Project 2 Adaptive Cruise Control

Aim :

• Developing the Adaptive Cruise Control Feature

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

Theory

Adaptive cruise control (ACC) is an active safety system that automatically controls the acceleration and braking of a vehicle. It is activated through a button on the steering wheel and canceled by the driver's braking and/or another button.

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.

Adaptive Cruise Control Simulink model :

This is the topmost system of the Adaptive Cruise Control model. where all the input and output signals are connected and resolved those signals.

Adaptive Cruise Control Subsystems :

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.

 

Signal Conversion block is used to Convert a signal to a new type without altering signal values.

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 are 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.

Here in that states are created as ACC_OFF mode, ACC_STANDBY mode, ACC_ON mode, and also transitions are created as per given conditions 

Creation of Simulink Data Dictionary File :

SLDD file is created to store the calibrated data and signals. In that file Storage Class for input and output signals are ImportExtern and ExportToFile respectively.

 

Tagging the system requirement to the word file :

 

Model Advisor checks :

code generation settings

Results:

After implementing all the requirements of Adaptive Cruise Control (ACC) in the Simulink model and running the simulation. if the model is running as per successfully the requirement without any error then we can say that model works as per the requirements.

model is running without any error.

Conclusion:

we modeled the Adaptive Cruise Control (ACC) feature as per the requirements using the Matlab Simulink