Project 2 Adaptive Cruise Control

ADAPTIVE CRUISE CONTROL

AIM:

To create simulink model for adaptive cruise control with given requirements.

OBJECTIVE:

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.

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.

REQUIREMENTS:

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.

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)]

Explanation:

Steps followed are:

To make a SLDD file.

1.Open a simulink model.

2.Click Modelling and press down arrow in the design.

3.Click link to data dictionary

4.Model properties box appears.

5. Click new and add new sldd file as mini project

6.Apply and close the box

7.Click model explorer and press external data and then press design data.

8.In design data add 13 signals and edit as per the requirement

After adding all the signals,

9.After adding right click in the design data and save.

Simulink model creation:

Simulink model:

Here in the model first we create a subsystem.

Subsystem(Adaptive_Cruise_Control):

Here in the subsystem we make 3 different subsystem to create the 3 different requirements they are Lead_Vehicle, Drive_Vehicle, ACC_Algorithm.

Subsystem(Lead_Vehicle):

Here in this subsystem we use 2 inport and it is connected to the Add block, the outport is as LeadVehicle_speed.As to find out the lead vehicle speed is quite complicated,for simplicity as per the requirement 1, the input from CameraInput_LeadVehicle signal and RadarInput_LeadVehicle signal are summed up to get the LeadVehicle_Speed output.

Subsystem(Drive_Vehicle):

Here in this we use 3 inport and it is connected to the Add block, the outports here are DriveVehicle_Speed and LeadVehicle_Detected.For DriveVehicle_Speed calculation we are adding CameraInput_DriveVehicle,RadarInput_DriveVehicle and Acceleration_Mode feedback from Cruise control algorithm.The outputs from this subsystem as DriveVehicle_Speed and Lead_Vehicle_Detected by propagating RadarInput_DriveVehicle in to signal conversion block.

Subsystem(ACC_Algorithm):

In this subsystem we are using a state flow logics to implement the requirements 3a,3b,3c,3c(i),3c(ii),3c(iii),3c(iv),3c(v),3c(vi).

The inputs for the state flow are,

• Time_Gap.
• Set_Speed.
• Set_Gap.
• CruiseSwitch.
• SetSwitch.
• DriveVehicle_Speed from Requirement 2 subsystem.
• LeadVehicle_Speed from Requirement 1 subsystem.
• LeadVehicle_Detected from Requirement 2 subsystem.

The output from this subsystem is, Acceleration_Mode-Based on the LeadVehicle_Speed the Acceleration_Mode udjust its controlling accaleration given output to maintain constant speed.

State flow logic(Adaptive Cruise Control Logic):

In this logic we had created three modes of operation as,

1. ACC_OFF mode.
2. ACC_STANDBY mode.
3. ACC_ON mode.

In ACC_ON mode we have further 6 modes of operations as,

• LeadVehicle_Detected_Follow (Default).
• LeadVehicle_Not_Detected.
• LeadVehicle_Detected_Resume.
• LeadVehicle_Not_Detected_Resume.
• LeadVehicle_Speed_lessthan_Set_Speed.
• LeadVehicle_Speed_equal_Set_Speed.

All these modes of operations are modelled as per the given as mentioned in requirements section.

And here we set the symbol pane,

Requirement tagging:

A MS Word file is created which contain all the requirements and necessary information to develop the model appropiately. This Word file is tagged for both the subsystem Requirement1, Requirement2 and Requirement3 respectively.

10.Right click in the requirement 1 of the simulink model

11.Click Link to selection in word.

Similarly requirement 2 and requirement 3 is tagged with word and then it shows as,

Requirement 1

Configuration parameter:

12.Click model properties

13.Configuration parameter box appears and select the values as below,

Select type as Fixed-step, solver as discrete (no continuous states)

14.Then click code generation and browse embedded codder (ert.file)

Model advisor report generation:

15.Run the model

16.then in the top left corner select model advisor

17.A system selector box appers, select and click apply.

18.Then click By task and select Modelling standards for MAB,

19.Click run selected checks.

Here only warnings is 14 and no fails condition.

20.Now click Generate report.

Code generation:

21.Click App on the top

22.Click Build

And the code is generated as below,

CONCLUSION:

The Adaptive cruise control is designed according to the requirements. The code is generated by using embedded coder. The model is checked for MAB test using Model Advisor and report is added. The requirement blocks are linked to selection in the Word document. There are many advancements in the Adaptive cruise control like turn by turn ACC, the vehicle automatically changes the speed according to the road condition, traffic, turning and slope. It has some limitations, it is not advisable to use ACC in the Bad weather conditions such as heavy rain, storm, foggy and snowy road. These weather condition may affect the sensor output which may lead to serious damage to vehicle and driver.