Project 2 Adaptive Cruise Control
Aim: To Develop a MATLAB Simulink Model for Adaptive Cruise Control Feature as per requirement and generate a C-Code for it.
Objective:
- 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
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.
Procedure for creating the MATLAB Simulink Model for Vehicle Direction Detection:
1. First In Matlab tool bar select Start Simulink button
2. After an dialouge box will open in that select create a Blank model
3. I saved my Blank model in the name of Adaptive_Cruise_Control.
4. Now before creating the simulink model we need to creat a simulink data dictionary for the given set of Signals & Calibration Data List.
|
Signal / Calibration Name |
Signal Type |
Data Type |
Dimension |
Min |
Max |
Initial Value |
Units |
|
CameraInput_LeadVehicle |
Input |
Uint8 |
1 |
0 |
255 |
- |
- |
|
RadarInput_LeadVehicle |
Input |
Uint8 |
1 |
0 |
255 |
- |
- |
|
CameraInput_DriveVehicle |
Input |
Uint8 |
1 |
0 |
255 |
- |
- |
|
RadarInput_DriveVehicle |
Input |
Uint8 |
1 |
0 |
255 |
- |
- |
|
Time_Gap |
Input |
Uint8 |
1 |
0 |
255 |
- |
- |
|
Set_Speed |
Input |
Uint8 |
1 |
0 |
255 |
- |
- |
|
Set_Gap |
Input |
Uint8 |
1 |
0 |
255 |
- |
- |
|
CruiseSwitch |
Input |
Boolean |
1 |
0 |
1 |
- |
- |
|
SetSwitch |
Input |
Boolean |
1 |
0 |
1 |
- |
- |
|
Acceleration_Mode |
Output |
Uint8 |
1 |
0 |
255 |
- |
- |
|
LeadVehicle_Speed |
Output |
Uint8 |
1 |
0 |
255 |
- |
- |
|
DriveVehicle_Speed |
Output |
Uint8 |
1 |
0 |
255 |
- |
- |
|
LeadVehicle_Detected |
Output |
Uint8 |
1 |
0 |
255 |
- |
- |
- Steps to create the Simulink Data Dictionary (SLDD) file:
- In the blank vehicle_direction_detection simulink model Goto Modeling tab -> Select model settings -> Model Properties.
- In Model Properties -> Select External Data.
- Under External data tab we can see a blank tab Data Dictionary in that type the sldd file in the name of Adaptive_cruise_control_dd and uncheck the Enable model access to base workspace check box.
- Finally press ok now simulink data dictionary is created with file name Adaptive_cruise_control_dd.sldd
- In the simulink model select the modeling tab -> select model explorer.
- Below picture shows how to add simulink signal and add simulink parameters.
- For the output signals we need to give name for header file and definition file, storage class as ExportToFile and sample time 0.01. Note keep always same name for all the constant parameters and output signals add in the data dictionary.
- All the input and output signal sample time is given as 0.01
- For input signals storage is selected as ImportedExtern.
5. After the successful creation of the data dictionary for this vehicle_direction_detection model. Now we can create the model for the given requirements.
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.
- Resolve the output signal LeadVehicle_Speed.
- To resolve the signals select the spectific signal and right click on it -> select properties.
- select the above created model and then create an subsystem.
- After selected the model in the right side end of the corner we can see the three dotes. Click on the dote and it will lead to creating subsystem. Rename the created subsystem as LeadVehicle.
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.
- Resolve the output signal DriveVehicle_Speed and LeadVehicle_Detected.
- To resolve the signals select the spectific signal and right click on it -> select properties.
- select the above created model and then create an subsystem.
- After selected the model in the right side end of the corner we can see the three dotes. Click on the dote and it will lead to creating subsystem. Rename the created subsystem as Drive vehicle.
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.
- Steps to create the Simulink State chart:
- In the created simulink file under simulation tab click on the library browser.
- A simulink library browser widow will open in that goto stateflow -> select Chart.
- Now the stateflow chart is created in the model file change the chart name to Adaptive cruise control logic.
- In simulink model select the modeling tab -> select model explorer.
- In model explorer window under Adaptive cruise control logic enter all the input and output signals of stateflow charte.
- select the above created model and then create an subsystem.
- After selected the model in the right side end of the corner we can see the three dotes. Click on the dote and it will lead to creating subsystem. Rename the created subsystem as Adaptive Cruise Algoritham.
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
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
Based on the all the above given requirement stateflow logic is created is shown below.
6. Tagging the requirements to the subsystems Lead vehicle, Drive vehicle & Adaptive Cruise Algoritham.
Tag the requirement to the Lead vehicle subsystem:
- For tag requirements in Lead vehicle subsystem first click on the subsystem and then right click on it -> Goto Requirements -> select 'Link to selection in work'.
