• Condition to transit from LeadVehicle_Detected_Resume to LeadVehicle_Detected_Follow; Input signals condition [(DriveVehicle_Speed == Set_Speed) && (LeadVehicle_Speed >= Set_Speed) && (Time_Gap >= Set_Gap)]
• Condition to transit from LeadVehicle_Detected_Resume to LeadVehicle_Not_Detected_Resume; Input signal condition LeadVehicle_Detected==0.
• Condition to transit from LeadVehicle_Detected_Resume to LeadVehicle_Speed_equal_Set_Speed; Input Signal condition [(DriveVehicle_Speed < Set_Speed) && (LeadVehicle_Speed > DriveVehicle_Speed) && (Time_Gap >= Set_Gap)]

>>  Requirement 3c (iv) - LeadVehicle_Not_Detected_Resume (ACC ON MODE):

• Output signal Acceleration_Mode is equal to 1.

>> Requirement 3c (v) - LeadVehicle_Speed_lessthan_Set_Speed (ACC ON MODE):

• Output signal Acceleration_Mode is equal to 4.
• Condition to transit from LeadVehicle_Speed_lessthan_Set_Speed to LeadVehicle_Not_Detected; Input signal condition [(LeadVehicle_Detected == 0) && (DriveVehicle_Speed == Set_Speed)]
• Condition to transit from LeadVehicle_Speed_lessthan_Set_Speed to LeadVehicle_Speed_equal_Set_Speed; Input signals condition [((LeadVehicle_Speed*1.25>=DriveVehicle_Speed) && (LeadVehicle_Speed * 0.75<=DriveVehicle_Speed)) && (DriveVehicle_Speed < Set_Speed) && ((Time_Gap<=1.25*Set_Gap) && (Time_Gap >=0.75*Set_Gap))]

>> Requirement 3c (vi) - LeadVehicle_Speed_equal_Set_Speed (ACC ON MODE):

• Output signal Acceleration_Mode is equal to 5.
• Condition to transit from LeadVehicle_Speed_equal_Set_Speed to LeadVehicle_Not_Detected_Resume; Input signal conditions is [(LeadVehicle_Detected == 0) || (DriveVehicle_Speed <= Set_Speed)]
• Condition to transit from LeadVehicle_Speed_equal_Set_Speed to LeadVehicle_Detected_Resume; Input signal conditions [(DriveVehicle_Speed < Set_Speed) && (LeadVehicle_Speed > DriveVehicle_Speed) || (Time_Gap >= Set_Gap)]
• Condition to transit from LeadVehicle_Speed_equal_Set_Speed to LeadVehicle_Speed_lessthan_Set_Speed; Input signals conditions [(LeadVehicle_Speed It will shown in below figure .

• After completions of the connection as per the requirements given above then go to the Modeling and then click on the Symbols pane in Design data 
• after that mention the given symbols to inputs and output. It show in below.

•  After create the model then go to model settings and then click on the solver confirmation parameters the change the solver selection type to fixed and solver to discrete and then change the solver step size to 0.01sec then click on okey, its shown in below figure 

                      

• After that go to code generation and change the systen target file to ert.tle (embedded coder) then click on okey. Then after open the interface and tick on the floating point numbers then click okey, its shown on given below figers

    

• After completion of all this steps go to modeling tab and click on the model advisor then select the system selector and then click on the modeling standards for MAB then click on the run check. This is for checking of designed model in the standards of MAB
• After that generat a report of model check in HTML file then name that report and select the path for report that is shown in given below figure 

               

• Then report shown like this

                  

• After completion of model advisor check then Go to apps tab and click on the embedded coder, then that new tab will open that is C code tab.

• On that tab Click on the build then the code will generate then it appears like gien below figure .

Results:

/*

 

* Academic License - for use in teaching, academic research, and meeting

 

* course requirements at degree granting institutions only. Not for

 

* government, commercial, or other organizational use.

 

* File: m4final_proj.c

 

* Code generated for Simulink model 'm4final_proj'.

