Project 2 Adaptive Cruise Control
AIM: Main Project – Adaptive Cruise Control (ACC)
INTRO
The Adaptive Cruise Control System block simulates an adaptive cruise control (ACC) system that tracks a set velocity and maintains a safe distance from a lead vehicle by adjusting the longitudinal acceleration of an ego vehicle. The block computes optimal control actions while satisfying safe distance, velocity, and acceleration constraints using model predictive control (MPC).
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.
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
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Signals & Calibration Data List:
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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 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 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<set_speed) &&="" (leadvehicle_speed<drivevehicle_speed)="" ||="" (time_gap="=" 0.75*set_gap)]<="" em=""></set_speed)>
The Model Advisor checks your model or subsystem for modeling conditions and configuration settings that cause inaccurate or inefficient simulation of the system that the model represents. The Model Advisor checks can help you verify compliance with industry standards and guidelines. By using the Model Advisor, you can implement consistent modeling guidelines across projects and development teams.
Upon completing the analysis of your model, the Model Advisor produces a report that lists the suboptimal conditions, settings, and modeling techniques and proposes solutions, when applicable.
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/*
* File: ADAS.c
*
* Code generated for Simulink model 'ADAS'.
* Model version : 1.1
* Simulink Coder version : 9.6 (R2021b) 14-May-2021
* C/C++ source code generated on : Sun Jun 26 18:50:29 2022
*
* Target selection: ert.tlc
* Embedded hardware selection: Intel->x86-64 (Mac OS X)
* Code generation objectives: Unspecified
* Validation result: Not run
*/
#include "ADAS.h"
#include "ADAS_private.h"
/* Named constants for Chart: '/Chart1' */
#define ADAS_IN_NO_ACTIVE_CHILD ((uint8_T)0U
#define ADAS_IN_OFF_MODE ((uint8_T)1U)
#define ADAS_IN_ON_MODE ((uint8_T)2U)
#define ADAS_IN_STANDBY_MODE ((uint8_T)3U)
#define ADA_IN_LeadVehicle_Not_Detected ((uint8_T)3U)
#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 signals (default storage) */
B_ADAS_T ADAS_B;
/* Block states (default storage) */
DW_ADAS_T ADAS_DW;
/* External inputs (root inport signals with default storage) */
ExtU_ADAS_T ADAS_U;
/* External outputs (root outports fed by signals with default storage) */
ExtY_ADAS_T ADAS_Y;
/* Real-time model */
static RT_MODEL_ADAS_T ADAS_M_;
RT_MODEL_ADAS_T *const ADAS_M = &ADAS_M_;
/* Model step function */
void ADAS_step(void)
{
