Internship | Motion Planning for Platoon Formations in Highway Scenarios

Are you interested to perform your MSc thesis project at TNO? You will design a planning algorithm for highway platooning able to perform automated emergency lane-changing maneuvers. Will your platoon formation safely navigate the highway?



Education type

university (wo)


Internship and graduation project

Hours a week

Fulltime – 40


Apply now


What will you be doing?

Automated vehicles will soon be part of our daily lives. These technologies will allow to improve traffic efficiency and safety. In recent years, extensive research effort has been dedicated to algorithms for highway platooning. Platooning strategies can significantly reduce emissions and congestions, while allowing efficient transportation of goods and passengers. Most of the state of the art focuses on the longitudinal control of the platoon formation to minimize the maneuver space (i.e., the distance between the vehicles) and the communication requirements. To fully exploit the benefits that these technologies will bring, algorithms to safely coordinate the vehicles in the platoon formation are crucial. Given the tight maneuver requirements, a delay in the communication, malfunctions, or small deviations from the planned path can compromise the safety of the entire formation. Hence, algorithms able to predict collisions and initialize emergency lane-changing maneuvers are fundamental to fully benefit of these technologies in total safety.

The main goal of this project is to devise a planning algorithm able to predict possible collisions with other vehicles in the platoon formation and consequently initialize an automated lane-changing maneuver. The path planner and path-following (lateral and longitudinal) controller of each vehicle in the platoon formation will interact to predict possible deviations from the planned path. In addition, each local planner will communicate with the other vehicles in the formation to share local intentions and to automatically plan an avoidance maneuver. The main techniques involved will be model predictive control and decomposition methods (e.g., ADMM).

Main Activities:
  1. Literature study to overview the state of the art in path planning for vehicle platoon.
  2. Define KPIs to evaluate the proposed approach and implement a baseline approach.
  3. Define the testing scenarios to evaluate and compare the proposed algorithm.
  4. Devise a path planning algorithm for automated lane-changing to prevent collisions.
  5. Evaluate the proposed method in comparison with the baseline approach in 2. in the scenarios defined in 3.

What do we require of you?

  • Background in robot motion planning and control
  • Experience with solvers such as QPOASES and IPOpt is recommended
  • Good communication in English
  • Creative and Pro-active
  • Experience with Python, MATLAB, ROS, or similar software is preferred
  • Not afraid of mathematics

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 vehicles and developed methods for testing automated vehicles. The developed software is tested in pilots and on the public road. More info on the department: 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 or she will help you to get acquainted with the department and give you guidelines for your research 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: Berend Kupers
Phone number: +31 (0)6-466 24056

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


Apply now



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