Project 2 Adaptive Cruise Control
MAIN PROJECT
ADAPTIVE CRUISE CONTROL
Objective of Main Project:
- Developing Adaptive Cruise Control feature as per the Requirement Document using MATLAB Simulink.
- Follow all the MBD related processes: Requirement Tagging & Traceability, SLDD creation, Configuration Parameter changes, Model Advisor check & Code Generation.
- In Configuration Parameters: enable “Support Floating Numbers” under Code Generation settings.
- Use Embedded Coder to generate the code.
- 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.
- Choose sample time for all signals as 0.01s
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.
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
The solution for requirement 3c(i)-(vi) can be seen below in the stateflow logic that was made for this model.
After creating these subsystems models, we can now connect them to get the complete model for Adaptive Cruise Control.
Tagging & Traceability
Once the model is complete, we can begin by tagging the information provided to us to build the model for the specific subsystems and flowcharts. We right click on the subsystem go to requirements and tag the model by the desired text copied from a Microsoft Word file. After tagging the text we can go to the Requirements editor to check whether it has been done or not. The model once tagged will light up with a gold colour.
Traceability is done when you select all parameters, you get a complete mapping between model elements and the generated code. Someone reading the model will get a better understanding of how its functioning. The traceability report has been attached with the answer.
SLDD Creation
We can create a new data dictionary containing all the given signals input and output data in a sldd file. Given below are all the signals that have been provided to us.
Configuration Parameter Update
Model Advisor Report
First, we click on run selected checks to check for any error in our model. After checking it will show it there are any faults or warning while running the model. Once the checks are completed, we can then generate a Model Advisor Report. The report has been attached with the other files for submissions.
CODE GENERATION
We go to the Apps menu from the main Options selections and go to C-Code and select generate code. We can see form the image below the C-code generated for our model.
C-CODE for the ADAPTIVE CRUISE CONTROL MODEL
/*
* File: AdaptiveCruiseControl.c
*
* Code generated for Simulink model 'AdaptiveCruiseControl'.
*
* Model version : 1.9
* Simulink Coder version : 9.5 (R2021a) 14-Nov-2020
* C/C++ source code generated on : Mon Jan 17 01:29:35 2022
*
* Target selection: ert.tlc
* Embedded hardware selection: Intel->x86-64 (Windows64)
* Code generation objectives:
* 1. Execution efficiency
* 2. RAM efficiency
* Validation result: Not run
*/
#include "AdaptiveCruiseControl.h"
/* Named constants for Chart: '<S2>/Chart' */
#define IN_ACC_OFF_MODE ((uint8_T)1U)
#define IN_ACC_ON_MODE ((uint8_T)2U)
#define IN_ACC_STANDBY_MODE ((uint8_T)3U)