real_T rtb_DriveVehicle_Spee
real_T rtb_LeadVehicle_Speed;
/* Sum: '/Add' incorporates:
* Inport: '/CameraInput_LeadVehicle'
* Inport: '/RadarInput_LeadVehicle'
*/
rtb_LeadVehicle_Speed = ADAS_U.CameraInput_LeadVehicle +
ADAS_U.RadarInput_LeadVehicle;
/* Sum: '/Add' incorporates:
* Inport: '/Acceleration_Mode'
* Inport: '/CameraInput_DriveVehicle'
* Inport: '/RadarInput_Drive Vehicle'
*/
rtb_DriveVehicle_Speed = (ADAS_U.CameraInput_DriveVehicle +
ADAS_U.RadarInput_DriveVehicle) + ADAS_U.Acceleration_Mode;
/* Chart: '/Chart1' incorporates:
* Inport: '/Cruise Switch'
* Inport: '/RadarInput_Drive Vehicle'
* Inport: '/Set Gap'
* Inport: '/Set Switch'
* Inport: '/Set_Speed'
* Inport: '/Time_Gap'
*/
if (ADAS_DW.is_active_c2_ADAS == 0U) {
ADAS_DW.is_active_c2_ADAS = 1U;
ADAS_DW.is_c2_ADAS = ADAS_IN_OFF_MODE;
ADAS_B.Acceleration_Mode = 0.0
} else {
switch (ADAS_DW.is_c2_ADAS) {
case ADAS_IN_OFF_MODE:
if ((ADAS_U.CruiseSwitch == 1.0) && (ADAS_U.SetSwitch == 0.0)) {
ADAS_DW.is_c2_ADAS = ADAS_IN_STANDBY_MODE;
ADAS_B.Acceleration_Mode = 1.0;
}
break;
case ADAS_IN_ON_MODE:
if (ADAS_U.SetSwitch == 0.0) {
ADAS_DW.is_ON_MODE = ADAS_IN_NO_ACTIVE_CHILD;
ADAS_DW.is_c2_ADAS = ADAS_IN_STANDBY_MODE;
ADAS_B.Acceleration_Mode = 1.0;
} else if (ADAS_U.CruiseSwitch == 0.0) {
ADAS_DW.is_ON_MODE = ADAS_IN_NO_ACTIVE_CHILD;
ADAS_DW.is_c2_ADAS = ADAS_IN_OFF_MODE;
ADAS_B.Acceleration_Mode = 0.0;
} else {
switch (ADAS_DW.is_ON_MODE) {
case IN_LeadVehicle_Detected_Follow:
if (ADAS_U.RadarInput_DriveVehicle == 0.0) {
ADAS_DW.is_ON_MODE = ADA_IN_LeadVehicle_Not_Detected;
ADAS_B.Acceleration_Mode = 1.0;
} else if (((ADAS_U.RadarInput_DriveVehicle == 1.0) &&
(rtb_LeadVehicle_Speed < ADAS_U.Set_Speed)) ||
(ADAS_U.Time_Gap < ADAS_U.SetGap)) {
ADAS_DW.is_ON_MODE = IN_LeadVehicle_Speed_lessthan_S;
ADAS_B.Acceleration_Mode = 4.0;
} else {
ADAS_B.Acceleration_Mode = 2.0;
}
break;
case IN_LeadVehicle_Detected_Resume:
if ((rtb_DriveVehicle_Speed == ADAS_U.Set_Speed) &&
(rtb_LeadVehicle_Speed >= ADAS_U.Set_Speed) && (ADAS_U.Time_Gap >=
ADAS_U.SetGap)) {
ADAS_DW.is_ON_MODE = IN_LeadVehicle_Detected_Follow;
ADAS_B.Acceleration_Mode = 2.0;
} else if ((rtb_DriveVehicle_Speed < ADAS_U.Set_Speed) &&
(rtb_LeadVehicle_Speed > rtb_DriveVehicle_Speed) &&
(ADAS_U.Time_Gap >= ADAS_U.SetGap)) {
ADAS_DW.is_ON_MODE = IN_LeadVehicle_Speed_equal_Set_;
ADAS_B.Acceleration_Mode = 5.0;
} else if (ADAS_U.RadarInput_DriveVehicle == 0.0) {
ADAS_DW.is_ON_MODE = IN_LeadVehicle_Not_Detected_Res;
ADAS_B.Accelearation_Mode = 1.0;
} else {
ADAS_B.Acceleration_Mode = 3.0;
}
break;
case ADA_IN_LeadVehicle_Not_Detected:
if ((ADAS_U.RadarInput_DriveVehicle == 1.0) && (rtb_DriveVehicle_Speed
== ADAS_U.Set_Speed) && (rtb_LeadVehicle_Speed >=
ADAS_U.Set_Speed) && (ADAS_U.Time_Gap >= ADAS_U.SetGap)) {
ADAS_DW.is_ON_MODE = IN_LeadVehicle_Detected_Follow;