- Meanwhile in word document highlight which of the thing need to tag.
- Similary tag the required documents to the remaining two subsystems Drive vehicle & Adaptive Cruise Algoritham.
7. Now a check is performed using Model Advisor tool in simulink to see whether the develped model meets the modeling standards for MAAB (MathWorks Automotive Advisory Board).
- After run the model advisor tool the Model sandards for MAB gives no any fail so the created model is satisfied the MAB guidelines
8. Finally generate the code for the created Adaptive_Cruise_Control model.
- For the select the whole Lead vehicle, Drive vehicle & Adaptive Cruise Algoritham subsystems and make it as a one subsystem and name it as Adaptive Cruise Control.
- Now before code generation we need to do some changes in the solver configuration and code generation settings for that in matlab under modeling tab -> select model setting. Then the model setting dialoug box will open now.
- In Configuration Parameters: enable “Support Floating Numbers” under Code Generation settings.
- To generate code select the substem named as vehicle direction detection and then In matlab on the simulink model file embedded coder tool box is availabele under APPS tab click on it.
- A new tab C CODE is open next to the APPS tab under that tab click athe Generate Code.
- After click on the generate code then the C Code is generated for the created model.
Code Generated for this model:
/*
* File: Adaptive_Cruise_Control.c
*
* Code generated for Simulink model 'Adaptive_Cruise_Control'.
*
* Model version : 1.10
* Simulink Coder version : 9.3 (R2020a) 18-Nov-2019
* C/C++ source code generated on : Mon Dec 6 12:11:01 2021
*
* Target selection: ert.tlc
* Embedded hardware selection: Intel->x86-64 (Windows64)
* Code generation objectives: Unspecified
* Validation result: Not run
*/
#include "Adaptive_Cruise_Control.h"
#include "Adaptive_Cruise_Control_private.h"
/* Named constants for Chart: '<S2>/Adaptive Cruise Contorl Logic' */
#define Ada_IN_LeadVehicle_Not_Detected ((uint8_T)3U)
#define Adaptive_Cr_IN_ACC_STANDBY_Mode ((uint8_T)3U)
#define Adaptive_Cru_IN_NO_ACTIVE_CHILD ((uint8_T)0U)
#define Adaptive_Cruise_IN_ACC_OFF_Mode ((uint8_T)1U)
#define Adaptive_Cruise__IN_ACC_On_Mode ((uint8_T)2U)
#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_Adaptive_Cruise_Control_T Adaptive_Cruise_Control_DW;
/* Real-time model */
RT_MODEL_Adaptive_Cruise_Cont_T Adaptive_Cruise_Control_M_;
RT_MODEL_Adaptive_Cruise_Cont_T *const Adaptive_Cruise_Control_M =
&Adaptive_Cruise_Control_M_;
/* Forward declaration for local functions */
static void Adaptive_Cruise_Con_ACC_On_Mode(uint8_T *Acceleration_Mode_f);
real_T rt_roundd_snf(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 = u * 0.0;
} else {
y = ceil(u - 0.5);
}
} else {
y = u;
}
return y;
}
/* Function for Chart: '<S2>/Adaptive Cruise Contorl Logic' */
static void Adaptive_Cruise_Con_ACC_On_Mode(uint8_T *Acceleration_Mode_f)
{
int32_T tmp;
int32_T tmp_0;
uint8_T tmp_1;
uint8_T tmp_2;
/* Inport: '<Root>/SetSwitch' incorporates:
* Inport: '<Root>/CruiseSwitch'
* Inport: '<Root>/Set_Gap'
* Inport: '<Root>/Set_Speed'
* Inport: '<Root>/Time_Gap'
*/
if (!SetSwitch) {
Adaptive_Cruise_Control_DW.is_ACC_On_Mode = Adaptive_Cru_IN_NO_ACTIVE_CHILD;
Adaptive_Cruise_Control_DW.is_c3_Adaptive_Cruise_Control =
Adaptive_Cr_IN_ACC_STANDBY_Mode;
*Acceleration_Mode_f = 1U;
} else if (!CruiseSwitch) {
Adaptive_Cruise_Control_DW.is_ACC_On_Mode = Adaptive_Cru_IN_NO_ACTIVE_CHILD;
