Project 1- Traffic Jam Assistant Feature

Project 1- Traffic Jam Assistant Feature

Project Problem Statement:

To develop one specific requirement of the Traffic Jam Assistant algorithm which would predominantly feature in the IPC algorithm.
Please note that the whole Traffic Jam Assistant is a very huge algorithm & only one small part of the logic is implemented here.
Idea is to familiarize with concepts of Model-Based Development in a MATLAB Environment.
The Project must be done keeping in mind the following processes & steps.

• This 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 the 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 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 the 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 their 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 the press of a button.
  The vehicle will now automatically follow the vehicle in front, takes over driving off, acceleration, braking and steering within the 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.

Solution :

Requirement :

Requirement No 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 No 2 (DisplayUnit Subsystem):

• 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”.

Top most Subsystem :

1. Create the model
2. Resolve and Prapogate all the signals.
3. when we first time naming or labelling the signal its called resolving the signal.
4. By the resolving signal and const it associated with the properties of the signal which defined in sldd its linked with parameters.
5. after that its called propagation, when we again labelled its or again used in the model.
6. configured solver and code genreation settings.
7. 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 Simulink Data Dictionary (SLDD) Data:

Created a Sldd file.

• 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.

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

SLDD Screenshot :

Code Generation :

Few Configuration Settings are needed to be set in order to proceed for Code Generation, Results, etc.

Configuration Settings :

• We change the Solver Settings and Code Generation Settings in the Configuration Parameters. We dont touch Coverage Settings here as we are not interested in MIL or SIL for this Model.
• Further, during Model Advisor Checks we have to visit Configuration Parameters to eliminate the warnings shown in Model Advisor Checks.

Configuration Settings was done as per the below procedure.

Code Generation :

Now we will proceed to the Code Generation process. We have already done the settings required in the Configuration Settings shown above.

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.

MAB Report :

• 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.
• after selecting this will get two options
• 1. by product , 2nd task
• 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 in below
• Given below images shows the menu of model advisor

Given below images shows the menu of model advisor:

Result :

• Understand the given requirement and developed the MATLAB Simulink as per the MBD Guidelines.
• Code Generation Profile was done using the Embedded Coder.
• Simulink Data Dictionary was created for the model and also linked with the developed model.
• Model Advisor Report was generated and this action was carried out after Code Generation.