Project 1- Traffic Jam Assistant Feature

AIM: To develop Traffic jam assistant algorithm bases on the requirement document

OBJECTIVES:

• Model must be developed in MATLAB Simulink as per MBD guidelines.
• Code Generation Profile must be in Embedded Coder.
• Simulink Data Dictionary must be created for the model & must be linked to the model.
• Model Advisor Report is mandatory & this will be followed by Code Generation.

 

Introduction to the Feature:

Traffic Jam Assistant is one of the most common features in Advanced Driver Assistance System. Traffic Jam Assistant helps the driver arrive more relaxed at their destination, even in dense traffic or in traffic jams. As a partially automated comfort function, the system takes over the longitudinal & lateral guidance of the vehicle. This means that the car can drive off, accelerate & brake automatically, as well as steer the vehicle within certain constraints. The driver has to permanently supervise the system & be ready to take over the complete control of the vehicle at any time.

Traffic Jam Assistant system helps to avoid rear end collisions in dense traffic conditions & traffic jams. In Traffic jams, the vehicle takes over driving off, acceleration, braking and steering within same lane.

Basic Working Principle:

Traffic Jam Assistant is based on the sensors and the functionality of the Adaptive Cruise Control (ACC) with stop & go and Lane Keeping Support (LKS). When ACC ‘Stop & Go’ is turned ON, the Traffic Jam Assistant continuously analyses the speed of the surrounding vehicles and compares it with the own driving speed. If the system detects dense traffic or a traffic jam at speeds less than 60 kmph, the driver can activate the functionality by press of a button. The vehicle will now automatically follow the vehicle in front, takes over driving off, acceleration, braking and steering within same lane.

Information regarding the Traffic Jam Assistant will be available to be displayed to the driver in the Instrument Panel Cluster (IPC). The Algorithm which the students need to implement here in this project is predominantly based on IPC units.

Configuration parameters setting:

We have chosen Fixed type solve selection and sample time as 0.01

              

Chosen Embedded coder for code generation

              

 

Final Model:

               

          

Requirement:1

• Input Signal “Input_Voltage” is compared against voltage values “VOLTAGE_MINIMUM_RANGE” & “VOLTAGE_MAXIMUM_RANGE”.
• Incoming input signal “Input_Voltage” must be greater than – equal to “VOLTAGE_MINIMUM_RANGE” and less than – equal to “VOLTAGE_MAXIMUM_RANGE”.
• Output signal from here is “Optimum_Voltage” which will be one of the inputs to the subsystem “DisplayUnit”.

              

           

Requirement:2 Display Unit:

• Input Signals are “Optimum_Voltage”, “Input_Switch”, “Enable_Display”. Signal “Enable_Display” must be saturated between the range 0 – 7. Output signal from the subsystem is “Output_Display”.
• Input Signal “Enable_Display” is compared against pre – defined set of values in a multiport switch. Total data ports in the multiport switch is 5.
• Multiport switch inputs 1 & 2 is connected to calibration signal “ON_MODE”, Multiport switch inputs 3 & 4 is connected to calibration signal “OFF_MODE” while Multiport switch input 5 is connected to calibration signal “STANDBY_MODE”.
• The output from Multiport switch is connected to the first input port of the Switch block. The third input port of the Switch block is connected to the calibration signal “NO_DISPLAY”.
• Meanwhile NOT value of input signal “Input_Switch” is compared in an AND gate against input signal “Optimum_Voltage” and the output from comparing if calibration signals “INTERRUPT_1” & “INTERRUPT_2” are equal. The output of the AND gate is the second input of the switch block.
• The output from the switch block is “Output_Display”.

 

             

          

 Creating Simulink Data Dictionary (sldd) file:

The Simulink data dictionary is created by selecting the modelling in the top pane and select link to data dictionary > Then the window pops up select create new and name the data dictionary file and apply > open the data dictionary in the model explorer in the modelling of the top pane. Add the signals and name and configure the input and output signals.

• Storage class of the input signal must be imported extern for the code generation.
• Storage class of the output signal must be Export to file for code generation.
• Storage class of the local signal must be Localizable for code generation.
• Calibration signals are added as parameters in the data dictionary and storage class of calibration signal must be Const for code generation.

Input Signals:

Name of the Signal	Data Type	Range
Input_Voltage	uint8	0 - 255
Input_Switch	boolean	0 – 1
Enable_Display	uint8	0 - 255

Output Signal:

Name of the Signal	Data Type	Range
Output_Display	uint8	0 - 255

Calibration Signals:

Name of the Signal	Data Type	Range	Initial Value
VOLTAGE_MINIMUM_RANGE	uint8	0 – 255	30
VOLTAGE_MAXIMUM_RANGE	uint8	0 – 255	50
OFF_MODE	uint8	0 – 255	2
ON_MODE	uint8	0 – 255	1
STANDBY_MODE	uint8	0 – 255	3
INTERRUPT_1	boolean	0 – 1	1
INTERRUPT_2	boolean	0 - 1	1
NO_DISPLAY	uint8	0 – 255	0

Local Signal:

Name of the Signal	Data Type	Range
Optimum_Voltage	boolean	0 - 1

            

Then the signal name in the model must be link to data dictionary by right clicking the signal and open properties. In that select Resolve to Simulink data objects and apply.

Resolving and Propagating the Signals:

Initially resolve the Input and Output signals and Propagate the respected subsystem signals as shown below.

               

             

         

 Model Advisor Check:

We will check the model according to the MAAB guidelines. Click on Modelling option and chose Model advisor as shown below

             

 

Now check the box of Modelling Standards of MAB in the By task option as shown below click on Run selected check

             

So, there are no errors in the model as per the MAAB guidelines we can clearly observe below.

              

Model Advisor Check Report:

             

Code Generation:

In the top pane select apps and select the embedded coder > click on Build

           

           

Generated Code and the Report is shown below

             

            

CONCLUSION:

Hence, Traffic jam assistant algorithm model is been developed in MATLAB Simulink as per MBD guidelines. Code Generation Profile is set as Embedded Coder. Simulink Data Dictionary is created for the model & linked to the model. Model Advisor check is done according to the MAAB guidelines and regenerated the Report. Finally, Code is Generated. Respective Files are attached.