Project 2 Adaptive Cruise Control
Project: Adaptive Cruise Control (ACC)
Aim of the Project:The aim of this project is to develop an Adaptive Cruise Control (ACC) system for passenger cars using MATLAB Simulink. The ACC system will automate speed control and maintain a safe distance from the preceding vehicle, improving driver comfort and reducing the risk of accidents.
Description:
The Adaptive Cruise Control feature allows the host vehicle to adapt its speed according to the flow of traffic. By utilizing a radar sensor installed at the front of the vehicle, the system continuously monitors the road ahead. When the road is clear, the ACC system maintains the speed set by the driver. However, if a slower vehicle is detected within the detection range, the system gently reduces speed by releasing the accelerator or actively engaging the brake control system. It also automatically accelerates to the driver's desired speed when the preceding vehicle speeds up or changes lanes.
Model:
The project utilizes MATLAB Simulink to develop the ACC system. The model consists of three main components: the Lead Vehicle, Drive Vehicle, and Adaptive Cruise Control Algorithm. The Lead Vehicle component processes data from camera and radar inputs to determine the speed of the lead vehicle. The Drive Vehicle component receives inputs from the camera and radar sensors and calculates the speed of the host vehicle, as well as detects the presence of a lead vehicle. The Adaptive Cruise Control Algorithm component implements the logic for the ACC system's different modes of operation, including OFF Mode, STANDBY Mode, and ON Mode.
Simulation Model:
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.
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.
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.
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
Requirement Taging :
SLDD creation:
Model Advisor Report Ganeration:
Code Ganeration Report:
Results:
Upon completion of the project, the developed ACC system will automate speed control and maintain a safe distance from the preceding vehicle. The system will enhance driver comfort by reducing the need for constant speed adjustments and allowing the driver to concentrate more on the road. The ACC algorithm will be implemented as a state machine in MATLAB Simulink, ensuring smooth transitions between different modes based on input signals. The final result will be a functional ACC system that can be integrated into passenger cars to improve driving experience and road safety.
Code:-
/*
* Event Support License -- for demonstration use and event support. Not
* for government, research, commercial, or other organizational use.
*
* File: Project_2.c
*
* Code generated for Simulink model 'Project_2'.
*
* Model version : 1.19
* Simulink Coder version : 9.9 (R2023a) 19-Nov-2022
* C/C++ source code generated on : Wed Jul 12 20:24:51 2023
*
* Target selection: ert.tlc
* Embedded hardware selection: Intel->x86-64 (Windows64)
* Code generation objectives: Unspecified
* Validation result: Not run
*/
#include "Project_2.h"
#include "rtwtypes.h"
#include
#include "rt_nonfinite.h"
#include "Project_2_private.h"
/* Named constants for Chart: '/ACC_Algorithm' */
#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 Pro_IN_LeadVehicle_Not_Detected ((uint8_T)3U)
