Challenge

Project 2 Adaptive Cruise Control

A. Objective of Main Project:

  1. Developing 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. Use Embedded Coder 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.

B. Steps to Developing Adaptive Cruise Control feature:

To develop model I have used 2017a version of MATLAB.

1. Main Model:


The main model (ACC_Subsytem) consists of 3 subsystems of requirement 1,2 and 3 as LeadVehicle, DirveVehicle and AdaptiveCruisecontrolAlgo respectively follows:


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.

  • Here I have used add block and in/out port as shown in the above figure.
  • To get Lead vehicle's speed we have added Camera input and Radar input of Lead vehicle.

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.

  • Here I have used add, signal conversion block and in/out port as shown in the above figure.
  • To get Drive vehicle's speed we have added Camera input, Radar input and acceleration mode of drive vehicle.
  • The Radar input from drive vehicle is converted to generated LeadVehicle_Detected signal.

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 3 is developed by using state flow diagram as shown in the above figure.

  • Adaptive cruise Control has few sub requirement and the whole picture of requirement 3 including all sub requirements are shown in the above figure.

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.

  • Both Requirement 3a and 3b is implemented as shown in the above figure.

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 has few sub requirement as shown in the above figure.

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)]

  • Both Requirement 3c(i) and 3c(ii) is implemented as shown in the above figure.

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(iii) is implemented as shown in the above figure.

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

  • Both Requirement 3c(v) and 3c(vi) is implemented as shown in the above figure.

2. MBD related processes:

2.1 Requirement Tagging & Traceability

Created requirement documents in .docx format.

The requirement tagging is done for each subsystem and state as per the above requirements.

The requirement tagging is done as shown in the below figure.


2.2 SLDD creation

Created data dictionary for the signals parameters mentioned above.

The data dictionary is created and linked to the model using Model properties as shown in the figures below.


2.3 Configuration Parameter changes

Before executing model, set the below configurations as per the requirement below.

Set Slover configuration as below.


Set Code generation configuration as below.

2.4 Model Advisor check

The model advisor check is done for the model and generated report for the same. And attached the figures below.



Here I am checking only 'Modelling Standards for MAAB' task so I performed 'Run Selected Checks'.

After the check is done successfully, we see that there 0 fail as shown in the above figure.

2.5 Code Generation

Before generating code we need to set the following code generation configuration as below.


Select the build option from the menu and click on "Build Model' as shown below.


After build, the C code is generated as follows and attached report as follows:

Here I have attached sample c code as follows:


2.5 Folder which contain ACC:

The below folder has all required files and folder to implement the model.


C. Conclusion:

  1. Implemented Adaptive Cruise Control feature as per the Requirement Document using MATLAB Simulink.
  2. All MBD related processes were performed step by step. Steps like Requirement Tagging & Traceability, SLDD creation, Configuration Parameter changes, Model Advisor check & Code Generation are performed.
  3. The configuration Parameters for code generation and solvers is also set as per the objective mentioned above. Few instances are : enable “Support Floating Numbers” under Code Generation settings and set the sample time for all signals as 0.01s.
  4. Appropriate store class is assigned to each signal parameters while creating data dictionary.
  5. After developing the ACC model, run the simulation. f model is running successfully without any errors then Adaptive Cruise Control works as per the requirement. In my case, the model is running successfully without nay errors.
  6. Generated C using Embedded coder.
  7. I have attached whole folder of Adaptive cruise control feature for reference.
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