Job

Internship | Optimization of a target tracker using machine learning

In the development of Automated Driving, many challenges have to be dealt with. One of them is detecting and estimating the behaviour of targets in the environment. In this project, you will optimize the target tracker by using machine learning.

Location

Helmond

Education type

university (wo)

Type

Internship and graduation project

Hours a week

Fulltime – 40

Interested?

Apply now

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What will you be doing?

One area of improvement of the Target Tracker is on making it smart. This entails developing the capability of the software to “learn” based on real-life data how to configure its parameters and achieving best performance per application. Currently such a configuration procedure is manual. What this involves is:
  • Significant amount of time has to be spent, while testing with recorded real-life data.
  • The configuration procedure is prone to errors, since it requires attention to detail, examining many different use cases and achieving the best trade-off between them.
  • This procedure also requires experience with the software and the system concepts e.g. an experienced person can be more effective in this procedure than a junior.
By automating such a configuration, the Target Tracker will be more easily applicable to different applications.
At the same time, an open question is posed: “How can the Target Tracker become less parameter-dependent and thus more robust and more easily applicable to different applications? Which of these parameters are more essential for increasing performance?”

Proposed approach:
  • Implementation of a machine learning approach, suitable for the configuration procedure.
  • Training and testing with the simulation framework should be done first. A prior investigation of typical scenarios (use-cases) and environments (urban, highway application) should be carried out and these scenarios should be implemented in the simulator.
  • Recorded real-life data should be used for training and testing as well, to validate the robustness of the implemented approach.
  • The above open question should be addressed as well.

What do we require of you?

We require that you are familiar with system theory and machine learning concepts. You are knowledgeable in C++/Python or you are willing to learn. Experience with Linux and ROS is beneficial. We like you to start as soon as possible. The thesis fits to a 9 month project (based on full time availability). We require you to work in Helmond at the TNO office to enable you to work with our tools and to have short communication lines.

What can you expect of your work situation?

TNO is an independent research organisation whose expertise and research make an important contribution to the competitiveness of companies and organisations, to the economy and to the quality of society as a whole. Innovation with purpose is what TNO stands for. With 3000 people we develop knowledge not for its own sake but for practical application. To create new products that make life more pleasant and valuable and help companies innovate. To find creative answers to the questions posed by society. We work for a variety of customers: governments, companies, service providers and non-governmental organisations. Working together on new knowledge, better products and clear recommendations for policy and processes. In everything we do, impact is the key. Our product and process innovations and recommendations are only worth something if our customers can use them to boost their competitiveness.

You will work at the Integrated Vehicle Safety department of TNO on the Automotive Campus in Helmond. In this department people are working on developing software for automated driving vehicles. The developed software is tested in pilots and on the public road. (more info on the department: https://www.tno.nl/en/focus-areas/traffic-transport/expertise-groups/research-on-integrated-vehicle-safety/ ). The people are young, enthusiastic and driven. You will work in an open area, within your own team. One of our employees will be your mentor. He will help you to get acquainted with the department and give you guidelines for your research in order to help you to get the best out of it.

What can TNO offer you?

You want to work on the precursor of your career; a work placement gives you an opportunity to take a good look at your prospective future employer. TNO goes a step further. It’s not just looking that interests us; you and your knowledge are essential to our innovation. That’s why we attach a great deal of value to your personal and professional development. You will, of course, be properly supervised during your work placement and be given the scope for you to get the best out of yourself. Naturally, we provide suitable work placement compensation.

Has this vacancy sparked your interest?

Then please feel free to apply on this vacancy! For further questions don’t hesitate to contact us.

Due to Covid-19 and the consequent uncertainties and restrictions, students who are not residing in the Netherlands may currently not be able to start an internship or graduation project at TNO.


Contact: Alexis Siagkris Lekkos
Phone number: +31 (0)6-111 53961



Note that applications via email and third party applications are not taken into consideration.

Interested?

Apply now

Apply

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