 

* Model version : 1.14

 

* Simulink Coder version : 9.7 (R2022a) 13-Nov-2021

 

* C/C++ source code generated on : Sun Jun 26 18:59:01 2022

 

* Target selection: ert.tlc

 

* Embedded hardware selection: Intel->x86-64 (Windows64)

 

* Code generation objectives: Unspecified

 

* Validation result: Not run 

 

*/

 

#include "m4final_proj.h"

 

#include "rtwtypes.h"

 

/* Named constants for Chart: '/ACC_Logic' */

 

#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 m4f_IN_LeadVehicle_Not_Detected ((uint8_T)3U)

 

#define m4final_pro_IN_ACC_STANDBY_MODE ((uint8_T)3U)

 

#define m4final_proj_IN_ACC_OFF_MODE ((uint8_T)1U)

 

#define m4final_proj_IN_ACC_ON_MODE ((uint8_T)2U)

 

#define m4final_proj_IN_NO_ACTIVE_CHILD ((uint8_T)0U)

  

/* Block states (default storage) */

 

DW_m4final_proj_T m4final_proj_DW;

 

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

 

ExtU_m4final_proj_T m4final_proj_U;

 

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

 

ExtY_m4final_proj_T m4final_proj_Y;

 

/* Real-time model */

 

static RT_MODEL_m4final_proj_T m4final_proj_M_;

 

RT_MODEL_m4final_proj_T *const m4final_proj_M = &m4final_proj_M_;

 

/* Model step function */

 

void m4final_proj_step(void)

 

{

 

real_T rtb_DriveVehicle_Speed;

 

uint8_T rtb_LeadVehicle_Speed;

 

/* Outputs for Atomic SubSystem: '/LeadVehicle' */

 

/* Sum: '/Add' incorporates:

 

* Inport: '/CameraInput_LeadVehicle'

 

* Inport: '/RadarInput_LeadVehicle'

 

*/

  

rtb_LeadVehicle_Speed = (uint8_T)(m4final_proj_U.CameraInput_LeadVehicle +

 

m4final_proj_U.RadarInput_LeadVehicle);

 

/* End of Outputs for SubSystem: '/LeadVehicle' */

 

/* Outputs for Atomic SubSystem: '/DriveVehicle' */

  

/* Sum: '/Add' incorporates:

 

* Inport: '/CameraInput_DriveVehicle'

 

* Inport: '/RadarInput_DriveVehicle'

 

* UnitDelay: '/Unit Delay'

 

*/

 

rtb_DriveVehicle_Speed = ((real_T)m4final_proj_U.CameraInput_DriveVehicle +

  

m4final_proj_Y.Acceleration_Mode) + (real_T)

  

m4final_proj_U.RadarInput_DriveVehicle;

 

/* End of Outputs for SubSystem: '/DriveVehicle' */

 

/* Chart: '/ACC_Logic' incorporates:

 

* Inport: '/CruiseSwitch'

 

* Inport: '/RadarInput_DriveVehicle'

 

* Inport: '/SetSwitch'

 

* Inport: '/Set_Gap'

 

* Inport: '/Set_Speed'

 

* Inport: '/Time_Gap'

 

* UnitDelay: '/Unit Delay'

 

*/

 

if (m4final_proj_DW.is_active_c3_m4final_proj == 0U) {

  

m4final_proj_DW.is_active_c3_m4final_proj = 1U;

  

m4final_proj_DW.is_c3_m4final_proj = m4final_proj_IN_ACC_OFF_MODE;

  

m4final_proj_Y.Acceleration_Mode = 0.0;

 

} else {

 

switch (m4final_proj_DW.is_c3_m4final_proj) {

 

case m4final_proj_IN_ACC_OFF_MODE:

  

m4final_proj_Y.Acceleration_Mode = 0.0;

 

if (m4final_proj_U.CruiseSwitch) {

  

m4final_proj_DW.is_c3_m4final_proj = m4final_pro_IN_ACC_STANDBY_MODE;

  

m4final_proj_Y.Acceleration_Mode = 1.0;

 

}

 

break;

 

case m4final_proj_IN_ACC_ON_MODE:

 

if (!m4final_proj_U.CruiseSwitch) {

 

m4final_proj_DW.is_ACC_ON_MODE = m4final_proj_IN_NO_ACTIVE_CHILD;

 

m4final_proj_DW.is_c3_m4final_proj = m4final_proj_IN_ACC_OFF_MODE;

