Project 2 Adaptive Cruise Control

ADAPTIVE CRUISE CONTROL

AIM:

To create an Adaptive Cruise Control system and meet the Requirements using MATLAB and Simulink.

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 a 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 speed 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 speed 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 intervention and vehicle acceleration only take place within defined limits. Even with Adoptive 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:

1. Developing Adaptive Cruise Control feature as per the Requirement Document using MATLAB Simulink.
2. Following all the MBA related processes: Requirement Tagging & Traceability, SLDD creations, Configuration parameter changes, Model Advisor check & code Generation.
3. In Configuration Parameters: enable “Support Floating Numbers” under Code Generation settings.
4. If choosing code generation, Storage class for Input signals: Imported Extern; Storage class for output signals: localizable; Storage class for calibration signals:
5. Choose sample time for all signals as 0.01s

STEPS CARRIED THROUGHOUT THE MODELLING:

STEP 1: CREATION OF SLDD

• Initially we will be loading the signals and calibration data list into a data dictionary.
• Click on the modelling options available in the file menu > select the drop down next to model properties > select link to data dictionary.
• Select new and type the name as per our choice.
• We can see the new data dictionary displayed in the down left corner of out simulink workspace.
• Click on that > click on the saved sldd > select design data > and upload manually all data given in the objectives.

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	-	-

STEP 2 : SOLVER CONFIGURATION

• Click on the modelling option available in the file menu > selected the drop down box bellow the model properties > open solver settings.
• Select solver type as fixed solver type > solver as discrete.

STEP 3 : SIMULINK MODEL

• Create three subsystems and tag as lead_vehicle, Drive_vehicle and Adaptive_Cruise_Contol.
• Model as per the instructions given in the objectives.
• Run time as 0.01s

MATLAB SIMULINK MODEL:

• The simulink model is the representative of the Adaptive Cruise control system.
• In this model there are two vehicles viz Lead vehicle and drive vehicle.
• These two vehicles uses the camera and Radar for functioning.
• The camera captures and read the signs in the road while the radar monitors the road and enables a interval between lead and drive vehicle.

ADAPTIVE CRUISE CONTROL SYSTEM:

• The Adaptive Cruise Control system consists of three subsystems i.e. Lead vehicles, Drive vehicle and the Adaptive Cruise Control.
• Each and every systems are modelled as per the instruction given in the objectives.
• Every system has its unique inputs which is called from the Data Dictionary.
• Signals given to each subsystem is also named by Right Click on signal>select signal properties>and select Resolve/Progogate as per application.
• This feature is closed loop system to avoid algebraic loop we are using a unit delay.

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.
• A unit delay is attached to the output to control the algebraic loop.

STATEFLOW:

REQUIREMENT 3a – ACC OFF MODE STAGE LOGIC:

• This is the default state inside state machine logic. Output signal Acceleration_Model is at value 0 in this state.
• This state is governed by input signal
• In 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 mood 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 (1) – 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 (2) – 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 (3) – 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 (4) – LEADVEHICLE_NOT_DETECTED_RESUME (ACC ON MOOD):

• Output signal Acceleration_Mode is equal to 1.

REQUIRMENT 3c (5) – 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 (6) – 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 toLeadVehicle_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 toLeadVehicle_Speed_lessthan_Set_Speed; Input signals conditions [(LeadVehicle_Speed
• Basically, we can understand that the adaptive cruise control feature enables a distance between the lead car and drive car which is also a good choice for safety.

RESULT:

• Now its time for simulating, as per the objective the sample time for the simulation is 0.01s.
• We have given an userdefined inputs for all the inputs as 1.
• The output is displayed using a display block and we can see the output as 1.
• This means that the system allows the drive vehicle to accelerate and result as the lead Vehicle and Drive vehicle are not in a closed interval.
• If the Lead Vehicle and Drive Vehicle are in closed interval or the distance which is not recommended then there will be no cruising so the output is will be 0.

STEP 4: ADVISOR CHECK:

• Click on the modelling option available in the file menu > select the advisor check available > system selector >

Vehicle_Direction_Detector > OK > click the by task box > click the show report after run > Generate report

• For detailed report please click Model Advisor Check for ACC.

RESULT:

Thus, the Developing Adaptive Cruise Control feature as per the Requirement Document using MATLAB Simulink is completed successfully and the MBD related processes: Requirement Tagging & Traceability, SLDD creation, configuration parameter changes, Model Advisor check & Code Generation are also followed successfully and the output is verified.