Project 2 Adaptive Cruise Control

Main Project Adaptive Cruise Control

Objective of Main Project:

1. To Develop a Adaptive Cruise Control feature as per the Requirement Document using MATLAB Simulink.
2. Follow all the MBD related processes: Requirement Tagging & Traceability, SLDD creation, Configuration Parameter changes, Model Advisor check & Code Generation.
3. In Configuration Parameters: enable “Support Floating Numbers” under Code Generation settings.
4. Using the Embedded Coder, We need to generate the code.
5. 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.
6. Choose sample time for all signals as 0.01s
7. Adaptive Cruise Control is a comfort and convenience system, brake interventions and vehicle acceleration only take place within defined limits.

Description About Adaptive cruise control :

• 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.
• 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

Resolve and Prapogate all the signals :

• The mandatory steps here is to follow is we need to resolve the input signal of the topmost sub-system, and also we need to resolve the output signal where the 1st output is displayed for example here we will Resolve the ouput in Stateflow (Accleration_Mode), the purpose of resolving is, we defined our paramter of the signal inputs and outputs through SLDD, by resolving process we can linked or propagate the datatypes and all others signal paramaters and calibration values to the inputs and output signals to the total system, if we missed to do resolving and propagate the signal MAB-Model advisor will arises, also simulation might be get failure
• By the resolving signal and const it associated with the properties(Datatype) of the signal which defined in sldd its linked with parameters.

after that its called propagation, when we again labelled its or again used in the model.

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.

4. ADD block:

Add or subtract inputs. Specify one of the following:

• a) character vector containing + or - for each input port, | for spacer between ports (e.g. ++|-|++)
• b) scalar, >= 1, specifies the number of input ports to be summed.
• When there is only one input port, add or subtract elements over all dimensions or one specified dimension

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.

Signal Conversion:

Convert a signal to a new type without altering signal values.

1. a) If the incoming signal is not a bus, the 'Signal copy' option creates a contiguous segment of memory to store a copy of an input signal.

If the incoming signal is a bus, the 'Signal copy' option outputs a copy of the incoming bus.

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)]

Adaptive_Cruise _Control_Model :

. Unit Delay:

Sample and hold with one sample period delay.

REQUIREMENT TAGGING AND TRACEABILITY :

• Requirement Tagging is also one of the Objective of the project. We can do the Requirement Tagging by selecting the heading of our requirement in the Word File and then Link the Selection in Word from Requirement section of subsystem.
  
• After clicking on the Requirement tagged, the Requirement document opens up and the Subsystem is highlighted. step by step screenshots were attached for better understanding.

Select the subsystem and right click select requirement tagging.

Simulink data dictionary :

Sldd file has been created

A data dictionary is a persistent repository of data that are relevant to your model.

we can also use the base workspace to store design data that are used by your model during simulation.

However, a data dictionary provides more capabilities.

The dictionary stores design data, which define parameters and signals, and include data that define the behavior of the model.

The dictionary does not store simulation data, which are inputs or outputs of model simulation that enter and exit Inport and Outport blocks.

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	-	-

Model Advisor :

Model advisor as a tool is available in in core Simulink blockset that automatically enables the user to check for common modelling mistakes which we missed out to notice during model development

The Model Advisor can analyze the model throughly or a sub set of model upon selecting model advisor option as below, developer can choose which version we would like to test.

Run the model for follow the MAAB Guidelines by Model Advisor.

• To verify the configuration parameters for your model, you can create a configuration parameter check.
• Custom checks provide you with the ability to specify which conditions and configuration settings the Model Advisor reviews and at which stage during model development the Model Advisor reviews them.
• you can create custom checks that automatically run while you edit the model and interactively run in the Model Advisor.

given below images shows the menu of model advisor .

• i have selected by task under the MAB guidelines.
• run the MAB guidelines and generate the reports
• reports contains fail, pass, not run, warning condition and help to understand the model error with model recommendations.
• generated report also attached with this file.

Configuration Parameter changes : Solver Settings and code generation parameter settings need to be changed by shown following steps

Solver settings :

C Code Generation : Code Generation process will be executed by following steps.

We have already done the settings required in the Configuration Settings shown below. Now, we simply have to go to Apps section and click on Embedded Coder.

Further, we click on Generate Code and we can a window pop-up with our Code. Simulink will create .c and .h files in our model folder, which means our code is successfully generated.

Generate C code : By selecting the following steps we can generate the easily > APPS > embedded coder > Generate code

.C code was saved we can find screenshot attachment of .C code to Adaptive_cruise_control_project accordingly.

Top-Most_Subsystem of Adaptive_Cruise_Control :

Step by step proccess followed to Accomplish this project :

Step 1 : Read the requirement and Develop the model as per project Requirement, continued to that Project Requirement word document was tagged to the subsystem for better traceability

Step 2 : Read the Given Signal and Calibration data list and then Simulink data dictionary (SLDD) was created properly also File saved

Step 3 : Using the model advisor MAB Guidelines were checked for developed Model. MAB report was taken screenshots were attached

Step 4 : Solver settings done per the requirements : Sample time for all signals as 0.01s was chosen

and C Code generation settings was done using the Configuration parameters all screenshots were attached

Step 5 : Embedded Code generation done and report was taken file then was attached.

Result :

• Developed a Adaptive Cruise Control feature as per the Requirement Document using MATLAB Simulink.
• Followed 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.
• Using the Embedded Coder, I generated the .C code.
• For the 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. was given for code generation,
• For all the singnals the sample time 0.01s changed