 

m4final_proj_Y.Acceleration_Mode = 0.0; 

 

} else if (!m4final_proj_U.SetSwitch) {

 

m4final_proj_DW.is_ACC_ON_MODE = m4final_proj_IN_NO_ACTIVE_CHILD;

  

m4final_proj_DW.is_c3_m4final_proj = m4final_pro_IN_ACC_STANDBY_MODE;

  

m4final_proj_Y.Acceleration_Mode = 1.0;

 

} else {

 

switch (m4final_proj_DW.is_ACC_ON_MODE) {

 

case IN_LeadVehicle_Detected_Follow:

  

m4final_proj_Y.Acceleration_Mode = 2.0;

 

if (((m4final_proj_U.RadarInput_DriveVehicle == 1) &&

 

(rtb_LeadVehicle_Speed < m4final_proj_U.Set_Speed)) ||

 

(m4final_proj_U.Time_Gap < m4final_proj_U.Set_Gap)) {

  

m4final_proj_DW.is_ACC_ON_MODE = IN_LeadVehicle_Speed_lessthan_S;

  

m4final_proj_Y.Acceleration_Mode = 4.0;

  

} else if (m4final_proj_U.RadarInput_DriveVehicle == 0) {

 

m4final_proj_DW.is_ACC_ON_MODE = m4f_IN_LeadVehicle_Not_Detected;

  

m4final_proj_Y.Acceleration_Mode = 1.0;

 

}

 

break;

 

case IN_LeadVehicle_Detected_Resume:

  

m4final_proj_Y.Acceleration_Mode = 3.0;

 

if ((rtb_DriveVehicle_Speed == m4final_proj_U.Set_Speed) &&

 

(rtb_LeadVehicle_Speed >= m4final_proj_U.Set_Speed) &&

 

(m4final_proj_U.Time_Gap >= m4final_proj_U.Set_Gap)) {

  

m4final_proj_DW.is_ACC_ON_MODE = IN_LeadVehicle_Detected_Follow;

  

m4final_proj_Y.Acceleration_Mode = 2.0;

 

} else if (m4final_proj_U.RadarInput_DriveVehicle == 0) {

  

m4final_proj_DW.is_ACC_ON_MODE = IN_LeadVehicle_Not_Detected_Res;

  

m4final_proj_Y.Acceleration_Mode = 1.0;

 

} else if ((rtb_DriveVehicle_Speed < m4final_proj_U.Set_Speed) &&

 

(rtb_LeadVehicle_Speed > rtb_DriveVehicle_Speed) &&

 

(m4final_proj_U.Time_Gap >= m4final_proj_U.Set_Gap)) {

  

m4final_proj_DW.is_ACC_ON_MODE = IN_LeadVehicle_Speed_equal_Set_;

  

m4final_proj_Y.Acceleration_Mode = 5.0;

  

}

 

break;

  

case m4f_IN_LeadVehicle_Not_Detected:

 

m4final_proj_Y.Acceleration_Mode = 1.0;

 

if ((m4final_proj_U.RadarInput_DriveVehicle == 1) &&

 

(rtb_DriveVehicle_Speed == m4final_proj_U.Set_Speed) &&

 

(rtb_LeadVehicle_Speed >= m4final_proj_U.Set_Speed) &&

 

(m4final_proj_U.Time_Gap >= m4final_proj_U.Set_Gap)) {

  

m4final_proj_DW.is_ACC_ON_MODE = IN_LeadVehicle_Detected_Follow;

 

m4final_proj_Y.Acceleration_Mode = 2.0;

 

} else if (((m4final_proj_U.RadarInput_DriveVehicle == 1) &&

 

(rtb_LeadVehicle_Speed < m4final_proj_U.Set_Speed)) || 

 

(m4final_proj_U.Time_Gap < m4final_proj_U.Set_Gap)) {

  

m4final_proj_DW.is_ACC_ON_MODE = IN_LeadVehicle_Speed_lessthan_S;

  

m4final_proj_Y.Acceleration_Mode = 4.0;

 

} 

 

break; 

 

case IN_LeadVehicle_Not_Detected_Res:

  

m4final_proj_Y.Acceleration_Mode = 1.0;

 

break;

