For a vehicle to function autonomously, it should be fully aware of its surroundings, own location and state. For platooning, vehicles in addition need the location and state of (at least) their predecessor. When considering both longitudinal and lateral control in platooning, this becomes even more relevant in order to avoid corner cutting.

For determining position information, sensors signals (e.g. RADAR, camera, IMU) on the ego vehicle have to be fused. One therefore needs to create an observer that fuses all relevant signals incorporating the (sometimes poor) reliability of sensor outputs. Subsequently, this needs to be combined with communicated trajectories and positions of upstream vehicles to plan a coherent path to be followed. In addition, as the path to be followed is dependent on the road layout, it should not only be coherent but also feasible. Finally, the generated path should also be tracked within the physical boundaries imposed by the road layout.

This research should answer the following two questions:

1. How to reconstruct the position information of the preceding vehicle such that it can be used for cooperative vehicle following?
2. How should the path tracking controller look like in order to achieve convergence to the path of the preceding vehicle within reasonable error bounds infinite time and to also achieve string stability?

Based on practical limitations, e.g., road layout, bounds should be determined indicating the performance of the closed loop control system. This research will make it possible to achieve real-world longitudinal and lateral cooperative driving and provides both a theoretical and practical foundation. From this, various research opportunities arise, e.g., the extension to heterogeneous platoons. By eliminating corner cutting it sets the foundations for achieving cooperative driving in urban environments, which is still an open research area.

For practical implementation, several cooperative automated vehicles are available in the Automotive Lab, which have successfully been used in cooperative driving experiments.

We are looking for a candidate who meets the following requirements:

• You are a talented and enthusiastic young researcher;
• You have MSc degree (or equivalent) in Mechanical Engineering, Electrical Engineering, Systems & Control, Automotive Technology, or a related discipline;
• You have a strong theoretical background;
• You have experience and interest in experimental work;
• You have good communication skills and the attitude to participate successfully in the work of a research team;
• You are creative, ambitious, organized, and persistent;
• You have good command of the English language (knowledge of Dutch is not required).

• A meaningful job in a dynamic and ambitious university with the possibility to present your work at international conferences;
• A full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months;
• To develop your teaching skills, you will spend 10% of your employment on teaching tasks;
• To support you during your PhD and to prepare you for the rest of your career, you will make a Training and Supervision plan and you will have free access to a personal development program for PhD students (PROOF program);
• A gross monthly salary and benefits (such as a pension scheme, pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labor Agreement for Dutch Universities;
• Additionally, an annual holiday allowance of 8% of the yearly salary, plus a year-end allowance of 8.3% of the annual salary;
• Should you come from abroad and comply with certain conditions, you can make use of the so-called '30% facility', which permits you not to pay tax on 30% of your salary;
• A broad package of fringe benefits, including an excellent technical infrastructure, moving expenses, and savings schemes;
• Family-friendly initiatives are in place, such as an international spouse program, and excellent on-campus children day care and sports facilities.