Adaptive_Cruise_Control_DW.is_c3_Adaptive_Cruise_Control =
Adaptive_Cruise_IN_ACC_OFF_Mode;
*Acceleration_Mode_f = 0U;
} else {
switch (Adaptive_Cruise_Control_DW.is_ACC_On_Mode) {
case IN_LeadVehicle_Detected_Follow:
*Acceleration_Mode_f = 2U;
if (LeadVehicle_Detected == 0) {
Adaptive_Cruise_Control_DW.is_ACC_On_Mode =
Ada_IN_LeadVehicle_Not_Detected;
*Acceleration_Mode_f = 1U;
} else {
if (((LeadVehicle_Detected == 1) && (LeadVehicle_Speed < Set_Speed)) ||
(Time_Gap < Set_Gap)) {
Adaptive_Cruise_Control_DW.is_ACC_On_Mode =
IN_LeadVehicle_Speed_lessthan_S;
*Acceleration_Mode_f = 4U;
}
}
break;
case IN_LeadVehicle_Detected_Resume:
*Acceleration_Mode_f = 3U;
/* Inport: '<Root>/Set_Speed' incorporates:
* Inport: '<Root>/Set_Gap'
* Inport: '<Root>/Time_Gap'
*/
if ((DriveVehicle_Speed == Set_Speed) && (LeadVehicle_Speed >= Set_Speed) &&
(Time_Gap >= Set_Gap)) {
Adaptive_Cruise_Control_DW.is_ACC_On_Mode =
IN_LeadVehicle_Detected_Follow;
*Acceleration_Mode_f = 2U;
} else if (LeadVehicle_Detected == 0) {
Adaptive_Cruise_Control_DW.is_ACC_On_Mode =
IN_LeadVehicle_Not_Detected_Res;
*Acceleration_Mode_f = 1U;
} else {
if ((DriveVehicle_Speed < Set_Speed) && (LeadVehicle_Speed >
DriveVehicle_Speed) && (Time_Gap >= Set_Gap)) {
Adaptive_Cruise_Control_DW.is_ACC_On_Mode =
IN_LeadVehicle_Speed_equal_Set_;
*Acceleration_Mode_f = 5U;
}
}
break;
case Ada_IN_LeadVehicle_Not_Detected:
*Acceleration_Mode_f = 1U;
/* Inport: '<Root>/Set_Speed' incorporates:
* Inport: '<Root>/Set_Gap'
* Inport: '<Root>/Time_Gap'
*/
if ((LeadVehicle_Detected == 1) && (DriveVehicle_Speed == Set_Speed) &&
(LeadVehicle_Speed >= Set_Speed) && (Time_Gap >= Set_Gap)) {
Adaptive_Cruise_Control_DW.is_ACC_On_Mode =
IN_LeadVehicle_Detected_Follow;
*Acceleration_Mode_f = 2U;
} else {
if (((LeadVehicle_Detected == 1) && (LeadVehicle_Speed < Set_Speed)) ||
(Time_Gap < Set_Gap)) {
Adaptive_Cruise_Control_DW.is_ACC_On_Mode =
IN_LeadVehicle_Speed_lessthan_S;
*Acceleration_Mode_f = 4U;
}
}
break;
case IN_LeadVehicle_Not_Detected_Res:
*Acceleration_Mode_f = 1U;
break;
case IN_LeadVehicle_Speed_equal_Set_:
*Acceleration_Mode_f = 5U;
/* Inport: '<Root>/Set_Speed' incorporates:
* Inport: '<Root>/Set_Gap'
* Inport: '<Root>/Time_Gap'
*/
if (((LeadVehicle_Speed < Set_Speed) && (LeadVehicle_Speed <
DriveVehicle_Speed)) || ((int32_T)rt_roundd_snf(0.75 * (real_T)
Set_Gap) == Time_Gap)) {
Adaptive_Cruise_Control_DW.is_ACC_On_Mode =
IN_LeadVehicle_Speed_lessthan_S;
*Acceleration_Mode_f = 4U;
} else if ((LeadVehicle_Detected == 0) || (DriveVehicle_Speed <= Set_Speed))
{
Adaptive_Cruise_Control_DW.is_ACC_On_Mode =
IN_LeadVehicle_Not_Detected_Res;
*Acceleration_Mode_f = 1U;
} else {
if (((DriveVehicle_Speed < Set_Speed) && (LeadVehicle_Speed >
DriveVehicle_Speed)) || (Time_Gap >= Set_Gap)) {
Adaptive_Cruise_Control_DW.is_ACC_On_Mode =
IN_LeadVehicle_Detected_Resume;
*Acceleration_Mode_f = 3U;
}
}
break;
default:
/* case IN_LeadVehicle_Speed_lessthan_Set_Speed: */
*Acceleration_Mode_f = 4U;
/* Inport: '<Root>/Set_Speed' */
if ((LeadVehicle_Detected == 0) && (DriveVehicle_Speed == Set_Speed)) {
Adaptive_Cruise_Control_DW.is_ACC_On_Mode =
Ada_IN_LeadVehicle_Not_Detected;
Conclusion:
The MATLAB model for Adaptive Cruise Control is developed as per the given requirements, Tagged the requirements to their corresponding Lead vehicle,Drive vehicle & Adaptive Cruise Algoritham subsystems, Simulink Data Dictionary file has been created and the code is generated using Embedded Coder in Simulink.