 

case IN_LeadVehicle_Speed_equal_Set_:

  

m4final_proj_Y.Acceleration_Mode = 5.0;

  

if (((rtb_DriveVehicle_Speed < m4final_proj_U.Set_Speed) &&

 

(rtb_LeadVehicle_Speed > rtb_DriveVehicle_Speed)) ||

 

(m4final_proj_U.Time_Gap >= m4final_proj_U.Set_Gap)) { 

 

m4final_proj_DW.is_ACC_ON_MODE = IN_LeadVehicle_Detected_Resume;

  

m4final_proj_Y.Acceleration_Mode = 3.0;

 

} else if (((real_T)rtb_LeadVehicle_Speed * 1.25 >=

 

rtb_DriveVehicle_Speed) && ((real_T)rtb_LeadVehicle_Speed *

 

0.75 <= rtb_DriveVehicle_Speed) && (rtb_DriveVehicle_Speed

  

< m4final_proj_U.Set_Speed) && ((m4final_proj_U.Time_Gap <=

 

1.25 * (real_T)m4final_proj_U.Set_Gap) && (m4final_proj_U.Time_Gap >=

 

0.75 * (real_T)m4final_proj_U.Set_Gap))) {

  

m4final_proj_DW.is_ACC_ON_MODE = IN_LeadVehicle_Speed_lessthan_S;

 

m4final_proj_Y.Acceleration_Mode = 4.0;

 

} else if ((m4final_proj_U.RadarInput_DriveVehicle == 0) ||

 

(rtb_DriveVehicle_Speed <= m4final_proj_U.Set_Speed)) {

  

m4final_proj_DW.is_ACC_ON_MODE = IN_LeadVehicle_Not_Detected_Res;

  

m4final_proj_Y.Acceleration_Mode = 1.0;

 

}

  

break;

 

default:

 

/* case IN_LeadVehicle_Speed_lessthan_Set_Speed: */ 

 

m4final_proj_Y.Acceleration_Mode = 4.0;

 

if (((rtb_LeadVehicle_Speed < m4final_proj_U.Set_Speed) &&

 

(rtb_LeadVehicle_Speed < rtb_DriveVehicle_Speed)) || (0.75 *

 

(real_T)m4final_proj_U.Set_Gap == m4final_proj_U.Time_Gap)) {

  

m4final_proj_DW.is_ACC_ON_MODE = IN_LeadVehicle_Speed_equal_Set_;

  

m4final_proj_Y.Acceleration_Mode = 5.0;

 

} else if ((m4final_proj_U.RadarInput_DriveVehicle == 0) &&

 

(rtb_DriveVehicle_Speed == m4final_proj_U.Set_Speed)) {

  

m4final_proj_DW.is_ACC_ON_MODE = m4f_IN_LeadVehicle_Not_Detected;

  

m4final_proj_Y.Acceleration_Mode = 1.0;

 

}

 

break;

 

}

 

}

 

break;

 

default:

 

/* case IN_ACC_STANDBY_MODE: */

 

m4final_proj_Y.Acceleration_Mode = 1.0;

 

if (!m4final_proj_U.CruiseSwitch) {

 

m4final_proj_DW.is_c3_m4final_proj = m4final_proj_IN_ACC_OFF_MODE;

 

m4final_proj_Y.Acceleration_Mode = 0.0;

 

} else if (m4final_proj_U.SetSwitch) {

 

m4final_proj_DW.is_c3_m4final_proj = m4final_proj_IN_ACC_ON_MODE;

 

m4final_proj_DW.is_ACC_ON_MODE = IN_LeadVehicle_Detected_Follow;

 

m4final_proj_Y.Acceleration_Mode = 2.0;

 

}

 

break;

 

}

 

}

 

/* End of Chart: '/ACC_Logic' */

 

}

 

/* Model initialize function */

 

void m4final_proj_initialize(void)

 

{

 

/* (no initialization code required) */

 

}

 

/* Model terminate function */

 

void m4final_proj_terminate(void)

 

{

 

/* (no terminate code required) */

 

}

 

/*

 

* File trailer for generated code.

 

* [EOF]

 

*/

Conclusion:

         Hence the Adaptive Cruise Control model is desinged and did all the necessary requirements and achive the requirements and observe the model