#define Project_2_IN_NO_ACTIVE_CHILD ((uint8_T)0U)
#define Project_2_IN_OFF_MODE ((uint8_T)1U)
#define Project_2_IN_ON_MODE ((uint8_T)2U)
#define Project_2_IN_STANDBY_MODE ((uint8_T)3U)
/* Block states (default storage) */
DW_Project_2_T Project_2_DW;
/* External outputs (root outports fed by signals with default storage) */
ExtY_Project_2_T Project_2_Y;
/* Real-time model */
static RT_MODEL_Project_2_T Project_2_M_;
RT_MODEL_Project_2_T *const Project_2_M = &Project_2_M_;
/* Model step function */
void Project_2_step(void)
{
real_T tmp;
/* Sum: '/Sum' incorporates:
* Inport: '/CameraInput_LeadVehicle'
* Inport: '/RadarInput_LeadVehicle'
*/
LeadVehicle_Speed = (uint8_T)(CameraInput_LeadVehicle + RadarInput_LeadVehicle);
/* Sum: '/Add' incorporates:
* Inport: '/CameraInput_DriveVehicle'
* Inport: '/RadarInput_DriveVehicle'
* UnitDelay: '/UnitDelay'
*/
tmp = floor(((real_T)CameraInput_DriveVehicle + Project_2_Y.Acceleration_Mode)
+ (real_T)RadarInput_DriveVehicle);
if (rtIsNaN(tmp) || rtIsInf(tmp)) {
tmp = 0.0;
} else {
tmp = fmod(tmp, 256.0);
}
/* Sum: '/Add' */
DriveVehicle_Speed = (uint8_T)(tmp < 0.0 ? (int32_T)(uint8_T)-(int8_T)(uint8_T)
-tmp : (int32_T)(uint8_T)tmp);
/* SignalConversion: '/Signal Conversion' incorporates:
* Inport: '/RadarInput_DriveVehicle'
*/
LeadVehicle_Detected = RadarInput_DriveVehicle;
/* Chart: '/ACC_Algorithm' incorporates:
* Inport: '/CruiseSwitch'
* Inport: '/SetSwitch'
* Inport: '/Set_Gap'
* Inport: '/Set_Speed'
* Inport: '/Time_Gap'
* UnitDelay: '/UnitDelay'
*/
if (Project_2_DW.is_active_c1_Project_2 == 0U) {
Project_2_DW.is_active_c1_Project_2 = 1U;
Project_2_DW.is_c1_Project_2 = Project_2_IN_OFF_MODE;
Project_2_Y.Acceleration_Mode = 0.0;
} else {
switch (Project_2_DW.is_c1_Project_2) {
case Project_2_IN_OFF_MODE:
Project_2_Y.Acceleration_Mode = 0.0;
if (CruiseSwitch && (!SetSwitch)) {
Project_2_DW.is_c1_Project_2 = Project_2_IN_STANDBY_MODE;
Project_2_Y.Acceleration_Mode = 1.0;
}
break;
case Project_2_IN_ON_MODE:
if (!CruiseSwitch) {
Project_2_DW.is_ON_MODE = Project_2_IN_NO_ACTIVE_CHILD;
Project_2_DW.is_c1_Project_2 = Project_2_IN_OFF_MODE;
Project_2_Y.Acceleration_Mode = 0.0;
} else if (!SetSwitch) {
Project_2_DW.is_ON_MODE = Project_2_IN_NO_ACTIVE_CHILD;
Project_2_DW.is_c1_Project_2 = Project_2_IN_STANDBY_MODE;
Project_2_Y.Acceleration_Mode = 1.0;
} else {
switch (Project_2_DW.is_ON_MODE) {
case IN_LeadVehicle_Detected_Follow:
Project_2_Y.Acceleration_Mode = 2.0;
if (LeadVehicle_Detected == 0) {
Project_2_DW.is_ON_MODE = Pro_IN_LeadVehicle_Not_Detected;
Project_2_Y.Acceleration_Mode = 1.0;
} else if (((LeadVehicle_Detected == 1) && (LeadVehicle_Speed <
Set_Speed)) || (Time_Gap < Set_Gap)) {
Project_2_DW.is_ON_MODE = IN_LeadVehicle_Speed_lessthan_S;
Project_2_Y.Acceleration_Mode = 4.0;
}
break;
case IN_LeadVehicle_Detected_Resume:
Project_2_Y.Acceleration_Mode = 3.0;
if ((DriveVehicle_Speed == Set_Speed) && (LeadVehicle_Speed >=
Set_Speed) && (Time_Gap >= Set_Gap)) {
Project_2_DW.is_ON_MODE = IN_LeadVehicle_Detected_Follow;
Project_2_Y.Acceleration_Mode = 2.0;
} else if (LeadVehicle_Detected == 0) {
Project_2_DW.is_ON_MODE = IN_LeadVehicle_Not_Detected_Res;
Project_2_Y.Acceleration_Mode = 1.0;
} else if ((DriveVehicle_Speed < Set_Speed) && (LeadVehicle_Speed >
DriveVehicle_Speed) && (Time_Gap >= Set_Gap)) {
