Smart Street Lights

Source code:

Use Case

Our use case is related to a new Smart Lighting Infrastructure, to be more adequate for a Traffic System which directly crossroad and our wasted time on those.

The idea behind our project is to create models which should represent an actual Live Situation Crossroad. In the model there are different options creating the simulation. There are different types of vehicles like cars, Police Cars, Ambulance Cars etc. The main focus is the differentiation named “Priority”. The Priority value of each vehicle represents the vehicles urgency to leave the crossroad.

When simulated in ADOxx the vehicles are related to the crossroad via relation as “horizontal relation”  or “vertical relation”. The program calculate the sum of the priorities in both sides of the crossroad and if the difference between them is for e.g. larger than 50 than the Traffic lights will switch to green for the road with the higher priority and red for the other one. 

Scenario 1

In  the first scenario we considered the case when there are vehicles only in one part on the cross-road by they have to wait because the street light is red. After the model is simulated in ADOxx the xml file will be exported and the program will calculate the priorities and will switch the street lights.

Scenario 2

In this scenario the traffic light is green for the “horizontal street” even though there are only two cars in this street. The program will calculate the priority of the streets and after the calculation will switch the traffic lights to give the priority to the “vertical street” where the ambulance and the police care are. 

Experiment

Smart Street Light
Smart Street Light, Optimise the every day Traffic situation through simulation/modelling and algorithm.
The Experiment is based on 3 Key Steps.

1. The Smart Street Lighting System should represent a system that can calculate “Real live Traffic Situations” and respond adequately in that way in that our cars and smart cars would benefit by saving a lot of our daily time on crossroads etc


2.To represent a Real Life Situation Adoxx Is used to model and simulate different traffic crossroads problems.


3. Based on the Exported Data from Adoxx (“Xml”), The Logistic calculate the data and respond adequately.

Implementations Steps

  • 2. After the importing Part is done, we can start to create a new model by using all the assets that the library offer, that means Vehicles like: Police Car, Normal Car, Ambulance Car and then by using Streets and Crossroads. Some scenarios already modelled you can find here.
  • Important point: Give each car a Priority Value Based on Assumptions, and link all the cars to their specific position by the connectors.
  • 3. Export the model as a XML File on the desired destination where you will import it later on the java program. Important Point: Please remove this line of code on the Xml File “” Like on the video.
  • 5 .After Importing the Project in Eclipse you can see the algorithm behind the Semaphore Function, Parsing process, Calculation Process and more. Important Point: Copy Your xml Code to the resources folder on the project or just open the “Actualmodel.xml” and paste your Xml Code it and save.
  • 6. On the “PriorityCal” Java code there is a line “DIFFERENCE_INTERVAL = 50;” Which represent a imaginable limit which represent the priority tolerance between streets before that our smart System should take action and change the Action: Run the “PriorityCal” Java code
  • 7. We can see on the console all the information that we need. The Code is ready to send the end result data to your Smart Cars/ Servers / Semaphores etc. If the Tolerance level exceeds our system will take action and will change the semaphores light’s in that way in which the traffic could benefit.It’s just a small example what the Logic behind the project could do.
  • 8. Program The Omirob “Mbot” Based On the Screenshot with the Makeblock software (you can download the software here: http://www.mblock.cc/) .
  • The Mbot in our experiment simulates a just arrived Autonomous car in the crossroad
  • 9. Enjoy

Results

We can conclude that based on our simple Experiment we could save in our case approximately 2 minutes of wasted times on just a single crossroad were the chance of that scenario to happen daily could be probably 20%, to 40% on an hourly basis. So based on these statistics we can conclude that by using Smart and Intelligent Traffic lights we could save millions of unnecessarily wasted minutes on roads/crossroads if we look it from a global perspective. The Project/Code could be expanded to do many more things in the future.