Improving Traffic Flow Prediction in Urban Areas by Incorporating a Real-Time Outlier Detection Model

In the last decennia the pressure on different types of mobility have severely increased in the Netherlands. Therefor the need for availability and reliability has increased. Siemens Mobility supplies solutions in this regard that contribute to everyday accessibility and quality of life. With the help of different technologies, data is being unlocked through which the operation of the underlying systems and therefor the provided mobility are made more transparent. This enables us to analyze and modulate these systems in a better way.

Urban Traffic flow is one of the subjects Siemens Mobility focusses on in order to provide better systems for traffic regulation, and advising the traveler on getting from A to B.

Siemens is researching a smart traffic control system that optimizes traffic flow by predicting the arrival of traffic and prioritizing the traffic flow accordingly. The prediction model within this system however is not yet perfected and less capable of handling outlier situations.
A previous graduate under my supervision has performed research on a stand-alone outlier detection model that successfully predicted the outliers of traffic on crossings within urban areas.

This assignment consists of researching whether the incorporation of an outlier detection model into the prediction model improves the system and therefor the potential traffic flow within the city? Below, you can find a very simplistic overview of the assignment’s context.

During your assignment you will be working on the real-time prediction model within the smart traffic control system. You will be coached by an experienced Siemens supervisor in the field of data science and cloud engineering. On top of that you will become part of the digital team of Siemens Mobility integrating your ideas into frontier solutions for optimizing traffic flow. Siemens is looking for an enthusiastic graduation intern that has affinity with data science and automation.


For more information, contact dr. ing. Marwan Hassani.

Graduating at Siemens Mobility

A challenging internship in a professional working environment with much room to develop yourself. You will follow an introduction program which will be your first step into the company and its wide network of people.


For Siemens, interns and graduates are important. You have the ability to let us stay sharp and show us new ideas and methods that help us grow. That’s why we take your internship- or graduation period seriously. In return we will guide you in these intense times to make sure you will not only learn the basics but help you get everything out of your time at Siemens.



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