Project 2 Adaptive Cruise Control

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.

AnStandard 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 stops & 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 stops & goes support the driver even in heavy traffic and traffic jams.

Image:-Adaptive Cruise Control

Simulink model:-

Objective of Main Project:-

1. Developing Adaptive Cruise Control feature as per the Requirement Document using MATLAB Simulink.
2. Follow all the MBD related processes: Requirement Tagging & Traceability, SLDD creation, Configuration Parameter changes, Model Advisor check & Code Generation.
3. In Configuration Parameters: enable “Support Floating Numbers” under Code Generation settings.
4. Use Embedded Coder to generate the code.
5. 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.
6. Choose sample time for all signals as 0.01s

Blocks used in this model is as follows:-

Total Simulink Model:-

Subsytem inside lookas as follows:-

Requirement 1– Lead Vehicle:-

1. 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).
2. 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.
3. We can simply add both the radar & camera inputs & the corresponding output is read as Speed profile output (Signal Name: LeadVehicle_Speed).
4. Speed data of the lead vehicle is critical in implementing the Adaptive Cruise Control algorithm.

Model:-

Subsytem inside lookas as follows:-

>>The requirements are fuilfilled using the inport & outport blocks and the Add block. It is now created as a sub-system and Named as the Requirement 1.

Requirement 2 – Drive Vehicle:-

1. Drive Vehicle is the vehicle driven by the user & this is the vehicle which has ACC algorithm in it.
2. 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.
3. Like the above requirement, sensor fusion techniques will also be deployed here, for complexity reasons we are ignoring them.
4. Two output signals come from this subsystem (Signal Name: DriveVehicle_Speed & LeadVehicle_Detected).
5. Signal DriveVehicle_Speed is summation of three input signals mentioned above & LeadVehicle_Detected is renamed from Input Signal RadarInput_DriveVehicle by were use of Signal Conversion block.

Model:-

Subsytem inside lookas as follows:-

>>The requirement is modeled exactly. We have also used the blocks (Add block, Signal conversion block) and signal names(CameraInput_DriveVehicle, RadarInput_DriveVehicle & Acceleration_Mode) suggested in the requirement.

>>The inport and outport blocks are used to create the input & output ports for the subsystem.

Requirement 3 – Adaptive Cruise Control Algorithm:-

1. 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.
2. The input signals to this state machine system are (Signal Name: Time_Gap, Set_Speed, Set_Gap, CruiseSwitch, SetSwitch).
3. 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.
4. Additionally, output signal (Signal Name: LeadVehicle_Speed) from requirement-1 is given as an input signal to this state machine block as well.
5. 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.

Model:-

Subsytem inside lookas as follows:-

>>>The different state machines, state actions & the transition conditions are also given in the requirement. We will look at them to create a complete algorithm within the chart block.

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 < Set_Speed) && (LeadVehicle_Speed < DriveVehicle_Speed) || (Time_Gap==0.75*Set_Gap)].

The above Requirement from(3a to 3C(vi)) The Algrathis is implemented inside the Chart as follows.:-

Algarithem_chart:-

>>>Here the output of the ACC algorithm (Signal name : Acceleration_Mode) is fed back as input to requirement 2 (Drive Vehicle). The output is fedback using a delay block, which delays the signal for a duration and sends it back as input. The delay block is used to avoid algebraic loop errors in simulink. They occur when the input is directly fed through by the output of the same block.

>>>Now all these requirements must be contained in a single subsystem. This will help in generating the code for the entire model in a simpler manner.

Now the process related to MBD must be followed.

Requirement Tagging & Traceability:-

Create the Word Document for the requirement what we done to craete the Model in simulink as follows.

For Requirement_1:-

Developing the ACC model as per the requirements developed:

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).
•	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.

Tagging as follows:-

Step@1:-

Right Click on the Requirement_1 subsystem and click on the Requirement and Choose the Link to copy in the Word as follows.

>>Now the Requirement-! Subsystem will be liked to the word document as follows.

For Requirement_2:-

Create the Word Document for the requirement what we done to craete the Model in simulink as follows.

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.

Tagging as follows:-

Step@1:-

Right Click on the Requirement_1 subsystem and click on the Requirement and Choose the Link to copy in the Word as follows.

>>Now the Requirement-! Subsystem will be liked to the word document as follows.

For Requirement_3:-

Create the Word Document for the requirement what we done to craete the Model in simulink as follows.

Tagging as follows:-

Step@1:-

Right Click on the Requirement_1 subsystem and click on the Requirement and Choose the Link to copy in the Word as follows.

