Internship/Thesis (f/m/d) in the field of Autonomous Driving: Trajectory Optimization and Control

to be filled from:

immediately

Your working environment

At MAN Truck & Bus, we are part of a strong international team and one of Europe's leading commercial vehicle manufacturers and providers of transportation solutions. Together with the Scania, Volkswagen Truck & Bus, Navistar and RIO brands, we are part of the TRATON GROUP.
As part of this group, we face major challenges: Our vehicles are becoming increasingly autonomous and connected in order to reduce emissions on the road. We are working on sustainable solutions for this. A career at MAN Truck & Bus offers countless opportunities to participate in this change. Putting the customer first, respect, team spirit, responsibility and avoiding waste - these are the corporate values we live by at MAN.

Pull together with us. As part of our global team of over 36,000 employees, you will join us in turning visions of the future into reality.
We see the individuality of our employees as a strength and welcome diverse applications from people with different backgrounds. If you need support during your application, please contact us.

Imagine a truck driving itself and now imagine it is running using your algorithms. If this excites you, then an internship is looking for you at MAN Truck & Bus in the field of Trajectory Optimization and Control. As a part of the Vehicle Control Group, we develop control strategies for fully automated Trucks and Trailers. As a part of our group, you will develop, test and benchmark the controls in simulation and real vehicles. Our prototypes are equipped with state-of-the-art computational hardware, sensors and measurements system. A video demonstration of our work is available on our press release page. You can get some more insights using the following link https://www.mantruckandbus.com/en/innovation/driverless-in-the-port-two-autonomous-trucks-on-the-home-straight.html

The following topics summarize the task carried out by us

• We develop concepts for modeling the dynamics of commercial vehicles and the influence of disturbance variables.
• We are responsible for formulating and implementing path and trajectory optimization and control strategies.
• We tackle the challenging task of implementing and optimizing control algorithms for forward and reverse driving.
• We adapt and implement methods for various vehicle types and truck-trailer combinations.
• We design test metrics and infrastructure to validate the functions utilizing simulation and test drives on full-scale prototypes

Your Advantages

• You will gain experience working in a team and learn how to solve complex problems independently. 
• You will gain hands-on experience with rapid controller prototyping and model-based software development for embedded controllers.
• You will gain practical experience in Control Theory, Trajectory Optimization and Model Predictive Control.
• You will learn how to develop, evaluate and validate concepts for autonomous driving in Software in Loop(SiL) and Hardware in Loop (HiL).
• You will also have the possibility to evaluate your work on real vehicles, i.e., Vehicle in Loop(ViL). 
• You will learn how to design reinforcement-learning-based control strategies and machine learning methods for dynamics parameter estimation.
• You will gain experience in real-world testing and measurements.
• You can independently decide your research direction for your Thesis during the internship.

Your qualifications

• You are studying engineering or computer science.
• You bring along a high degree of independence and reliability.
• You have a professional appearance and enjoy working in a team.
• You have profound knowledge in the field of control engineering and system theory, and advantageously in the areas of vehicle dynamics/system modeling.
• You have excellent knowledge of Matlab / Simulink.
• Programming skills in C, C++ and Python are advantageous. 
• You have practical experience in control design and practical experience with automotive measurement and test engineering.
• You have first-hand experience with Optimal Control Problems(OCP), Model Predictive Control(MPC), Trajectory Optimization and Control Theory.
• Experience with Optimal Control toolboxes like Casadi, Acados and quadratic programming solvers is an advantage. 

Additional information

The work period is flexible. We can arrange the duration of the internship/thesis as per the university's requirements and guidelines. Please state the desired employment date and the work's planned duration in your cover letter.

Job information 

This position is with [[division]] in München (department EEAC (66235299)). 

Reference number: 1258 

Claudia Wünsche, claudia.wuensche@man.eu will be happy to answer any questions you may have. 

The contact person for the department is Mohit Kumar Garg, mohit.garg@man.eu

Integrity and compliance are essential parts of our corporate culture. 

We promote diversity and equal opportunities and look forward to receiving diverse applications.