Project_2_DW.is_ON_MODE = IN_LeadVehicle_Speed_equal_Set_;
Project_2_Y.Acceleration_Mode = 5.0;
}
break;
case Pro_IN_LeadVehicle_Not_Detected:
Project_2_Y.Acceleration_Mode = 1.0;
if ((LeadVehicle_Detected == 1) && (DriveVehicle_Speed == Set_Speed) &&
(LeadVehicle_Speed >= Set_Speed) && (Time_Gap >= Set_Gap)) {
Project_2_DW.is_ON_MODE = IN_LeadVehicle_Detected_Follow;
Project_2_Y.Acceleration_Mode = 2.0;
} else if (((LeadVehicle_Detected == 1) && (LeadVehicle_Speed <
Set_Speed)) || (Time_Gap < Set_Gap)) {
Project_2_DW.is_ON_MODE = IN_LeadVehicle_Speed_lessthan_S;
Project_2_Y.Acceleration_Mode = 4.0;
}
break;
case IN_LeadVehicle_Not_Detected_Res:
Project_2_Y.Acceleration_Mode = 1.0;
break;
case IN_LeadVehicle_Speed_equal_Set_:
Project_2_Y.Acceleration_Mode = 5.0;
if ((LeadVehicle_Detected == 0) || (DriveVehicle_Speed <= Set_Speed))
{
Project_2_DW.is_ON_MODE = IN_LeadVehicle_Not_Detected_Res;
Project_2_Y.Acceleration_Mode = 1.0;
} else if (((DriveVehicle_Speed < Set_Speed) && (LeadVehicle_Speed >
DriveVehicle_Speed)) || (Time_Gap >= Set_Gap)) {
Project_2_DW.is_ON_MODE = IN_LeadVehicle_Detected_Resume;
Project_2_Y.Acceleration_Mode = 3.0;
} else if (((LeadVehicle_Speed < Set_Speed) && (LeadVehicle_Speed <
DriveVehicle_Speed)) || (0.75 * (real_T)Set_Gap ==
Time_Gap)) {
Project_2_DW.is_ON_MODE = IN_LeadVehicle_Speed_lessthan_S;
Project_2_Y.Acceleration_Mode = 4.0;
}
break;
default:
/* case IN_LeadVehicle_Speed_lessthan_Set_Speed: */
Project_2_Y.Acceleration_Mode = 4.0;
if ((LeadVehicle_Detected == 0) && (DriveVehicle_Speed == Set_Speed))
{
Project_2_DW.is_ON_MODE = Pro_IN_LeadVehicle_Not_Detected;
Project_2_Y.Acceleration_Mode = 1.0;
} else if (((real_T)LeadVehicle_Speed * 1.25 >= DriveVehicle_Speed) &&
((real_T)LeadVehicle_Speed * 0.75 <= DriveVehicle_Speed) &&
(DriveVehicle_Speed < Set_Speed) && (Time_Gap <= 1.25 *
(real_T)Set_Gap) && (Time_Gap >= 0.75 * (real_T)Set_Gap))
{
Project_2_DW.is_ON_MODE = IN_LeadVehicle_Speed_equal_Set_;
Project_2_Y.Acceleration_Mode = 5.0;
}
break;
}
}
break;
default:
/* case IN_STANDBY_MODE: */
Project_2_Y.Acceleration_Mode = 1.0;
if (!CruiseSwitch) {
Project_2_DW.is_c1_Project_2 = Project_2_IN_OFF_MODE;
Project_2_Y.Acceleration_Mode = 0.0;
} else if (CruiseSwitch && SetSwitch) {
Project_2_DW.is_c1_Project_2 = Project_2_IN_ON_MODE;
Project_2_DW.is_ON_MODE = IN_LeadVehicle_Detected_Follow;
Project_2_Y.Acceleration_Mode = 2.0;
}
break;
}
}
/* End of Chart: '/ACC_Algorithm' */
}
/* Model initialize function */
void Project_2_initialize(void)
{
/* Registration code */
/* initialize non-finites */
rt_InitInfAndNaN(sizeof(real_T));
}
/* Model terminate function */
void Project_2_terminate(void)
{
/* (no terminate code required) */
}
/*
* File trailer for generated code.
*
* [EOF]
*/
Results: Upon completion of the project, the developed ACC system will automate speed control and maintain a safe distance from the preceding vehicle. The system will enhance driver comfort by reducing the need for constant speed adjustments and allowing the driver to concentrate more on the road. The ACC algorithm will be implemented as a state machine in MATLAB Simulink, ensuring smooth transitions between different modes based on input signals. The final result will be a functional ACC system that can be integrated into passenger cars to improve driving experience and road safety.