#define IN_LeadVehicle_Detected_Follow ((uint8_T)1U)
#define IN_LeadVehicle_Detected_Resume ((uint8_T)2U)
#define IN_LeadVehicle_Not_Detected ((uint8_T)3U)
#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 signals and states (default storage) */
DW rtDW;
/* Real-time model */
static RT_MODEL rtM_;
RT_MODEL *const rtM = &rtM_;
extern real_T rt_roundd(real_T u);
real_T rt_roundd(real_T u)
{
real_T y;
if (fabs(u) < 4.503599627370496E+15) {
if (u >= 0.5) {
y = floor(u + 0.5);
} else if (u > -0.5) {
y = 0.0;
} else {
y = ceil(u - 0.5);
}
} else {
y = u;
}
return y;
}
/* Model step function */
void AdaptiveCruiseControl_step(void)
{
int32_T tmp;
int32_T tmp_0;
uint8_T tmp_1;
uint8_T tmp_2;
boolean_T guard1 = false;
/* Sum: '<S4>/Add' incorporates:
* Inport: '<Root>/CameraInput_LeadVehicle '
* Inport: '<Root>/RadarInput_LeadVehicle'
*/
LeadVehicle_Speed = (uint8_T)((uint32_T)CameraInput_LeadVehicle +
RadarInput_LeadVehicle);
/* SignalConversion: '<S3>/Signal Conversion' incorporates:
* Inport: '<Root>/RadarInput_DriveVehicle'
*/
LeadVehicle_Detected = RadarInput_DriveVehicle;
/* Sum: '<S3>/Add' incorporates:
* Inport: '<Root>/CameraInput_DriveVehicle'
* UnitDelay: '<S1>/Unit Delay'
*/
DriveVehicle_Speed = (uint8_T)((uint32_T)(uint8_T)((uint32_T)
CameraInput_DriveVehicle + Acceleration_Mode) + LeadVehicle_Detected);
/* Chart: '<S2>/Chart' incorporates:
* Inport: '<Root>/CruiseSwitch'
* Inport: '<Root>/Set_Gap'
* Inport: '<Root>/Set_Speed'
* Inport: '<Root>/Time_Gap'
*/
if (rtDW.bitsForTID0.is_active_c3_AdaptiveCruiseCont == 0U) {
rtDW.bitsForTID0.is_active_c3_AdaptiveCruiseCont = 1U;
rtDW.bitsForTID0.is_c3_AdaptiveCruiseControl = IN_ACC_OFF_MODE;
Acceleration_Mode = 0U;
} else {
guard1 = false;
switch (rtDW.bitsForTID0.is_c3_AdaptiveCruiseControl) {
case IN_ACC_OFF_MODE:
Acceleration_Mode = 0U;
if (CruiseSwitch) {
rtDW.bitsForTID0.is_c3_AdaptiveCruiseControl = IN_ACC_STANDBY_MODE;
Acceleration_Mode = 1U;
}
break;
case IN_ACC_ON_MODE:
switch (rtDW.bitsForTID0.is_ACC_ON_MODE) {
case IN_LeadVehicle_Detected_Follow:
Acceleration_Mode = 2U;
if (LeadVehicle_Detected == 0) {
rtDW.bitsForTID0.is_ACC_ON_MODE = IN_LeadVehicle_Not_Detected;
Acceleration_Mode = 1U;
} else if (((LeadVehicle_Detected == 1) && (LeadVehicle_Speed <
Set_Speed)) || (Time_Gap < Set_Gap)) {
rtDW.bitsForTID0.is_ACC_ON_MODE = IN_LeadVehicle_Speed_lessthan_S;
Acceleration_Mode = 4U;
}
break;
case IN_LeadVehicle_Detected_Resume:
Acceleration_Mode = 3U;
if ((DriveVehicle_Speed < Set_Speed) && (LeadVehicle_Speed >
DriveVehicle_Speed) && (Time_Gap >= Set_Gap)) {
rtDW.bitsForTID0.is_ACC_ON_MODE = IN_LeadVehicle_Speed_equal_Set_;
Acceleration_Mode = 5U;
} else if (LeadVehicle_Detected == 0) {
rtDW.bitsForTID0.is_ACC_ON_MODE = IN_LeadVehicle_Not_Detected_Res;
Acceleration_Mode = 1U;
}
break;
case IN_LeadVehicle_Not_Detected:
Acceleration_Mode = 1U;
if ((LeadVehicle_Detected == 1) && (DriveVehicle_Speed == Set_Speed) &&
(LeadVehicle_Speed >= Set_Speed) && (Time_Gap >= Set_Gap)) {
rtDW.bitsForTID0.is_ACC_ON_MODE = IN_LeadVehicle_Detected_Follow;