>>Now the Requirement-! Subsystem will be liked to the word document as follows.

Tagging and requirements are created successfully

Creation Of "SLDD" File:-

>> We have named the signals. Now we must create a data dictionary and define all those signals. Use the model properties under modeling settings to create and link the data dictionary to the model.

Step@1

In this step open the Simulink Editor window , and select the modeling tab as follows.

Step@2

>>From the selection Modeling window click on the model settings and click on the model perameters as follows.

>>then we get the windoe as follows.

Step@3

>> From the above data select the " External data icon".

>>Click on the apply and ok

Step@4

Now select the External data which is left side bottom of the simulnk window as follows.

>>Then A new windoew is opena s follows.

Step@5

Now add the variable as follows.

'

the inputs and output signals are resolved so the signals will take the values from sldd and pass them to the logical blocks. Otherwise, it may take some junk values if it is unresolved

Model Update:-

The model update is done by Ctrl-D. this is done to check for any static errors. If no errors are coming the model is working fine without any errors.

Simulation:-

The model is simulated too for checking for errors and warnings

Configuration Parameter Update:-

Various configuration parameters are updated as per the code generation the solver type should be fixed for code generation

MODEL ADVISORY:-

For checking the model we are used the model advisory tool

Goto Modeling and click on th Model Advisor Icon and choose the Model advisory as follows

>>>Now click on the selevtion requirements for the Model Advisory checks

>>And click n the Run checks As follows

>>After the click on the Report as follows.

Then Choose the reqired formet for the modeling as follows.

>>The generated Report As foillows.

Code generation:-

Goto configaration parameters and select the file as "ert.tlc"

After theat select the Apps Tab choose the embedded coder and select the C coder as follows.

Code Report as follows:-

Generated code :-

Generated Total Code view:-

/*
 * Event Support License -- for demonstration use and event support.  Not
 * for government, research, commercial, or other organizational use.
 *
 * File: ACC_Project_2.c
 *
 * Code generated for Simulink model 'ACC_Project_2'.
 *
 * Model version                  : 1.6
 * Simulink Coder version         : 9.7 (R2022a) 13-Nov-2021
 * C/C++ source code generated on : Mon Feb 27 18:02:07 2023
 *
 * Target selection: ert.tlc
 * Embedded hardware selection: Intel->x86-64 (Windows64)
 * Code generation objectives: Unspecified
 * Validation result: Not run
 */

#include "ACC_Project_2.h"
#include "rtwtypes.h"

/* Named constants for Chart: '<S1>/Requirement3' */
#define ACC_IN_LeadVehicle_Not_Detected ((uint8_T)3U)
#define ACC_Project_2_IN_OFF_mode      ((uint8_T)1U)
#define ACC_Project_2_IN_ON_mode       ((uint8_T)2U)
#define ACC_Project_2_IN_Standby_mode  ((uint8_T)3U)
#define ACC_Project__IN_NO_ACTIVE_CHILD ((uint8_T)0U)
#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)

/* Block states (default storage) */
DW_ACC_Project_2_T ACC_Project_2_DW;

/* External inputs (root inport signals with default storage) */
ExtU_ACC_Project_2_T ACC_Project_2_U;

/* External outputs (root outports fed by signals with default storage) */
ExtY_ACC_Project_2_T ACC_Project_2_Y;

/* Real-time model */
static RT_MODEL_ACC_Project_2_T ACC_Project_2_M_;
RT_MODEL_ACC_Project_2_T *const ACC_Project_2_M = &ACC_Project_2_M_;

/* Model step function */
void ACC_Project_2_step(void)
{
  real_T rtb_Add;
  real_T rtb_Add_i;

  /* Sum: '<S3>/Add' incorporates:
   *  Inport: '<Root>/CameraInput_LeadVehicle'
   *  Inport: '<Root>/RadarInput_LeadVehicle'
   */
  rtb_Add = ACC_Project_2_U.CameraInput_LeadVehicle +
    ACC_Project_2_U.RadarInput_LeadVehicle;

  /* Sum: '<S4>/Add' incorporates:
   *  Inport: '<Root>/ RadarInput_DriveVehicle'
   *  Inport: '<Root>/Acceleration_Mode1'
   *  Inport: '<Root>/CameraInput_DriveVehicle'
   */
  rtb_Add_i = (ACC_Project_2_U.CameraInput_DriveVehicle +
               ACC_Project_2_U.Acceleration_Mode1) +
    ACC_Project_2_U.RadarInput_DriveVehicle;

