Challenge

Project 2 Adaptive Cruise Control

SShubham Dipak Belokar5 Jul 2022

Project 2 Adaptive Cruise Control (ACC).

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 a 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, the 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 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 & 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.

The objective of the 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

Requirement 1– Lead Vehicle:

A lead vehicle is a vehicle that 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 cameras & 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 that has ACC algorithm in it.
Like the Lead Vehicle, the Driver 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 the 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, the 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) that 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 the 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 the 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 substate inside the 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)>

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	-	-

Procedure:

As per the Requirement document, implemented the Adaptive Cruise Control feature.

Lead vehicle

To detect the lead vehicle speed, simply added both the radar & camera inputs & the corresponding output is read as Speed profile output.

Drive Vehicle

To regulate the "Drive Vehicle speed, as per the Requirement Document added Cameralnput. Radarinput & Acceleration Mode feedback from ACC Algorithm.

To detect the Lead vehicle. Radarinput is converted using "Signal Conversion Block

• To avoid the algebraic error "Unit delay block is used for the Acceleration Mode feedback

ACC 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 the 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, the output signal (Signal Name LeadVehicle Speed) from requirement-1 is given as an input signal to this state machine
Output from this subsystem a signal (Signal Name Acceleration Model which governs the vehicular speed of the drive vehicle which automatically adjust to speed & velocity to match the lead vehicle.
The rest of the signal developed as per the Requirement.

DEVELOPMENT OF MATLAB MODEL

This is the main model subsystem that having 9 inputs CameraInput_LeadVehicle, RadarInput_LeadVehicle, CameraInput_DriveVehicle, RadarInput_DriveVehi, Time_Gap, Set_Speed, Set_Gap, CruiseSwitch and SetSwitch entering into the Adaptive Cruise Control subsystem and 4 outputs Acceleration_Mode, LeadVehicle_Speed, DriveVehicle_Speed, LeadVehicle_Detected

There are 3 requirements are designed in 2 subsystems and one state machine flow chart

Requirement Tagging

all the requirements are tagged for better understandability, anyone who is reviewing the model or who is trying to update the model can get a clear idea of what logic is used in the system. from the requirement manager, we can see what are all are tagged and the description.

go to the APP section -> then after manager requirement -> then it show the window appear below with requirement details and property inspector.

Developing SLDD

All the inputs, outputs, calibration parameters are saved in SLDD, and also propogated and resolve the signal from SLDD so while simulation the model takes all the values and its parameters from the Simulink Data Dictionary.

Signal Resolution for inputs and outputs

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 unwanted 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.