Acceleration_Mode = 2U;
} else if (((LeadVehicle_Detected == 1) && (LeadVehicle_Speed <
Set_Speed)) || (Time_Gap < Set_Gap)) {
rtDW.bitsForTID0.is_ACC_ON_MODE = IN_LeadVehicle_Speed_lessthan_S;
Acceleration_Mode = 4U;
}
break;
case IN_LeadVehicle_Not_Detected_Res:
Acceleration_Mode = 1U;
if ((DriveVehicle_Speed == Set_Speed) && (LeadVehicle_Speed >= Set_Speed)
&& (Time_Gap >= Set_Gap)) {
rtDW.bitsForTID0.is_ACC_ON_MODE = IN_LeadVehicle_Detected_Follow;
Acceleration_Mode = 2U;
}
break;
case IN_LeadVehicle_Speed_equal_Set_:
Acceleration_Mode = 5U;
if (((LeadVehicle_Speed < Set_Speed) && (LeadVehicle_Speed <
DriveVehicle_Speed)) || ((int32_T)rt_roundd(0.75 * (real_T)Set_Gap)
== Time_Gap)) {
rtDW.bitsForTID0.is_ACC_ON_MODE = IN_LeadVehicle_Speed_lessthan_S;
Acceleration_Mode = 4U;
} else if ((DriveVehicle_Speed < Set_Speed) && (LeadVehicle_Speed >
DriveVehicle_Speed) && (Time_Gap >= Set_Gap)) {
rtDW.bitsForTID0.is_ACC_ON_MODE = IN_LeadVehicle_Detected_Resume;
Acceleration_Mode = 3U;
} else if ((LeadVehicle_Detected == 0) && (DriveVehicle_Speed <=
Set_Speed)) {
rtDW.bitsForTID0.is_ACC_ON_MODE = IN_LeadVehicle_Not_Detected_Res;
Acceleration_Mode = 1U;
}
break;
default:
/* case IN_LeadVehicle_Speed_lessthan_Set_Speed: */
Acceleration_Mode = 4U;
if ((LeadVehicle_Detected == 0) && (DriveVehicle_Speed == Set_Speed)) {
rtDW.bitsForTID0.is_ACC_ON_MODE = IN_LeadVehicle_Not_Detected;
Acceleration_Mode = 1U;
} else {
tmp = (int32_T)rt_roundd((real_T)LeadVehicle_Speed * 1.25);
tmp_0 = (int32_T)rt_roundd(1.25 * (real_T)Set_Gap);
if (tmp < 256) {
tmp_1 = (uint8_T)tmp;
} else {
tmp_1 = MAX_uint8_T;
}
if (tmp_0 < 256) {
tmp_2 = (uint8_T)tmp_0;
} else {
tmp_2 = MAX_uint8_T;
}
if ((tmp_1 >= DriveVehicle_Speed) && ((int32_T)rt_roundd((real_T)
LeadVehicle_Speed * 0.75) <= DriveVehicle_Speed) &&
(DriveVehicle_Speed < Set_Speed) && (Time_Gap <= tmp_2) &&
(Time_Gap >= (int32_T)rt_roundd(0.75 * (real_T)Set_Gap))) {
rtDW.bitsForTID0.is_ACC_ON_MODE = IN_LeadVehicle_Speed_equal_Set_;
Acceleration_Mode = 5U;
}
}
break;
}
break;
default:
/* case IN_ACC_STANDBY_MODE: */
Acceleration_Mode = 1U;
if (!SetSwitch) {
guard1 = true;
} else if (!CruiseSwitch) {
rtDW.bitsForTID0.is_c3_AdaptiveCruiseControl = IN_ACC_OFF_MODE;
Acceleration_Mode = 0U;
} else if (SetSwitch) {
guard1 = true;
}
break;
}
if (guard1) {
rtDW.bitsForTID0.is_c3_AdaptiveCruiseControl = IN_ACC_ON_MODE;
rtDW.bitsForTID0.is_ACC_ON_MODE = IN_LeadVehicle_Detected_Follow;
Acceleration_Mode = 2U;
}
}
/* End of Chart: '<S2>/Chart' */
}
/* Model initialize function */
void AdaptiveCruiseControl_initialize(void)
{
/* (no initialization code required) */
}
/*
* File trailer for generated code.
*
* [EOF]
*/
CONCLUSION
The Adaptive Cruise Control model has successfully been built using Simulink and have also completed the Requirement Tagging & Traceability, SLDD creation, Configuration Parameter updates, Model Advisor check & Code Generation. The screenshots of each case have been given in the report and separate files for each operation have been attached in the submission files.