  /* Chart: '<S1>/Requirement3' incorporates:
   *  Inport: '<Root>/ RadarInput_DriveVehicle'
   *  Inport: '<Root>/CruiseSwitch'
   *  Inport: '<Root>/SetSwitch'
   *  Inport: '<Root>/Set_Gap'
   *  Inport: '<Root>/Set_Speed'
   *  Inport: '<Root>/Time_Gap'
   */
  if (ACC_Project_2_DW.is_active_c3_ACC_Project_2 == 0U) {
    ACC_Project_2_DW.is_active_c3_ACC_Project_2 = 1U;
    ACC_Project_2_DW.is_c3_ACC_Project_2 = ACC_Project_2_IN_OFF_mode;

    /* Outport: '<Root>/Acceleration_Mode' */
    ACC_Project_2_Y.Acceleration_Mode = 0.0;
  } else {
    switch (ACC_Project_2_DW.is_c3_ACC_Project_2) {
     case ACC_Project_2_IN_OFF_mode:
      /* Outport: '<Root>/Acceleration_Mode' */
      ACC_Project_2_Y.Acceleration_Mode = 0.0;
      if (ACC_Project_2_U.CruiseSwitch == 1.0) {
        ACC_Project_2_DW.is_c3_ACC_Project_2 = ACC_Project_2_IN_Standby_mode;

        /* Outport: '<Root>/Acceleration_Mode' */
        ACC_Project_2_Y.Acceleration_Mode = 1.0;
      }
      break;

     case ACC_Project_2_IN_ON_mode:
      if (ACC_Project_2_U.CruiseSwitch == 0.0) {
        ACC_Project_2_DW.is_ON_mode = ACC_Project__IN_NO_ACTIVE_CHILD;
        ACC_Project_2_DW.is_c3_ACC_Project_2 = ACC_Project_2_IN_OFF_mode;

        /* Outport: '<Root>/Acceleration_Mode' */
        ACC_Project_2_Y.Acceleration_Mode = 0.0;
      } else if (ACC_Project_2_U.SetSwitch == 0.0) {
        ACC_Project_2_DW.is_ON_mode = ACC_Project__IN_NO_ACTIVE_CHILD;
        ACC_Project_2_DW.is_c3_ACC_Project_2 = ACC_Project_2_IN_Standby_mode;

        /* Outport: '<Root>/Acceleration_Mode' */
        ACC_Project_2_Y.Acceleration_Mode = 1.0;
      } else {
        switch (ACC_Project_2_DW.is_ON_mode) {
         case IN_LeadVehicle_Detected_Follow:
          /* Outport: '<Root>/Acceleration_Mode' */
          ACC_Project_2_Y.Acceleration_Mode = 2.0;
          if (rtb_Add_i == 0.0) {
            ACC_Project_2_DW.is_ON_mode = ACC_IN_LeadVehicle_Not_Detected;

            /* Outport: '<Root>/Acceleration_Mode' */
            ACC_Project_2_Y.Acceleration_Mode = 1.0;
          } else if (((rtb_Add_i == 1.0) && (rtb_Add < ACC_Project_2_U.Set_Speed))
                     || (ACC_Project_2_U.Time_Gap < ACC_Project_2_U.Set_Gap)) {
            ACC_Project_2_DW.is_ON_mode = IN_LeadVehicle_Speed_lessthan_S;

            /* Outport: '<Root>/Acceleration_Mode' */
            ACC_Project_2_Y.Acceleration_Mode = 4.0;
          }
          break;

         case IN_LeadVehicle_Detected_Resume:
          /* Outport: '<Root>/Acceleration_Mode' */
          ACC_Project_2_Y.Acceleration_Mode = 3.0;
          if ((ACC_Project_2_U.RadarInput_DriveVehicle <
               ACC_Project_2_U.Set_Speed) && (rtb_Add >
               ACC_Project_2_U.RadarInput_DriveVehicle) &&
              (ACC_Project_2_U.Time_Gap >= ACC_Project_2_U.Set_Gap)) {
            ACC_Project_2_DW.is_ON_mode = IN_LeadVehicle_Speed_equal_Set_;

            /* Outport: '<Root>/Acceleration_Mode' */
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Results:-

>>> After implementing the ACC model run the simulation. So the model is running successfully without any errors then the Adaptive Cruise Control works as per the requirement

>>> The model is running successfully without any error.

Conclusion:-

Hence. The Adaptive Cruise Control feature is developed as per the Requirement Document using MATLAB Simulink