ADAS_B.Acceleration_Mode = 2.0;
} else if (((ADAS_U.RadarInput_DriveVehicle == 1.0) &&
(rtb_LeadVehicle_Speed < ADAS_U.Set_Speed)) ||
(ADAS_U.Time_Gap < ADAS_U.SetGap)) {
ADAS_DW.is_ON_MODE = IN_LeadVehicle_Speed_lessthan_S;
ADAS_B.Acceleration_Mode = 4.0;
} else {
ADAS_B.Acceleration_Mode = 1.0;
}
break;
case IN_LeadVehicle_Not_Detected_Res:
ADAS_B.Accelearation_Mode = 1.0;
break;
case IN_LeadVehicle_Speed_equal_Set_:
if ((ADAS_U.RadarInput_DriveVehicle == 0.0) || (rtb_DriveVehicle_Speed
<= ADAS_U.Set_Speed)) {
ADAS_DW.is_ON_MODE = IN_LeadVehicle_Not_Detected_Res;
ADAS_B.Accelearation_Mode = 1.0;
} else if (((rtb_DriveVehicle_Speed < ADAS_U.Set_Speed) &&
(rtb_LeadVehicle_Speed > rtb_DriveVehicle_Speed)) ||
(ADAS_U.Time_Gap >= ADAS_U.SetGap)) {
ADAS_DW.is_ON_MODE = IN_LeadVehicle_Detected_Resume;
ADAS_B.Acceleration_Mode = 3.0;
} else {
ADAS_B.Acceleration_Mode = 5.0;
}
break;
default:
/* case IN_LeadVehicle_Speed_lessthan_Set_Speed: */
if ((ADAS_U.RadarInput_DriveVehicle == 0.0) && (rtb_DriveVehicle_Speed
== ADAS_U.Set_Speed)) {
ADAS_DW.is_ON_MODE = ADA_IN_LeadVehicle_Not_Detected;
ADAS_B.Acceleration_Mode = 1.0;
} else if ((rtb_LeadVehicle_Speed * 1.25 >= rtb_DriveVehicle_Speed) &&
(rtb_LeadVehicle_Speed * 0.75 <= rtb_DriveVehicle_Speed) &&
(rtb_DriveVehicle_Speed < ADAS_U.Set_Speed) &&
(ADAS_U.Time_Gap <= 1.25 * ADAS_U.SetGap) &&
(ADAS_U.Time_Gap >= 0.75 * ADAS_U.SetGap)) {
ADAS_DW.is_ON_MODE = IN_LeadVehicle_Speed_equal_Set_;
ADAS_B.Acceleration_Mode = 5.0;
} else {
ADAS_B.Acceleration_Mode = 4.0;
}
break;
}
}
break;
default:
/* case IN_STANDBY_MODE: */
if (ADAS_U.CruiseSwitch == 0.0)
{
ADAS_DW.is_c2_ADAS = ADAS_IN_OFF_MODE;
ADAS_B.Acceleration_Mode = 0.0;
}
else if ((ADAS_U.CruiseSwitch == 1.0) && (ADAS_U.SetSwitch == 1.0))
{
ADAS_DW.is_c2_ADAS = ADAS_IN_ON_MODE;
ADAS_DW.is_ON_MODE = IN_LeadVehicle_Detected_Follow;
ADAS_B.Acceleration_Mode = 2.0;
}
break;
}
}
/* End of Chart: '/Chart1' */
/* Outport: '/Output' */
ADAS_Y.Acceleration_Mode[0] = ADAS_B.Acceleration_Mode;
ADAS_Y.Acceleration_Mode[1] = ADAS_B.Accelearation_Mode;
}
/* Model initialize function */
void ADAS_initialize(void)
{
/* (no initialization code required) */
}
/* Model terminate function */
void ADAS_terminate(void)
{
/* (no terminate code required) */
}
/*
* File trailer for generated code.
*
* [EOF]
*/
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RESULT:The ACC system decides which mode to use based on real-time radar measurements. For example, if the lead car is too close, the ACC system switches from speed control to spacing control. Similarly, if the lead car is further away, the ACC system switches from spacing control to speed control. In other words, the ACC system makes the ego car travel at a driver-set speed as long as it maintains a safe distance.